Webservice-Energy (WMS)

WMS Webservice-Energy (WMS) A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS WFS WMS GEOSERVER Lionel MENARD MINES ParisTech Research Engineer Work

1, rue Claude Daunesse - CS 10207

SOPHIA ANTIPOLIS 06904 FRANCE lionel.menard@mines-paristech.fr NONE NONE text/xml image/png application/atom+xml application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html application/json XML INIMAGE BLANK JSON Webservice-Energy (WMS) A compliant implementation of WMS plus most of the SLD extension (dynamic styling). Can also generate PDF, SVG, KML, GeoRSS AUTO:42001 AUTO:42002 AUTO:42003 AUTO:42004 AUTO:97001 AUTO:97002 AUTO:97003 AUTO:97004 CRS:27 CRS:83 CRS:84 EPSG:2000 EPSG:2001 EPSG:2002 EPSG:2003 EPSG:2004 EPSG:2005 EPSG:2006 EPSG:2007 EPSG:2008 EPSG:2009 EPSG:2010 EPSG:2011 EPSG:2012 EPSG:2013 EPSG:2014 EPSG:2015 EPSG:2016 EPSG:2017 EPSG:2018 EPSG:2019 EPSG:2020 EPSG:2021 EPSG:2022 EPSG:2023 EPSG:2024 EPSG:2025 EPSG:2026 EPSG:2027 EPSG:2028 EPSG:2029 EPSG:2030 EPSG:2031 EPSG:2032 EPSG:2033 EPSG:2034 EPSG:2035 EPSG:2036 EPSG:2037 EPSG:2038 EPSG:2039 EPSG:2040 EPSG:2041 EPSG:2042 EPSG:2043 EPSG:2044 EPSG:2045 EPSG:2046 EPSG:2047 EPSG:2048 EPSG:2049 EPSG:2050 EPSG:2051 EPSG:2052 EPSG:2053 EPSG:2054 EPSG:2055 EPSG:2056 EPSG:2057 EPSG:2058 EPSG:2059 EPSG:2060 EPSG:2061 EPSG:2062 EPSG:2063 EPSG:2064 EPSG:2065 EPSG:2066 EPSG:2067 EPSG:2068 EPSG:2069 EPSG:2070 EPSG:2071 EPSG:2072 EPSG:2073 EPSG:2074 EPSG:2075 EPSG:2076 EPSG:2077 EPSG:2078 EPSG:2079 EPSG:2080 EPSG:2081 EPSG:2082 EPSG:2083 EPSG:2084 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EPSG:66056405 EPSG:66066405 EPSG:66076405 EPSG:66086405 EPSG:66096405 EPSG:66106405 EPSG:66116405 EPSG:66126405 EPSG:66126413 EPSG:66136405 EPSG:66146405 EPSG:66156405 EPSG:66166405 EPSG:66186405 EPSG:66196405 EPSG:66196413 EPSG:66206405 EPSG:66216405 EPSG:66226405 EPSG:66236405 EPSG:66246405 EPSG:66246413 EPSG:66256405 EPSG:66266405 EPSG:66276405 EPSG:66276413 EPSG:66286405 EPSG:66296405 EPSG:66306405 EPSG:66316405 EPSG:66326405 EPSG:66336405 EPSG:66346405 EPSG:66356405 EPSG:66366405 EPSG:66376405 EPSG:66386405 EPSG:66396405 EPSG:66406405 EPSG:66406413 EPSG:66416405 EPSG:66426405 EPSG:66436405 EPSG:66446405 EPSG:66456405 EPSG:66456413 EPSG:66466405 EPSG:66576405 EPSG:66586405 EPSG:66596405 EPSG:66596413 EPSG:66606405 EPSG:66616405 EPSG:66616413 EPSG:66636405 EPSG:66646405 EPSG:66656405 EPSG:66666405 EPSG:66676405 EPSG:68016405 EPSG:68026405 EPSG:68036405 EPSG:68046405 EPSG:68056405 EPSG:68066405 EPSG:68086405 EPSG:68096405 EPSG:68136405 EPSG:68146405 EPSG:68156405 EPSG:68186405 EPSG:68206405 EPSG:69036405 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 paca:PACA-Aggregate PACA Maps Aggregation This is an aggregated map of the PACA region layers. EPSG:4326 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_05 ATLAS_PACA_BTI_05 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 225.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_05 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DISTRICT_DIVISION_EPSG_4326_SHP ATLAS_PACA_DISTRICT_DIVISION_EPSG_4326_SHP Shapefile of the districts in the region Provence-Alpes-Cote d'Azur (PACA) Extracted from the GEOFLA products of IGN, the Frence institute of geography features ATLAS_PACA_DISTRICT_DIVISION_EPSG_4326 EPSG:4326 CRS:84 4.230271799999996 7.718399999999987 42.9818114999999 45.12685389999994 mapserv:1-Tanger-Tetouan 1-Tanger-Tetouan features 1-Tanger-Tetouan EPSG:4326 CRS:84 -6.250138999999933 -4.4526389999999765 34.714576000000136 35.922638000000006 mapserv:10-Tadla-Azilal 10-Tadla-Azilal features 10-Tadla-Azilal EPSG:4326 CRS:84 -7.2664069999999015 -5.500705999999923 31.356558000000007 32.765398000000005 mapserv:11-Souss-Massa-Draa 11-Souss-Massa-Draa features 11-Souss-Massa-Draa EPSG:4326 CRS:84 -10.439818999999943 -5.117640999999992 29.03186900000003 32.03419300000007 mapserv:12-Marrakech-Tensift-Haouz 12-Marrakech-Tensift-Haouz features 12-Marrakech-Tensift-Haouz EPSG:4326 CRS:84 -9.842359999999928 -6.975689999999986 30.80919399999999 32.815728000000036 mapserv:13-Doukkala-Abda 13-Doukkala-Abda features 13-Doukkala-Abda EPSG:4326 CRS:84 -9.435415999999975 -7.932388999999944 31.69379799999996 33.45847300000008 mapserv:14-Guelmim-Es-Semara 14-Guelmim-Es-Semara 14-Guelmim-Es-Semara features EPSG:4326 CRS:84 -12.577548999999976 -6.374502999999947 25.994252000000017 30.41250599999995 mapserv:15-Laayoune-Boujdour-Sakia-Hamra 15-Laayoune-Boujdour-Sakia-Hamra features 15-Laayoune-Boujdour-Sakia-Hamra EPSG:4326 CRS:84 -15.000415999999973 -11.478849999999909 24.39006000000012 28.215139000000022 mapserv:16-Oued-Eddahab-Lagouira 16-Oued-Eddahab-Lagouira features 16-Oued-Eddahab-Lagouira EPSG:4326 CRS:84 -17.105415999999934 -12.0 20.76958200000007 24.58723500000002 mapserv:2-Taza-Hoceima-Taounate 2-Taza-Hoceima-Taounate features 2-Taza-Hoceima-Taounate EPSG:4326 CRS:84 -5.488778999999965 -2.9459079999999744 33.56939700000004 35.26208500000001 mapserv:3-Mont-Rif-Tazghine 3-Mont-Rif-Tazghine features 3-Mont-Rif-Tazghine EPSG:4326 CRS:84 -4.059117999999955 -0.9974059999998985 31.709694000000013 35.440139999999985 mapserv:4-Gharb-Ghrarda-Beni-Hsen 4-Gharb-Ghrarda-Beni-Hsen features 4-Gharb-Ghrarda-Beni-Hsen EPSG:4326 CRS:84 -6.7118639999999345 -5.146657999999945 34.095649000000094 34.98803100000009 mapserv:5-Fes-Boulmane 5-Fes-Boulmane features 5-Fes-Boulmane EPSG:4326 CRS:84 -5.43361699999997 -2.969073999999921 32.62382100000008 34.32542700000005 mapserv:6-Rabat-Sale-Zemmour-Zaer 6-Rabat-Sale-Zemmour-Zaer features 6-Rabat-Sale-Zemmour-Zaer EPSG:4326 CRS:84 -7.126805999999931 -5.744724999999903 33.142079000000024 34.18736300000012 mapserv:7-Meknes-Tafilalet 7-Meknes-Tafilalet features 7-Meknes-Tafilalet EPSG:4326 CRS:84 -6.397847999999897 -3.2439829999999574 30.00613000000004 34.268013999999994 mapserv:8-Grand-Casablanca 8-Grand-Casablanca features 8-Grand-Casablanca EPSG:4326 CRS:84 -7.8948559999999475 -7.345587999999907 33.319427000000076 33.73430600000012 mapserv:9-Chaouia-Ourdigha 9-Chaouia-Ourdigha features 9-Chaouia-Ourdigha EPSG:4326 CRS:84 -8.123165999999912 -5.999924999999962 32.34926400000006 33.830418000000066 paca:ATLAS_PACA_ASPECT_SRTM_EPSG_4326_r32 ATLAS_PACA_ASPECT_SRTM_EPSG_4326_r32 Local azimuth (degree) of the Digital Elevation Model extracted from SRTMv4 (http://www.cgiar-csi.org/category/elevation/) WCS GeoTIFF ATLAS_PACA_ASPECT_SRTM_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_01 ATLAS_PACA_BTI_01 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 0.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_01 geossDataCore EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_02 ATLAS_PACA_BTI_02 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_02 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_03 ATLAS_PACA_BTI_03 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_03 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_04 ATLAS_PACA_BTI_04 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 90.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_04 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_06 ATLAS_PACA_BTI_06 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 270.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_06 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_07 ATLAS_PACA_BTI_07 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 0.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_07 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_08 ATLAS_PACA_BTI_08 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 35.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_08 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_BTI_12 ATLAS_PACA_BTI_12 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Irradiation on Tilted plan (slope = 45.0 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_BTI_12 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DEM_SRTM_EPSG_4326_r32 ATLAS_PACA_DEM_SRTM_EPSG_4326_r32 Digital Elevation Model extracted from SRTMv4 (http://www.cgiar-csi.org/data/elevation/item/45-srtm-90m-digital-elevation-database-v41) WCS GeoTIFF ATLAS_PACA_DEM_SRTM_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DISTRICT_DIVISION_EPSG_4326_16b ATLAS_PACA_DISTRICT_DIVISION_EPSG_4326_16b Map of the district divisions for the solar atlas of Provence-Alpes-Cote d''Azur (PACA) It comprises the 964 districts of PACA with a surrounding margin of 4 km. It has been created from the product GEOFLA of IGN, the french institute of geography (http://professionnels.ign.fr/ficheProduitCMS.do?idDoc=5323861) WCS GeoTIFF EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DNI ATLAS_PACA_DNI Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Beam Normal Irradiation in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DNI EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DNI_EPSG_4326_8b ATLAS_PACA_DNI_EPSG_4326_8b WCS GeoTIFF ATLAS_PACA_DNI_EPSG_4326_8b EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_01 ATLAS_PACA_DTI_01 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 0.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_01 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_02 ATLAS_PACA_DTI_02 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_02 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_03 ATLAS_PACA_DTI_03 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_03 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_04 ATLAS_PACA_DTI_04 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 90.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_04 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_05 ATLAS_PACA_DTI_05 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 225.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_05 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_06 ATLAS_PACA_DTI_06 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 270.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_06 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_07 ATLAS_PACA_DTI_07 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 0.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_07 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_08 ATLAS_PACA_DTI_08 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 35.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_08 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_DTI_12 ATLAS_PACA_DTI_12 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Diffuse Irradiation on Tilted plan (slope = 45.0 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_DTI_12 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_01 ATLAS_PACA_GTI_01 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 0.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_01 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 mapserv:ATLAS_PACA_GTI_01_MEAN_YEAR ATLAS_PACA_GTI_01_MEAN_YEAR ATLAS_PACA_GTI_01_MEAN_YEAR WCS GeoTIFF EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_02 ATLAS_PACA_GTI_02 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_02 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_03 ATLAS_PACA_GTI_03 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_03 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_04 ATLAS_PACA_GTI_04 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 90.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_04 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_05 ATLAS_PACA_GTI_05 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 225.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_05 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_06 ATLAS_PACA_GTI_06 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 270.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_06 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_07 ATLAS_PACA_GTI_07 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 16.7 deg, azimuth = 0.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_07 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_08 ATLAS_PACA_GTI_08 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 35.0 deg, azimuth = 180.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_08 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_GTI_12 ATLAS_PACA_GTI_12 Solar Atlas of Provence-Alpes-Cte d'Azur: mean of yearly sum of Global Irradiation on Tilted plan (slope = 45.0 deg, azimuth = 135.0 deg) in kWh/m^2 (2004-2010) WCS GeoTIFF ATLAS_PACA_GTI_12 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_LAND_USE_CLC2006_EPSG_4326_8b ATLAS_PACA_LAND_USE_CLC2006_EPSG_4326_8b Raster data on land cover from the CLC2006 inventory, extracted for Provence-Alpes-Cote d'Azur. Data categorized using the 44 classes of the 3-level Corine nomenclature Extracted with the wms request: http://sd1878-2.sivit.org/geoserver/wms?SERVICE=WMS&VERSION=1.3.0&REQUEST=GetMap&BBOX=3.91625,42.916667,8.01625,45.416667&LAYERS=topp:RCLC06_WGS&CRS=EPSG:4326&FORMAT=image/geotiff 8&WIDTH=1640&HEIGHT=1500 WCS GeoTIFF EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MASK_EPSG_4326_8b ATLAS_PACA_MASK_EPSG_4326_8b Binary mask for the solar atlas of Provence-Alpes-Cote d'Azur (PACA) It comprises the five territorial regions of PACA with a surrounding margin of 4 km WCS GeoTIFF EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 Max temperature of the month 01 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 Max temperature of the month 02 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 Max temperature of the month 03 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 Max temperature of the month 04 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 Max temperature of the month 05 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 Max temperature of the month 06 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 Max temperature of the month 07 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 Max temperature of the month 08 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 Max temperature of the month 09 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 Max temperature of the month 10 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 Max temperature of the month 11 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MAX_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 ATLAS_PACA_MAX_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 Max temperature of the month 12 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MAX_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 Mean temperature of the month 01 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 Mean temperature of the month 02 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 Mean temperature of the month 03 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 Mean temperature of the month 04 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 Mean temperature of the month 05 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 Mean temperature of the month 06 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 Mean temperature of the month 07 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 Mean temperature of the month 08 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 Mean temperature of the month 09 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 Mean temperature of the month 10 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 Mean temperature of the month 11 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 Mean temperature of the month 12 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MEAN_TEMPERATURE_MSG_UNIGE_EPSG_4326_r32 ATLAS_PACA_MEAN_TEMPERATURE_MSG_UNIGE_EPSG_4326_r32 Description: Map of estimated mean daytime air temperature at 2-m height [Degree C], August 30, 2009, PACA Region. The layer was generated from input satellite MSG-SEVIRI images (provided by EUMETSAT) and in-situ temperature measurements (collected by Meteo France and provided by ARMINES) through the application of a supervised regression techique based on support vector machines (SVM). Hourly MSG-SEVIRI images acquired between 8 am and 5 pm were used. For each pixel, first air temperature was separately estimated from each hourly MSG-SEVIRI observation not affected by cloud cover, and, then, the mean of the resulting estimates was displayed in the present layer. Pixels in which cloud cover was present at all observation times and sea areas were masked out. Scientific reference: G. Moser and S. B. Serpico. WCS GeoTIFF ATLAS_PACA_MEAN_TEMPERATURE_MSG_UNIGE_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 Min temperature of the month 01 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH01_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 Min temperature of the month 02 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH02_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 Min temperature of the month 03 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH03_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 Min temperature of the month 04 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH04_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 Min temperature of the month 05 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH05_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 Min temperature of the month 06 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH06_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 Min temperature of the month 07 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH07_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 Min temperature of the month 08 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH08_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 Min temperature of the month 09 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH09_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 Min temperature of the month 10 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH10_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 Min temperature of the month 11 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH11_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_MIN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 ATLAS_PACA_MIN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 Min temperature of the month 12 extracted from the webservice EMPClimate (http://www.webservice-energy.org/web-services/w3c-web-services/emp-climate-w3c) WCS GeoTIFF ATLAS_PACA_MIN_TEMPERATURE_MONTH12_NCEP_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_SLOPE_SRTM_EPSG_4326_r32 ATLAS_PACA_SLOPE_SRTM_EPSG_4326_r32 Local slope in % (atan of the slope angle) of the Digital Elevation Model extracted from SRTMv4 (http://www.cgiar-csi.org/data/elevation/item/45-srtm-90m-digital-elevation-database-v41) WCS GeoTIFF ATLAS_PACA_SLOPE_SRTM_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_r32 ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_r32 Distance to the nearest electric source point (km) (from scanned map of ErDF) WCS GeoTIFF ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_shp ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_shp features ATLAS_PACA_SOURCE_POINTS_DISTKM_EPSG_4326_shp EPSG:4326 CRS:84 4.107525 7.802474999999999 42.188358333057494 45.8833083330575 paca:ATLAS_PACA_STD_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 ATLAS_PACA_STD_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 WCS GeoTIFF ATLAS_PACA_STD_TEMPERATURE_MODIS_UNIGE_EPSG_4326_r32 EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_TERRITORIAL_DIVISION_EPSG_4326_8b ATLAS_PACA_TERRITORIAL_DIVISION_EPSG_4326_8b Map of the territorial divisions for the solar atlas of Provence-Alpes-Cote d'Azur (PACA) It comprises the six territorial regions of PACA with a surrounding margin of 4 km It has been created from the product GEOFLA of IGN, the French institute of geography (http://professionnels.ign.fr/ficheProduitCMS.do?idDoc=5323861) WCS GeoTIFF EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_TERRITORIAL_DIVISION_EPSG_4326_SHP ATLAS_PACA_TERRITORIAL_DIVISION_EPSG_4326_SHP Shapefile of the territorial divisions for the solar atlas of Provence-Alpes-Cote d'Azur (PACA). It comprises the six territorial regions of PACA with a surrounding margin of 4 km features ATLAS_PACA_TERRITORIAL_DIVISION_EPSG_4326 EPSG:4326 CRS:84 4.230283393392478 7.716127328151047 42.9820330559485 45.1268479138663 paca:ATLAS_PACA_WINDSPEED_10M_CLASSES_EPSG_4326_8b ATLAS_PACA_WINDSPEED_10M_CLASSES_EPSG_4326_8b WCS GeoTIFF ATLAS_PACA_WINDSPEED_10M_CLASSES_EPSG_4326_8b EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_ZONE_FLOOD_RISK_EPSG_4326_8b ATLAS_PACA_ZONE_FLOOD_RISK_EPSG_4326_8b Map of flood risks (Atlas Zone Inondable validé) extracted from the GIS CARMEN (DREAL - PACA). (http://carmen.developpement-durable.gouv.fr/25/environnement.map) WCS GeoTIFF ATLAS_PACA_ZONE_FLOOD_RISK_EPSG_4326_8b_geo EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 paca:ATLAS_PACA_ZONE_NATURE_RESERVES_EPSG_4326_8b ATLAS_PACA_ZONE_NATURE_RESERVES_EPSG_4326_8b Map of natural reserves (Parc National" + "Réserve naturelle nationale" + "Réserve naturelle régionale" + "Parc naturel régional") extracted from the GIS CARMEN (DREAL - PACA). (http://carmen.developpement-durable.gouv.fr/25/environnement.map) WCS GeoTIFF ATLAS_PACA_ZONE_NATURE_RESERVES_EPSG_4326_8b_geo EPSG:4326 CRS:84 3.91625 8.01625 42.916666666166996 45.416666666667 marine:Average_value_of_current_power Average value of current power Map of averaged values of depth-averaged current power. Information was produced using a 5-year time series extracted from Homere sea state hindcast (Boudière et al. 2013, Boudière et al. 2014). References: E. Boudière, C. Maisondieu, F. Ardhuin, M. Accensi, L. Pineau-Guillou, and J. Lepesqueur, “A suitable metocean hindcast database for the design of Marine energy converters,” International Journal of Marine Energy, vol. 3–4, pp. e40–e52, Dec. 2013. E. Boudière and C. Maisondieu, “Manuel de l’utilisateur de la base de données HOMERE,” 2014. WCS GeoTIFF MeanPowerCurrent Current Climatology Marine Energy EPSG:4326 CRS:84 -4.8992109298706055 -4.3382109298706055 48.000179290771484 48.329179290771485 marine:Average_value_of_significant_wave_height Average value of significant wave height Average value of Hs Abstract : Map of averaged values of significant wave height (Hs). Information was produced using a 5-year time series extracted from Homere sea state hindcast (Boudière et al. 2013, Boudière et al. 2014). References: E. Boudière, C. Maisondieu, F. Ardhuin, M. Accensi, L. Pineau-Guillou, and J. Lepesqueur, “A suitable metocean hindcast database for the design of Marine energy converters,” International Journal of Marine Energy, vol. 3–4, pp. e40–e52, Dec. 2013. E. Boudière and C. Maisondieu, “Manuel de l’utilisateur de la base de données HOMERE,” 2014. WCS GeoTIFF Hs_Annual Wave Climatology Marine Energy EPSG:4326 CRS:84 -4.8992109298706055 -4.3382109298706055 48.000179290771484 48.329179290771485 marine:Average_value_of_wave_energy_period_Te Average value of wave energy period (Te) Map of averaged values of wave energy period. Information was produced using a 5-year time series extracted from Homere sea state hindcast (BoudiËre et al. 2013, BoudiËre et al. 2014). References: E. BoudiËre, C. Maisondieu, F. Ardhuin, M. Accensi, L. Pineau-Guillou, and J. Lepesqueur, ìA suitable metocean hindcast database for the design of Marine energy converters,î International Journal of Marine Energy, vol. 3ñ4, pp. e40ñe52, Dec. 2013. E. BoudiËre and C. Maisondieu, ìManuel de líutilisateur de la base de donnÈes HOMERE,î 2014. WCS GeoTIFF Te_Annual Wave Climatology Marine Energy EPSG:4326 CRS:84 -4.8992109298706055 -4.3382109298706055 48.000179290771484 48.329179290771485 marine:Average_value_of_wave_power_density_Te Average value of wave power density (Te) Map of averaged values of wave power density. Information was produced using a 5-year time series extracted from Homere sea state hindcast (Boudière et al. 2013, Boudière et al. 2014). References: E. Boudière, C. Maisondieu, F. Ardhuin, M. Accensi, L. Pineau-Guillou, and J. Lepesqueur, “A suitable metocean hindcast database for the design of Marine energy converters,” International Journal of Marine Energy, vol. 3–4, pp. e40–e52, Dec. 2013. E. Boudière and C. Maisondieu, “Manuel de l’utilisateur de la base de données HOMERE,” 2014. WCS GeoTIFF WavePower_Annual Wave Climatology Marine Energy EPSG:4326 CRS:84 -4.8992109298706055 -4.3382109298706055 48.000179290771484 48.329179290771485 mapserv:BNI_y_min1109_max1815_geo BNI_y_min1109_max1815_geo Yearly sum DNI PACA BNI_y_min1109_max1815_geo WCS GeoTIFF EPSG:4326 CRS:84 4.0 8.002777777778098 45.5 48.502222222223274 cams_jade:CAMS_JADE_monthly_GHI_2005_01 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Jan 2005 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa computed with McClear version 3 and CAMS radiation bias correction - CAMS project For more info: <a href="http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume">http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume</a> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_01 Copernicus CAMS ARMINES MINES ParisTech Transvalor Solar Energy Solar Radiation EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_02 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Fev 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_02 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_03 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Mar 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_03 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_04 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Apr 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_04 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_05 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa May 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_05 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_06 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Jun 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_06 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_07 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Jul 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_07 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_08 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Aug 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_08 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_09 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Sep 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_09 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_10 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Oct 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_10 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_11 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Nov 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_11 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_monthly_GHI_2005_12 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa Dec 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_monthly_GHI_2005_12 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 cams_jade:CAMS_JADE_yearly_GHI_2005 Global Horizontal Irradiance (GHI) from Copernicus Atmosphere Monitoring Service (CAMS) radiation service dataset "JADE" over Africa year 2005 http://www.soda-pro.com/help/cams-services/cams-radiation-service/download-africa-volume ]]> WCS GeoTIFF CAMS_JADE_yearly_GHI_2005 EPSG:4326 CRS:84 -20.1 54.1 -37.1 40.1 mapserv:Chaouia-Ourdigha_BNI Chaouia-Ourdigha_BNI Chaouia-Ourdigha_BNI WCS VRT EPSG:4326 CRS:84 -8.12317 -5.9999278 32.34924598 33.8304 mapserv:Chaouia-Ourdigha_GHI Chaouia-Ourdigha_GHI Chaouia-Ourdigha_GHI WCS VRT EPSG:4326 CRS:84 -8.12317 -5.9999278 32.34924598 33.8304 mapserv:Chaouia-Ourdigha_vent Chaouia-Ourdigha_vent Chaouia-Ourdigha_vent WCS VRT EPSG:4326 CRS:84 -8.12317 -5.999933199999999 32.349244199999994 33.8304 mapserv:DNI_MoyMensuelle_kWhm-2_geotiff DNI_MoyMensuelle_kWhm-2_geotiff DNI_MoyMensuelle_kWhm-2_geotiff WCS GeoTIFF EPSG:4326 CRS:84 -16.75 45.083086 55.916667 75.99992 mapserv:Doukkala-Abda_BNI Doukkala-Abda_BNI Doukkala-Abda_BNI WCS VRT EPSG:4326 CRS:84 -9.43542 -7.932393 31.693824720000002 33.4585 mapserv:Doukkala-Abda_GHI Doukkala-Abda_GHI Doukkala-Abda_GHI WCS VRT EPSG:4326 CRS:84 -9.43542 -7.932393 31.693824720000002 33.4585 mapserv:Doukkala-Abda_vent Doukkala-Abda_vent Doukkala-Abda_vent WCS VRT EPSG:4326 CRS:84 -9.43542 -7.932393 31.6938226 33.4585 energeo_pia:Europe_life_expectancies Europe_life_expectancies WCS GeoTIFF Europe_life_expectancies EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 mapserv:Fes-Boulmane_BNI Fes-Boulmane_BNI Fes-Boulmane_BNI WCS VRT EPSG:4326 CRS:84 -5.43362 -2.96907664 32.623793160000005 34.3254 mapserv:Fes-Boulmane_GHI Fes-Boulmane_GHI Fes-Boulmane_GHI WCS VRT EPSG:4326 CRS:84 -5.43362 -2.96907664 32.623793160000005 34.3254 mapserv:Fes-Boulmane_vent Fes-Boulmane_vent Fes-Boulmane_vent WCS VRT EPSG:4326 CRS:84 -5.43362 -2.9690796000000006 32.6237952 34.3254 energeo_pia_2013:GAINS_BIO_CLE_O3_2005_LLE1 GAINS_BIO_CLE_O3_2005_LLE1 WCS GeoTIFF 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CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_CLE_O3_2050_LLE2 GAINS_BIO_CLE_O3_2050_LLE2 WCS GeoTIFF GAINS_BIO_CLE_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_CLE_PM25_2005_LLE_doll1 GAINS_BIO_CLE_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (CLE) WCS GeoTIFF GAINS_BIO_CLE_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_CLE_PM25_2005_LLE_doll2 GAINS_BIO_CLE_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (CLE) WCS GeoTIFF GAINS_BIO_CLE_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_CLE_PM25_2005_LLE_yoll1 GAINS_BIO_CLE_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (CLE) WCS GeoTIFF GAINS_BIO_CLE_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_CLE_PM25_2005_LLE_yoll2 GAINS_BIO_CLE_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (CLE) WCS GeoTIFF GAINS_BIO_CLE_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2005_LLE1 GAINS_BIO_MFR_O3_2005_LLE1 WCS GeoTIFF GAINS_BIO_MFR_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2005_LLE2 GAINS_BIO_MFR_O3_2005_LLE2 WCS GeoTIFF GAINS_BIO_MFR_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2030_LLE1 GAINS_BIO_MFR_O3_2030_LLE1 WCS GeoTIFF GAINS_BIO_MFR_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2030_LLE2 GAINS_BIO_MFR_O3_2030_LLE2 WCS GeoTIFF GAINS_BIO_MFR_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2040_LLE1 GAINS_BIO_MFR_O3_2040_LLE1 WCS GeoTIFF GAINS_BIO_MFR_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2040_LLE2 GAINS_BIO_MFR_O3_2040_LLE2 WCS GeoTIFF GAINS_BIO_MFR_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2050_LLE1 GAINS_BIO_MFR_O3_2050_LLE1 WCS GeoTIFF GAINS_BIO_MFR_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_O3_2050_LLE2 GAINS_BIO_MFR_O3_2050_LLE2 WCS GeoTIFF GAINS_BIO_MFR_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_PM25_2005_LLE_doll1 GAINS_BIO_MFR_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (MTFR) WCS GeoTIFF GAINS_BIO_MFR_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_PM25_2005_LLE_doll2 GAINS_BIO_MFR_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (MTFR) WCS GeoTIFF GAINS_BIO_MFR_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_PM25_2005_LLE_yoll1 GAINS_BIO_MFR_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (MTFR) WCS GeoTIFF GAINS_BIO_MFR_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BIO_MFR_PM25_2005_LLE_yoll2 GAINS_BIO_MFR_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Open Europe scenario (MTFR) WCS GeoTIFF GAINS_BIO_MFR_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2005_LLE1 GAINS_BL_CLE_O3_2005_LLE1 WCS GeoTIFF GAINS_BL_CLE_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2005_LLE2 GAINS_BL_CLE_O3_2005_LLE2 WCS GeoTIFF GAINS_BL_CLE_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2020_LLE1 GAINS_BL_CLE_O3_2020_LLE1 WCS GeoTIFF GAINS_BL_CLE_O3_2020_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2020_LLE2 GAINS_BL_CLE_O3_2020_LLE2 WCS GeoTIFF GAINS_BL_CLE_O3_2020_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2030_LLE1 GAINS_BL_CLE_O3_2030_LLE1 WCS GeoTIFF GAINS_BL_CLE_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2030_LLE2 GAINS_BL_CLE_O3_2030_LLE2 WCS GeoTIFF GAINS_BL_CLE_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2040_LLE1 GAINS_BL_CLE_O3_2040_LLE1 WCS GeoTIFF GAINS_BL_CLE_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2040_LLE2 GAINS_BL_CLE_O3_2040_LLE2 WCS GeoTIFF GAINS_BL_CLE_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2050_LLE1 GAINS_BL_CLE_O3_2050_LLE1 WCS GeoTIFF GAINS_BL_CLE_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_O3_2050_LLE2 GAINS_BL_CLE_O3_2050_LLE2 WCS GeoTIFF GAINS_BL_CLE_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_PM25_2005_LLE_doll1 GAINS_BL_CLE_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (CLE) WCS GeoTIFF GAINS_BL_CLE_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_PM25_2005_LLE_doll2 GAINS_BL_CLE_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (CLE) WCS GeoTIFF GAINS_BL_CLE_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_PM25_2005_LLE_yoll1 GAINS_BL_CLE_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (CLE) WCS GeoTIFF GAINS_BL_CLE_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_CLE_PM25_2005_LLE_yoll2 GAINS_BL_CLE_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (CLE) WCS GeoTIFF GAINS_BL_CLE_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2005_LLE1 GAINS_BL_FEF_O3_2005_LLE1 WCS GeoTIFF GAINS_BL_FEF_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2005_LLE2 GAINS_BL_FEF_O3_2005_LLE2 WCS GeoTIFF GAINS_BL_FEF_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2020_LLE1 GAINS_BL_FEF_O3_2020_LLE1 WCS GeoTIFF GAINS_BL_FEF_O3_2020_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2020_LLE2 GAINS_BL_FEF_O3_2020_LLE2 WCS GeoTIFF GAINS_BL_FEF_O3_2020_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2030_LLE1 GAINS_BL_FEF_O3_2030_LLE1 WCS GeoTIFF GAINS_BL_FEF_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2030_LLE2 GAINS_BL_FEF_O3_2030_LLE2 WCS GeoTIFF GAINS_BL_FEF_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2040_LLE1 GAINS_BL_FEF_O3_2040_LLE1 WCS GeoTIFF GAINS_BL_FEF_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2040_LLE2 GAINS_BL_FEF_O3_2040_LLE2 WCS GeoTIFF GAINS_BL_FEF_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2050_LLE1 GAINS_BL_FEF_O3_2050_LLE1 WCS GeoTIFF GAINS_BL_FEF_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_O3_2050_LLE2 GAINS_BL_FEF_O3_2050_LLE2 WCS GeoTIFF GAINS_BL_FEF_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_PM25_2005_LLE_doll1 GAINS_BL_FEF_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (FEF) WCS GeoTIFF GAINS_BL_FEF_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_PM25_2005_LLE_doll2 GAINS_BL_FEF_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (FEF) WCS GeoTIFF GAINS_BL_FEF_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_PM25_2005_LLE_yoll1 GAINS_BL_FEF_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (FEF) WCS GeoTIFF GAINS_BL_FEF_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_FEF_PM25_2005_LLE_yoll2 GAINS_BL_FEF_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (FEF) WCS GeoTIFF GAINS_BL_FEF_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2005_LLE1 GAINS_BL_MFR_O3_2005_LLE1 WCS GeoTIFF GAINS_BL_MFR_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2005_LLE2 GAINS_BL_MFR_O3_2005_LLE2 WCS GeoTIFF GAINS_BL_MFR_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2020_LLE1 GAINS_BL_MFR_O3_2020_LLE1 WCS GeoTIFF GAINS_BL_MFR_O3_2020_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2020_LLE2 GAINS_BL_MFR_O3_2020_LLE2 WCS GeoTIFF GAINS_BL_MFR_O3_2020_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2030_LLE1 GAINS_BL_MFR_O3_2030_LLE1 WCS GeoTIFF GAINS_BL_MFR_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2030_LLE2 GAINS_BL_MFR_O3_2030_LLE2 WCS GeoTIFF GAINS_BL_MFR_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2040_LLE1 GAINS_BL_MFR_O3_2040_LLE1 WCS GeoTIFF GAINS_BL_MFR_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2040_LLE2 GAINS_BL_MFR_O3_2040_LLE2 WCS GeoTIFF GAINS_BL_MFR_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2050_LLE1 GAINS_BL_MFR_O3_2050_LLE1 WCS GeoTIFF GAINS_BL_MFR_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_O3_2050_LLE2 GAINS_BL_MFR_O3_2050_LLE2 WCS GeoTIFF GAINS_BL_MFR_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_PM25_2005_LLE_doll1 GAINS_BL_MFR_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (MTFR) WCS GeoTIFF GAINS_BL_MFR_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_PM25_2005_LLE_doll2 GAINS_BL_MFR_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (MTFR) WCS GeoTIFF GAINS_BL_MFR_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_PM25_2005_LLE_yoll1 GAINS_BL_MFR_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (MTFR) WCS GeoTIFF GAINS_BL_MFR_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_BL_MFR_PM25_2005_LLE_yoll2 GAINS_BL_MFR_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Baseline scenario (MTFR) WCS GeoTIFF GAINS_BL_MFR_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2005_LLE1 GAINS_MAX_CLE_O3_2005_LLE1 WCS GeoTIFF GAINS_MAX_CLE_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2005_LLE2 GAINS_MAX_CLE_O3_2005_LLE2 WCS GeoTIFF GAINS_MAX_CLE_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2030_LLE1 GAINS_MAX_CLE_O3_2030_LLE1 WCS GeoTIFF GAINS_MAX_CLE_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2030_LLE2 GAINS_MAX_CLE_O3_2030_LLE2 WCS GeoTIFF GAINS_MAX_CLE_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2040_LLE1 GAINS_MAX_CLE_O3_2040_LLE1 WCS GeoTIFF GAINS_MAX_CLE_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2040_LLE2 GAINS_MAX_CLE_O3_2040_LLE2 WCS GeoTIFF GAINS_MAX_CLE_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2050_LLE1 GAINS_MAX_CLE_O3_2050_LLE1 WCS GeoTIFF GAINS_MAX_CLE_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_O3_2050_LLE2 GAINS_MAX_CLE_O3_2050_LLE2 WCS GeoTIFF GAINS_MAX_CLE_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_PM25_2005_LLE_doll1 GAINS_MAX_CLE_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (CLE) WCS GeoTIFF GAINS_MAX_CLE_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_PM25_2005_LLE_doll2 GAINS_MAX_CLE_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (CLE) WCS GeoTIFF GAINS_MAX_CLE_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_PM25_2005_LLE_yoll1 GAINS_MAX_CLE_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (CLE) WCS GeoTIFF GAINS_MAX_CLE_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_CLE_PM25_2005_LLE_yoll2 GAINS_MAX_CLE_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (CLE) WCS GeoTIFF GAINS_MAX_CLE_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2005_LLE1 GAINS_MAX_MFR_O3_2005_LLE1 WCS GeoTIFF GAINS_MAX_MFR_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2005_LLE2 GAINS_MAX_MFR_O3_2005_LLE2 WCS GeoTIFF GAINS_MAX_MFR_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2030_LLE1 GAINS_MAX_MFR_O3_2030_LLE1 WCS GeoTIFF GAINS_MAX_MFR_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2030_LLE2 GAINS_MAX_MFR_O3_2030_LLE2 WCS GeoTIFF GAINS_MAX_MFR_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2040_LLE1 GAINS_MAX_MFR_O3_2040_LLE1 WCS GeoTIFF GAINS_MAX_MFR_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2040_LLE2 GAINS_MAX_MFR_O3_2040_LLE2 WCS GeoTIFF GAINS_MAX_MFR_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2050_LLE1 GAINS_MAX_MFR_O3_2050_LLE1 WCS GeoTIFF GAINS_MAX_MFR_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_O3_2050_LLE2 GAINS_MAX_MFR_O3_2050_LLE2 WCS GeoTIFF GAINS_MAX_MFR_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_PM25_2005_LLE_doll1 GAINS_MAX_MFR_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (MTFR) WCS GeoTIFF GAINS_MAX_MFR_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_PM25_2005_LLE_doll2 GAINS_MAX_MFR_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (MTFR) WCS GeoTIFF GAINS_MAX_MFR_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_PM25_2005_LLE_yoll1 GAINS_MAX_MFR_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (MTFR) WCS GeoTIFF GAINS_MAX_MFR_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_MAX_MFR_PM25_2005_LLE_yoll2 GAINS_MAX_MFR_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Max. Renewable Energy scenario (MTFR) WCS GeoTIFF GAINS_MAX_MFR_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2005_LLE1 GAINS_NUC_CLE_O3_2005_LLE1 WCS GeoTIFF GAINS_NUC_CLE_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2005_LLE2 GAINS_NUC_CLE_O3_2005_LLE2 WCS GeoTIFF GAINS_NUC_CLE_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2030_LLE1 GAINS_NUC_CLE_O3_2030_LLE1 WCS GeoTIFF GAINS_NUC_CLE_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2030_LLE2 GAINS_NUC_CLE_O3_2030_LLE2 WCS GeoTIFF GAINS_NUC_CLE_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2040_LLE1 GAINS_NUC_CLE_O3_2040_LLE1 WCS GeoTIFF GAINS_NUC_CLE_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2040_LLE2 GAINS_NUC_CLE_O3_2040_LLE2 WCS GeoTIFF GAINS_NUC_CLE_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2050_LLE1 GAINS_NUC_CLE_O3_2050_LLE1 WCS GeoTIFF GAINS_NUC_CLE_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_O3_2050_LLE2 GAINS_NUC_CLE_O3_2050_LLE2 WCS GeoTIFF GAINS_NUC_CLE_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_PM25_2005_LLE_doll1 GAINS_NUC_CLE_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (CLE) WCS GeoTIFF GAINS_NUC_CLE_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_PM25_2005_LLE_doll2 GAINS_NUC_CLE_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (CLE) WCS GeoTIFF GAINS_NUC_CLE_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_PM25_2005_LLE_yoll1 GAINS_NUC_CLE_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (CLE) WCS GeoTIFF GAINS_NUC_CLE_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_CLE_PM25_2005_LLE_yoll2 GAINS_NUC_CLE_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (CLE) WCS GeoTIFF GAINS_NUC_CLE_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2005_LLE1 GAINS_NUC_FEF_O3_2005_LLE1 WCS GeoTIFF GAINS_NUC_FEF_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2005_LLE2 GAINS_NUC_FEF_O3_2005_LLE2 WCS GeoTIFF GAINS_NUC_FEF_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2030_LLE1 GAINS_NUC_FEF_O3_2030_LLE1 WCS GeoTIFF GAINS_NUC_FEF_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2030_LLE2 GAINS_NUC_FEF_O3_2030_LLE2 WCS GeoTIFF GAINS_NUC_FEF_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2040_LLE1 GAINS_NUC_FEF_O3_2040_LLE1 WCS GeoTIFF GAINS_NUC_FEF_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2040_LLE2 GAINS_NUC_FEF_O3_2040_LLE2 WCS GeoTIFF GAINS_NUC_FEF_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2050_LLE1 GAINS_NUC_FEF_O3_2050_LLE1 WCS GeoTIFF GAINS_NUC_FEF_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_O3_2050_LLE2 GAINS_NUC_FEF_O3_2050_LLE2 WCS GeoTIFF GAINS_NUC_FEF_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_PM25_2005_LLE_doll1 GAINS_NUC_FEF_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (FEF) WCS GeoTIFF GAINS_NUC_FEF_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_PM25_2005_LLE_doll2 GAINS_NUC_FEF_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (FEF) WCS GeoTIFF GAINS_NUC_FEF_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_PM25_2005_LLE_yoll1 GAINS_NUC_FEF_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (FEF) WCS GeoTIFF GAINS_NUC_FEF_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 gn:GAINS_NUC_FEF_PM25_2005_LLE_yoll2 GAINS_NUC_FEF_PM25_2005_LLE_yoll2 WCS GeoTIFF GAINS_NUC_FEF_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_FEF_PM25_2005_LLE_yoll2 GAINS_NUC_FEF_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (FEF) WCS GeoTIFF GAINS_NUC_FEF_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2005_LLE1 GAINS_NUC_MFR_O3_2005_LLE1 WCS GeoTIFF GAINS_NUC_MFR_O3_2005_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2005_LLE2 GAINS_NUC_MFR_O3_2005_LLE2 WCS GeoTIFF GAINS_NUC_MFR_O3_2005_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2030_LLE1 GAINS_NUC_MFR_O3_2030_LLE1 WCS GeoTIFF GAINS_NUC_MFR_O3_2030_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2030_LLE2 GAINS_NUC_MFR_O3_2030_LLE2 WCS GeoTIFF GAINS_NUC_MFR_O3_2030_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2040_LLE1 GAINS_NUC_MFR_O3_2040_LLE1 WCS GeoTIFF GAINS_NUC_MFR_O3_2040_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2040_LLE2 GAINS_NUC_MFR_O3_2040_LLE2 WCS GeoTIFF GAINS_NUC_MFR_O3_2040_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2050_LLE1 GAINS_NUC_MFR_O3_2050_LLE1 WCS GeoTIFF GAINS_NUC_MFR_O3_2050_LLE1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_O3_2050_LLE2 GAINS_NUC_MFR_O3_2050_LLE2 WCS GeoTIFF GAINS_NUC_MFR_O3_2050_LLE2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_PM25_2005_LLE_doll1 GAINS_NUC_MFR_PM25_2005_LLE_doll1 Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (MTFR) WCS GeoTIFF GAINS_NUC_MFR_PM25_2005_LLE_doll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_PM25_2005_LLE_doll2 GAINS_NUC_MFR_PM25_2005_LLE_doll2 National mean Days of Life Loss Expectancy per person above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (MTFR) WCS GeoTIFF GAINS_NUC_MFR_PM25_2005_LLE_doll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_PM25_2005_LLE_yoll1 GAINS_NUC_MFR_PM25_2005_LLE_yoll1 Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (MTFR) WCS GeoTIFF GAINS_NUC_MFR_PM25_2005_LLE_yoll1 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 energeo_pia_2013:GAINS_NUC_MFR_PM25_2005_LLE_yoll2 GAINS_NUC_MFR_PM25_2005_LLE_yoll2 National mean Years of Life Loss Expectancy for population above 30 years in 2005 due to PM2.5 from GAINS Island Europe scenario (MTFR) WCS GeoTIFF GAINS_NUC_MFR_PM25_2005_LLE_yoll2 EPSG:4326 CRS:84 -10.0625 55.0625 34.9375 70.0625 mapserv:GHI_MoyMensuelle_kWhm-2_geotiff GHI_MoyMensuelle_kWhm-2_geotiff GHI_MoyMensuelle_kWhm-2_geotiff WCS GeoTIFF EPSG:4326 CRS:84 -16.75 45.083086 55.916667 75.99992 mapserv:GHI_y_min1297_max1733_geo GHI_y_min1297_max1733_geo Yearly sum GHI PACA GHI_y_min1297_max1733_geo WCS GeoTIFF EPSG:4326 CRS:84 4.0 8.002777777778098 45.5 48.502222222223274 mapserv:Gharb-Ghrarda-Beni-Hsen_BNI Gharb-Ghrarda-Beni-Hsen_BNI Gharb-Ghrarda-Beni-Hsen_BNI WCS VRT EPSG:4326 CRS:84 -6.71186 -5.14665472 34.09561786 34.988 mapserv:Gharb-Ghrarda-Beni-Hsen_GHI Gharb-Ghrarda-Beni-Hsen_GHI Gharb-Ghrarda-Beni-Hsen_GHI WCS VRT EPSG:4326 CRS:84 -6.71186 -5.14665472 34.09561786 34.988 mapserv:Gharb-Ghrarda-Beni-Hsen_vent Gharb-Ghrarda-Beni-Hsen_vent Gharb-Ghrarda-Beni-Hsen_vent WCS VRT EPSG:4326 CRS:84 -6.71186 -5.1466566 34.0956176 34.988 mapserv:Grand-Casablanca_BNI Grand-Casablanca_BNI Grand-Casablanca_BNI WCS VRT EPSG:4326 CRS:84 -7.89486 -7.345592160000001 33.319421 33.7343 mapserv:Grand-Casablanca_GHI Grand-Casablanca_GHI Grand-Casablanca_GHI WCS VRT EPSG:4326 CRS:84 -7.89486 -7.345592160000001 33.319421 33.7343 mapserv:Grand-Casablanca_vent Grand-Casablanca_vent Grand-Casablanca_vent WCS VRT EPSG:4326 CRS:84 -7.89486 -7.3455915 33.31942 33.7343 mapserv:Guelmim-Es-Semara_BNI Guelmim-Es-Semara_BNI Guelmim-Es-Semara_BNI WCS VRT EPSG:4326 CRS:84 -12.5775 -6.374452080000001 25.9942451 30.4125 mapserv:Guelmim-Es-Semara_GHI Guelmim-Es-Semara_GHI Guelmim-Es-Semara_GHI WCS VRT EPSG:4326 CRS:84 -12.5775 -6.374452080000001 25.9942451 30.4125 mapserv:Guelmim-Es-Semara_vent Guelmim-Es-Semara_vent Guelmim-Es-Semara_vent WCS VRT EPSG:4326 CRS:84 -12.5775 -6.374437200000001 25.9942345 30.4125 helioclim1:HC1_mean_Gd_1985 HC1_mean_Gd_1985 HelioClim-1 Yearly Mean of Irradiance - Year 1985 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1985 WCS GeoTIFF Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1985_2005 HC1_mean_Gd_1985_2005 HelioClim-1 Yearly Mean of Irradiance - Years 1985-2005 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1985_2005 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 qc:HC1_mean_Gd_1985_EPSG_4326_r32_geo HC1_mean_Gd_1985_EPSG_4326_r32_geo WCS GeoTIFF HC1_mean_Gd_1985_EPSG_4326_r32_geo EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 Data Quality Information helioclim1:HC1_mean_Gd_1986 HC1_mean_Gd_1986 HelioClim-1 Yearly Mean of Irradiance - Year 1986 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1986 WCS GeoTIFF Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1987 HC1_mean_Gd_1987 HelioClim-1 Yearly Mean of Irradiance - Year 1987 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1987 WCS GeoTIFF Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1988 HC1_mean_Gd_1988 HelioClim-1 Yearly Mean of Irradiance - Year 1988 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1988 WCS GeoTIFF Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1989 HC1_mean_Gd_1989 HelioClim-1 Yearly Mean of Irradiance - Year 1989 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1989 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1990 HC1_mean_Gd_1990 HelioClim-1 Yearly Mean of Irradiance - Year 1990 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1990 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1991 HC1_mean_Gd_1991 HelioClim-1 Yearly Mean of Irradiance - Year 1991 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1991 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1992 HC1_mean_Gd_1992 HelioClim-1 Yearly Mean of Irradiance - Year 1992 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1992 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1993 HC1_mean_Gd_1993 HelioClim-1 Yearly Mean of Irradiance - Year 1993 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1993 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1994 HC1_mean_Gd_1994 HelioClim-1 Yearly Mean of Irradiance - Year 1994 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1994 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1995 HC1_mean_Gd_1995 HelioClim-1 Yearly Mean of Irradiance - Year 1995 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1995 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1996 HC1_mean_Gd_1996 HelioClim-1 Yearly Mean of Irradiance - Year 1996 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1996 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1997 HC1_mean_Gd_1997 HelioClim-1 Yearly Mean of Irradiance - Year 1997 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1997 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1998 HC1_mean_Gd_1998 HelioClim-1 Yearly Mean of Irradiance - Year 1998 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1998 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_1999 HC1_mean_Gd_1999 HelioClim-1 Yearly Mean of Irradiance - Year 1999 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_1999 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2000 HC1_mean_Gd_2000 HelioClim-1 Yearly Mean of Irradiance - Year 2000 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2000 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2001 HC1_mean_Gd_2001 HelioClim-1 Yearly Mean of Irradiance - Year 2001 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2001 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2002 HC1_mean_Gd_2002 HelioClim-1 Yearly Mean of Irradiance - Year 2002 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2002 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2003 HC1_mean_Gd_2003 HelioClim-1 Yearly Mean of Irradiance - Year 2003 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2003 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2004 HC1_mean_Gd_2004 HelioClim-1 Yearly Mean of Irradiance - Year 2004 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2004 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim1:HC1_mean_Gd_2005 HC1_mean_Gd_2005 HelioClim-1 Yearly Mean of Irradiance - Year 2005 The HelioClim-1 database, abbreviated in HC-1, offers daily values of Surface Solar Irradiation (SSI) for the period 1985–2005. It has been created from archives of images of the Meteosat First Generation. This dataset provides for each year (1985-2005) a map of yearly mean of irradiance in (w/m2). WCS GeoTIFF HC1_mean_Gd_2005 Surface solar irradiation Insolation Irradiance Irradiation GHI HelioClim HelioClim1 HelioClim-1 MINES ParisTech GEOSS GEOSS Data CORE geossDataCore geossNoMonetaryCharge EPSG:4326 CRS:84 -70.125 70.125 -70.125 70.125 helioclim3v4mc:HelioClim3v4-MC_BNI_Apr2005 HelioClim3v4-MC_BNI_Apr2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Apr. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Apr. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Apr2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Aug2005 HelioClim3v4-MC_BNI_Aug2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Aug. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Aug. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Aug2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Dec2005 HelioClim3v4-MC_BNI_Dec2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Dec. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Dec. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Dec2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Feb2005 HelioClim3v4-MC_BNI_Feb2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Feb. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Feb. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Feb2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Jan2005 HelioClim3v4-MC_BNI_Jan2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Jan. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Jan. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Jan2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Jul2005 HelioClim3v4-MC_BNI_Jul2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Jul. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Jul. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Jul2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Jun2005 HelioClim3v4-MC_BNI_Jun2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Jun. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Jun. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Jun2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Mar2005 HelioClim3v4-MC_BNI_Mar2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Mar. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Mar. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Mar2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_May2005 HelioClim3v4-MC_BNI_May2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of May. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of May. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_May2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Nov2005 HelioClim3v4-MC_BNI_Nov2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Nov. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Nov. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Nov2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Oct2005 HelioClim3v4-MC_BNI_Oct2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Oct. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Oct. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Oct2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_Sep2005 HelioClim3v4-MC_BNI_Sep2005 HelioClim3v4-MC Monthly Direct Normal Irradiation for the month of Sep. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the month of Sep. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_Sep2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_BNI_year2005 HelioClim3v4-MC_BNI_year2005 HelioClim3v4-MC Yearly Direct Normal Irradiation for the year 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Direct component of the irradiation received by a plane normal to sun rays during the year 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. Yearly irradiation values are computed only for pixels for which 12 monthly irradiation values are available. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_BNI_year2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Apr2005 HelioClim3v4-MC_DHI_Apr2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Apr. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Apr. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Apr2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Aug2005 HelioClim3v4-MC_DHI_Aug2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Aug. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Aug. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Aug2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Dec2005 HelioClim3v4-MC_DHI_Dec2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Dec. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Dec. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Dec2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Feb2005 HelioClim3v4-MC_DHI_Feb2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Feb. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Feb. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Feb2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Jan2005 HelioClim3v4-MC_DHI_Jan2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Jan. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Jan. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Jan2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Jul2005 HelioClim3v4-MC_DHI_Jul2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Jul. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Jul. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Jul2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Jun2005 HelioClim3v4-MC_DHI_Jun2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Jun. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Jun. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Jun2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Mar2005 HelioClim3v4-MC_DHI_Mar2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Mar. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Mar. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu : WCS GeoTIFF HelioClim3v4-MC_DHI_Mar2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_May2005 HelioClim3v4-MC_DHI_May2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of May. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of May. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_May2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Nov2005 HelioClim3v4-MC_DHI_Nov2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Nov. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Nov. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Nov2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Oct2005 HelioClim3v4-MC_DHI_Oct2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Oct. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Oct. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Oct2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_Sep2005 HelioClim3v4-MC_DHI_Sep2005 HelioClim3v4-MC Monthly Diffuse Horizontal Irradiation for the month of Sep. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the month of Sep. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_Sep2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_DHI_year2005 HelioClim3v4-MC_DHI_year2005 HelioClim3v4-MC Yearly Diffuse Horizontal Irradiation for the year 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Diffuse irradiation received by a horizontal plane during the year 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. Yearly irradiation values are computed only for pixels for which 12 monthly irradiation values are available. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_DHI_year2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Apr2005 HelioClim3v4-MC_GHI_Apr2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Apr. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Apr. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Apr2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Aug2005 HelioClim3v4-MC_GHI_Aug2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Aug. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Aug. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Aug2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Dec2005 HelioClim3v4-MC_GHI_Dec2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Dec. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Dec. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Dec2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Feb2005 HelioClim3v4-MC_GHI_Feb2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Feb. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Feb. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Feb2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Jan2005 HelioClim3v4-MC_GHI_Jan2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Jan. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Jan. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Jan2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Jul2005 HelioClim3v4-MC_GHI_Jul2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Jul. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Jul. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Jul2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Jun2005 HelioClim3v4-MC_GHI_Jun2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Jun. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Jun. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Jun2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Mar2005 HelioClim3v4-MC_GHI_Mar2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Mar. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Mar. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Mar2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_May2005 HelioClim3v4-MC_GHI_May2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of May. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of May. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_May2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Nov2005 HelioClim3v4-MC_GHI_Nov2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Nov. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Nov. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Nov2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Oct2005 HelioClim3v4-MC_GHI_Oct2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Oct. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Oct. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Oct2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_Sep2005 HelioClim3v4-MC_GHI_Sep2005 HelioClim3v4-MC Monthly Global Horizontal Irradiation for the month of Sep. 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the month of Sep. 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_Sep2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 helioclim3v4mc:HelioClim3v4-MC_GHI_year2005 HelioClim3v4-MC_GHI_year2005 HelioClim3v4-MC Yearly Global Horizontal Irradiation for the year 2005 in kWh/m2. Copyright 2013 MINES ParisTech / Transvalor Global irradiation received by a horizontal plane during the year 2005 for the field-of-view of the Meteosat satellite. MINES ParisTech has developed the Heliosat-2 method that converts 15 min Meteosat images into irradiation maps and stores them into the HelioClim3 database. Yearly irradiation values are computed only for pixels for which 12 monthly irradiation values are available. A monthly irradiation value is computed only if at least 25 daily irradiation values are available. The irradiation values of the missing days are computed by taking into account the mean value of the valid days and the length of each missing day. A day is valid if the HelioSat-2 method can be applied on at least one 15 min slot. Gaps in the day are filled by taking into account the available 15 min irradiation values and the length of the day. The other irradiation components (direct, diffuse) received on an horizontal, tilted or normal plane are then computed and provided via the SoDa Service (www.soda-is.com and pro.soda-is.com) since 2003. Such data are used by academics for teaching and research in solar energy, environment, climate and others, and by companies for the sitting of solar plants (PV, CST), their sizing, and the monitoring of their production. Since 2009, the French company Transvalor is in charge of the SoDa Service. Transvalor provides in addition a series of user-tailored services, such as these maps made with MINES ParisTech that combine HelioClim-3 data with an advanced model McClear that estimates the irradiation that should be received for a given site and given instant if the sky were clear, aka clear sky irradiation. Here MC stands for McClear. Transvalor and MINES ParisTech have set up the McClear Clear-Sky Irradiation service that delivers time series of clear sky global, direct, direct normal, and diffuse irradiation for any site in the world, any period of time starting in 2004 up to now, with a time step ranging from 1 min to 1 month. The McClear is an outcome of the MACC and MACC-II EU-funded projects. More Information: Heliosat-2 publication: http://hal.archives-ouvertes.fr/docs/00/36/13/64/PDF/solar_energy04_heliosat2.pdf HelioClim-3: http://www.soda-is.com/eng/helioclim/helioclim3_eng.html McClear publication: http://www.atmos-meas-tech.net/6/2403/2013/amt-6-2403-2013.pdf McClear Web service: http://www.soda-pro.com/web-services/radiation/cams-mcclear Copernicus projects: https://atmosphere.copernicus.eu WCS GeoTIFF HelioClim3v4-MC_GHI_year2005 GA_BUSINESS EPSG:4326 CRS:84 -66.0 66.0 -66.0 66.0 energeo_pia:LLE_2005_PM_GAINS_baseline_doll1 LLE_2005_PM_GAINS_baseline_doll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Baseline scenario WCS GeoTIFF LLE_2005_PM_GAINS_baseline_doll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_baseline_doll2 LLE_2005_PM_GAINS_baseline_doll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Baseline scenario WCS GeoTIFF LLE_2005_PM_GAINS_baseline_doll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_baseline_yoll1 LLE_2005_PM_GAINS_baseline_yoll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Baseline scenario WCS GeoTIFF LLE_2005_PM_GAINS_baseline_yoll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_baseline_yoll2 LLE_2005_PM_GAINS_baseline_yoll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Baseline scenario WCS GeoTIFF LLE_2005_PM_GAINS_baseline_yoll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_island_europe_doll1 LLE_2005_PM_GAINS_island_europe_doll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Island Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_island_europe_doll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_island_europe_doll2 LLE_2005_PM_GAINS_island_europe_doll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Island Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_island_europe_doll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_island_europe_yoll1 LLE_2005_PM_GAINS_island_europe_yoll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Island Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_island_europe_yoll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_island_europe_yoll2 LLE_2005_PM_GAINS_island_europe_yoll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Island Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_island_europe_yoll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_max_ren_doll1 LLE_2005_PM_GAINS_max_ren_doll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Max renewable power scenario WCS GeoTIFF LLE_2005_PM_GAINS_max_ren_doll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_max_ren_doll2 LLE_2005_PM_GAINS_max_ren_doll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Max renewable power scenario WCS GeoTIFF LLE_2005_PM_GAINS_max_ren_doll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_max_ren_yoll1 LLE_2005_PM_GAINS_max_ren_yoll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Max renewable power scenario WCS GeoTIFF LLE_2005_PM_GAINS_max_ren_yoll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_max_ren_yoll2 LLE_2005_PM_GAINS_max_ren_yoll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Max renewable power scenario WCS GeoTIFF LLE_2005_PM_GAINS_max_ren_yoll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_open_europe_doll1 LLE_2005_PM_GAINS_open_europe_doll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Open Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_open_europe_doll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_open_europe_doll2 LLE_2005_PM_GAINS_open_europe_doll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Open Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_open_europe_doll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_open_europe_yoll1 LLE_2005_PM_GAINS_open_europe_yoll1 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Open Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_open_europe_yoll1 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_2005_PM_GAINS_open_europe_yoll2 LLE_2005_PM_GAINS_open_europe_yoll2 Loss of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS Open Europe scenario WCS GeoTIFF LLE_2005_PM_GAINS_open_europe_yoll2 EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c00_doll LLE_vs_GAINS_baseline_c00_doll Lost of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c00_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c00_yoll LLE_vs_GAINS_baseline_c00_yoll Lost of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c00_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c01_doll LLE_vs_GAINS_baseline_c01_doll Lost of Life Expectancy for cohort 30-34 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c01_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c01_yoll LLE_vs_GAINS_baseline_c01_yoll Lost of Life Expectancy for cohort 30-34 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c01_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c02_doll LLE_vs_GAINS_baseline_c02_doll Lost of Life Expectancy for cohort 35-39 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c02_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c02_yoll LLE_vs_GAINS_baseline_c02_yoll Lost of Life Expectancy for cohort 35-39 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c02_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c03_doll LLE_vs_GAINS_baseline_c03_doll Lost of Life Expectancy for cohort 40-44 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c03_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c03_yoll LLE_vs_GAINS_baseline_c03_yoll Lost of Life Expectancy for cohort 40-44 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c03_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c04_doll LLE_vs_GAINS_baseline_c04_doll Lost of Life Expectancy for cohort 45-49 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c04_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c04_yoll LLE_vs_GAINS_baseline_c04_yoll Lost of Life Expectancy for cohort 45-49 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c04_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c05_doll LLE_vs_GAINS_baseline_c05_doll Lost of Life Expectancy for cohort 50-54 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c05_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c05_yoll LLE_vs_GAINS_baseline_c05_yoll Lost of Life Expectancy for cohort 50-54 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c05_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c06_doll LLE_vs_GAINS_baseline_c06_doll Lost of Life Expectancy for cohort 55-59 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c06_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c06_yoll LLE_vs_GAINS_baseline_c06_yoll Lost of Life Expectancy for cohort 55-59 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c06_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c07_doll LLE_vs_GAINS_baseline_c07_doll Lost of Life Expectancy for cohort 60-64 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c07_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c07_yoll LLE_vs_GAINS_baseline_c07_yoll Lost of Life Expectancy for cohort 60-64 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c07_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c08_doll LLE_vs_GAINS_baseline_c08_doll Lost of Life Expectancy for cohort 65-69 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c08_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c08_yoll LLE_vs_GAINS_baseline_c08_yoll Lost of Life Expectancy for cohort 65-69 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c08_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c09_doll LLE_vs_GAINS_baseline_c09_doll Lost of Life Expectancy for cohort 70-74 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c09_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c09_yoll LLE_vs_GAINS_baseline_c09_yoll Lost of Life Expectancy for cohort 70-74 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c09_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c10_doll LLE_vs_GAINS_baseline_c10_doll Lost of Life Expectancy for cohort 75-79 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c10_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c10_yoll LLE_vs_GAINS_baseline_c10_yoll Lost of Life Expectancy for cohort 75-79 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c10_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c11_doll LLE_vs_GAINS_baseline_c11_doll Lost of Life Expectancy for cohort 80-84 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c11_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c11_yoll LLE_vs_GAINS_baseline_c11_yoll Lost of Life Expectancy for cohort 80-84 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c11_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c12_doll LLE_vs_GAINS_baseline_c12_doll Lost of Life Expectancy for cohort 85-89 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c12_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c12_yoll LLE_vs_GAINS_baseline_c12_yoll Lost of Life Expectancy for cohort 85-89 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c12_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c13_doll LLE_vs_GAINS_baseline_c13_doll Lost of Life Expectancy for cohort 90-94 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c13_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c13_yoll LLE_vs_GAINS_baseline_c13_yoll Lost of Life Expectancy for cohort 90-94 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c13_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c14_doll LLE_vs_GAINS_baseline_c14_doll Lost of Life Expectancy for cohort 95-99 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c14_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c14_yoll LLE_vs_GAINS_baseline_c14_yoll Lost of Life Expectancy for cohort 95-99 years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c14_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c15_doll LLE_vs_GAINS_baseline_c15_doll Lost of Life Expectancy for cohort 100+ years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c15_doll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo_pia:LLE_vs_GAINS_baseline_c15_yoll LLE_vs_GAINS_baseline_c15_yoll Lost of Life Expectancy for cohort 100+ years in 2005 due to PM 2.5 from GAINS baseline scenario WCS GeoTIFF LLE_vs_GAINS_baseline_c15_yoll EPSG:4326 CRS:84 -13.0625 55.0625 34.9375 70.0625 energeo:LLE_vs_TNO_2008_layer_08 LLE_vs_TNO_2008_layer_08 WCS GeoTIFF LLE_vs_TNO_2008_layer_08 EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_01_doll LLE_vs_TNO_layer_27_01_doll Lost of Life Expectancy for cohort 30-34 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_01_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c00_doll LLE_vs_TNO_layer_27_c00_doll Lost of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c00_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c00_yoll LLE_vs_TNO_layer_27_c00_yoll Lost of Life Expectancy for population over 30 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c00_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c01_doll LLE_vs_TNO_layer_27_c01_doll Lost of Life Expectancy for cohort 30-34 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c01_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c01_yoll LLE_vs_TNO_layer_27_c01_yoll Lost of Life Expectancy for cohort 30-34 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c01_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c02_doll LLE_vs_TNO_layer_27_c02_doll Lost of Life Expectancy for cohort 35-39 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c02_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c02_yoll LLE_vs_TNO_layer_27_c02_yoll Lost of Life Expectancy for cohort 35-39 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c02_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c03_doll LLE_vs_TNO_layer_27_c03_doll Lost of Life Expectancy for cohort 40-44 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c03_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c03_yoll LLE_vs_TNO_layer_27_c03_yoll Lost of Life Expectancy for cohort 40-44 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c03_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c04_doll LLE_vs_TNO_layer_27_c04_doll Lost of Life Expectancy for cohort 45-49 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c04_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c04_yoll LLE_vs_TNO_layer_27_c04_yoll Lost of Life Expectancy for cohort 45-49 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c04_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c05_doll LLE_vs_TNO_layer_27_c05_doll Lost of Life Expectancy for cohort 50-54 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c05_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c05_yoll LLE_vs_TNO_layer_27_c05_yoll Lost of Life Expectancy for cohort 50-54 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c05_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c06_doll LLE_vs_TNO_layer_27_c06_doll Lost of Life Expectancy for cohort 55-59 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c06_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c06_yoll LLE_vs_TNO_layer_27_c06_yoll Lost of Life Expectancy for cohort 55-59 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c06_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c07_doll LLE_vs_TNO_layer_27_c07_doll Lost of Life Expectancy for cohort 60-64 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c07_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c07_yoll LLE_vs_TNO_layer_27_c07_yoll Lost of Life Expectancy for cohort 60-64 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c07_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c08_doll LLE_vs_TNO_layer_27_c08_doll Lost of Life Expectancy for cohort 65-69 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c08_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c08_yoll LLE_vs_TNO_layer_27_c08_yoll Lost of Life Expectancy for cohort 65-69 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c08_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c09_doll LLE_vs_TNO_layer_27_c09_doll Lost of Life Expectancy for cohort 70-74 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c09_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c09_yoll LLE_vs_TNO_layer_27_c09_yoll Lost of Life Expectancy for cohort 70-74 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c09_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c10_doll LLE_vs_TNO_layer_27_c10_doll Lost of Life Expectancy for cohort 75-79 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c10_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c10_yoll LLE_vs_TNO_layer_27_c10_yoll Lost of Life Expectancy for cohort 75-79 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c10_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c11_doll LLE_vs_TNO_layer_27_c11_doll Lost of Life Expectancy for cohort 80-84 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c11_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c11_yoll LLE_vs_TNO_layer_27_c11_yoll Lost of Life Expectancy for cohort 80-84 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c11_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c12_doll LLE_vs_TNO_layer_27_c12_doll Lost of Life Expectancy for cohort 85-89 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c12_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c12_yoll LLE_vs_TNO_layer_27_c12_yoll Lost of Life Expectancy for cohort 85-89 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c12_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c13_doll LLE_vs_TNO_layer_27_c13_doll Lost of Life Expectancy for cohort 90-94 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c13_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c13_yoll LLE_vs_TNO_layer_27_c13_yoll Lost of Life Expectancy for cohort 90-94 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c13_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c14_doll LLE_vs_TNO_layer_27_c14_doll Lost of Life Expectancy for cohort 95-99 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c14_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c14_yoll LLE_vs_TNO_layer_27_c14_yoll Lost of Life Expectancy for cohort 95-99 years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c14_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c15_doll LLE_vs_TNO_layer_27_c15_doll Lost of Life Expectancy for cohort 100+ years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c15_doll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 energeo_pia:LLE_vs_TNO_layer_27_c15_yoll LLE_vs_TNO_layer_27_c15_yoll Lost of Life Expectancy for cohort 100+ years in 2005 due to PM 2.5 from Total PM 2.5 (TNO 2008) WCS GeoTIFF LLE_vs_TNO_layer_27_c15_yoll EPSG:4326 CRS:84 -15.0625 35.0625 34.9375 70.0625 mapserv:Laayoune-Boujdour-Sakia-Hamra_BNI Laayoune-Boujdour-Sakia-Hamra_BNI Laayoune-Boujdour-Sakia-Hamra_BNI WCS VRT EPSG:4326 CRS:84 -15.0004 -11.478831940000001 24.39001891 28.2151 mapserv:Laayoune-Boujdour-Sakia-Hamra_GHI Laayoune-Boujdour-Sakia-Hamra_GHI Laayoune-Boujdour-Sakia-Hamra_GHI WCS VRT EPSG:4326 CRS:84 -15.0004 -11.478831940000001 24.39001891 28.2151 mapserv:Laayoune-Boujdour-Sakia-Hamra_vent Laayoune-Boujdour-Sakia-Hamra_vent Laayoune-Boujdour-Sakia-Hamra_vent WCS VRT EPSG:4326 CRS:84 -15.0004 -11.4788311 24.390016 28.2151 mapserv:MAR_electricity MAR_electricity features MAR_electricity EPSG:4326 CRS:84 -14.497039200000007 -1.2477016000000045 26.117334599999996 35.88252459999999 mapserv:MAR_postes_elec MAR_postes_elec features MAR_postes_elec EPSG:4326 CRS:84 -15.959404060000006 -1.2476162833333353 23.681692080275905 35.83091961476713 mapserv:MAR_water MAR_water features MAR_water EPSG:4326 CRS:84 -9.503583620740528 -1.7249906134961748 29.769356002204404 35.70848023062511 mapserv:MOROCCO MOROCCO features MOROCCO EPSG:4326 CRS:84 -17.10541599999999 -0.9974059999999554 20.76958200000007 35.92263800000006 mapserv:MOROCCO_routes_asphaltees MOROCCO_routes_asphaltees features MOROCCO_routes_asphaltees EPSG:4326 CRS:84 -17.082984964059445 -0.9961681571375826 20.777824470657773 35.881445702417956 mapserv:MOROCCO_villes MOROCCO_villes features MOROCCO_villes EPSG:4326 CRS:84 -15.9431274 -1.9203727 23.6940663 35.7682828 marine:Marine_Energy_Resource_Characterization Marine Energy Resource Characterization Information relevant for the characterization of marine energy resource has been produced based on Homere sea state hindcast (Boudière et al. 2013, Boudière et al. 2014). The information reaches spatial resolution down to 200 m near the coast and focuses on the availability and spatial/temporal variability of the resource. The parameters are : Hs : Significant wave height (m), Te : Energy period (s), CgE : Wave power density (kW/m), fPeak : Wave peak frequency (Hz) For any computational grid point, annual and seasonal averages of these parameters are displayed within each row of the table. Also, dedicated links deliver synthetic information about wave climate and characterization of weather windows. Further information will be added as the current project goes on. References E. Boudière, C. Maisondieu, F. Ardhuin, M. Accensi, L. Pineau-Guillou, and J. Lepesqueur, “A suitable metocean hindcast database for the design of Marine energy converters,” International Journal of Marine Energy, vol. 3–4, pp. e40–e52, Dec. 2013. E. Boudière and C. 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merra:WindIntensity1989 WindIntensity1989 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1989 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1990 WindIntensity1990 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1990 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1991 WindIntensity1991 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1991 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1992 WindIntensity1992 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1992 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1993 WindIntensity1993 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1993 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1994 WindIntensity1994 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1994 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1995 WindIntensity1995 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1995 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1996 WindIntensity1996 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1996 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1997 WindIntensity1997 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1997 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1998 WindIntensity1998 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1998 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity1999 WindIntensity1999 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity1999 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2000 WindIntensity2000 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2000 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2001 WindIntensity2001 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2001 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2002 WindIntensity2002 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2002 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2003 WindIntensity2003 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2003 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2004 WindIntensity2004 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2004 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2005 WindIntensity2005 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2005 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2006 WindIntensity2006 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2006 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2007 WindIntensity2007 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2007 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2008 WindIntensity2008 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2008 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2009 WindIntensity2009 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2009 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2010 WindIntensity2010 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2010 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 merra:WindIntensity2011 WindIntensity2011 global 10-m wind intensity from MERRA for the entire 1985 year WCS GeoTIFF WindIntensity2011 EPSG:4326 CRS:84 -180.333951762523 180.33395176231704 -90.25069637877 90.25069637883 mapserv:adevelopper adevelopper features adevelopper EPSG:4326 CRS:84 5.25 151.1778 31.4711 44.015 australia:australia_january_epsg4326 australia_january_epsg4326 WCS GeoTIFF australia_epsg4326 EPSG:4326 CRS:84 112.02500000000012 153.9750000000002 -43.97500000000006 -10.025000000000011 gn:bluemarble-2048 bluemarble-2048 from NASA's Earth Observatory bluemarble-2048 WCS GeoTIFF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 bom_solar:bom_solar_an bom_solar_an Average daily solar exposure annual. Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_an features Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_apr bom_solar_apr Average daily solar exposure April. Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_apr features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_aug bom_solar_aug Average daily solar exposure August Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_aug Australia EPSG:4326 CRS:84 113.156196594238 153.637268066406 -43.639591217041 -10.6935186386108 bom_solar:bom_solar_aut bom_solar_aut Average daily solar exposure autumn Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_aut features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_dec bom_solar_dec Average daily solar exposure December Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_dec Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_dry bom_solar_dry Average daily solar exposure May to September (Northern dry season) Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_dry Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_feb bom_solar_feb Average daily solar exposure February Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_feb features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_jan bom_solar_jan Average daily solar exposure January Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_jan Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_jul bom_solar_jul Average daily solar exposure July Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_jul features Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_jun bom_solar_jun Average daily solar exposure June Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_jun features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_mar bom_solar_mar Average daily solar exposure March Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_mar features Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_may bom_solar_may Average daily solar exposure May Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_may Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_nov bom_solar_nov Average daily solar exposure November Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_nov Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_oct bom_solar_oct Average daily solar exposure October Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_oct features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_sep bom_solar_sep Average daily solar exposure September Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_sep Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_spr bom_solar_spr Average daily solar exposure spring Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_spr features Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6935186386108 bom_solar:bom_solar_sum bom_solar_sum Average daily solar exposure summer Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_sum features Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_wet bom_solar_wet Average daily solar exposure October to April (Northern wet season) Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf bom_solar_wet features Australia EPSG:4326 CRS:84 113.155097961426 153.637237548828 -43.6412696838379 -10.6927394866943 bom_solar:bom_solar_win bom_solar_win Average daily solar exposure winter Global solar exposure is the total amount of solar energy falling on a horizontal surface. The daily global solar exposure is the total solar energy for a day, and is typically between 1 and 35 MJ/m2 (megajoules per square metre). The Bureau of Meteorology's (BOM) computer radiation model uses visible images from geostationary meteorological satellites to estimate daily global solar exposures at ground level. At each location the image brightness is used to provide an estimate of the solar irradiance at the ground. Essentially, the irradiance at the ground can be calculated from the irradiance at the top of the earth's atmosphere, the amount absorbed in the atmosphere (dependant on the amount of water vapour present), the amount reflected from the surface (surface albedo) and the amount reflected from clouds (cloud albedo). These instantaneous irradiance values are integrated over the day to give daily solar exposure in megajoules per square metre. More information: http://www.bom.gov.au/jsp/ncc/climate_averages/solar-exposure/index.jsp?period=an#maps Access constraints: http://www.bom.gov.au/climate/averages/climatology/solar_radiation/average-solar-exposure-metadata.pdf features bom_solar_win Australia EPSG:4326 CRS:84 113.155097961426 153.636016845703 -43.6412696838379 -10.6927394866943 energeo:cc_15_30_hOM_bfond_hFR_Lo cc_15_30_hOM_bfond_hFR_Lo Legend for understanding map title names and their related configuration eg: cc_15_50_lOM_bfond_hFR_Lo_geo Each parameter is separated with an underscore (_) (1) Impact category: cc= climate change, res= resources, daly= daly, eco= ecosystem (2) Life time: 15 years vs 20 years vs 25 years (3) Number of wind turbines per farm: 30 vs 40 vs 50 (max.capacity : 50 wind turbines per farm) (4) Maintenance scenario: low Operating Maintenance (lOM) or high Operating Maintenance (hOM) (5) Foundation type: only fixed (xfond) vs floating & fixed (both: bfond) (6) Failure rate: low Failure Rate (lFR) or high Failure Rate (hFR) (7) Electricity loss: 4 % electricity loss included (Lo) vs non-included electricity loss (NoLo) (8) geo: GeoTIFF file WCS GeoTIFF cc_15_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_30_hOM_bfond_lFR_Lo cc_15_30_hOM_bfond_lFR_Lo WCS GeoTIFF cc_15_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_30_lOM_bfond_hFR_Lo cc_15_30_lOM_bfond_hFR_Lo WCS GeoTIFF cc_15_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_30_lOM_bfond_lFR_Lo cc_15_30_lOM_bfond_lFR_Lo WCS GeoTIFF cc_15_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_40_hOM_bfond_hFR_Lo cc_15_40_hOM_bfond_hFR_Lo WCS GeoTIFF cc_15_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_40_hOM_bfond_lFR_Lo cc_15_40_hOM_bfond_lFR_Lo WCS GeoTIFF cc_15_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_40_lOM_bfond_hFR_Lo cc_15_40_lOM_bfond_hFR_Lo WCS GeoTIFF cc_15_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_40_lOM_bfond_lFR_Lo cc_15_40_lOM_bfond_lFR_Lo WCS GeoTIFF cc_15_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_50_hOM_bfond_hFR_Lo cc_15_50_hOM_bfond_hFR_Lo WCS GeoTIFF cc_15_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_50_hOM_bfond_lFR_Lo cc_15_50_hOM_bfond_lFR_Lo WCS GeoTIFF cc_15_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_50_lOM_bfond_hFR_Lo cc_15_50_lOM_bfond_hFR_Lo WCS GeoTIFF cc_15_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_15_50_lOM_bfond_lFR_Lo cc_15_50_lOM_bfond_lFR_Lo WCS GeoTIFF cc_15_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_30_hOM_bfond_hFR_Lo cc_20_30_hOM_bfond_hFR_Lo WCS GeoTIFF cc_20_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_30_hOM_bfond_lFR_Lo cc_20_30_hOM_bfond_lFR_Lo WCS GeoTIFF cc_20_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_30_lOM_bfond_hFR_Lo cc_20_30_lOM_bfond_hFR_Lo WCS GeoTIFF cc_20_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_30_lOM_bfond_lFR_Lo cc_20_30_lOM_bfond_lFR_Lo WCS GeoTIFF cc_20_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_40_hOM_bfond_hFR_Lo cc_20_40_hOM_bfond_hFR_Lo WCS GeoTIFF cc_20_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_40_hOM_bfond_lFR_Lo cc_20_40_hOM_bfond_lFR_Lo WCS GeoTIFF cc_20_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_40_lOM_bfond_hFR_Lo cc_20_40_lOM_bfond_hFR_Lo WCS GeoTIFF cc_20_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_40_lOM_bfond_lFR_Lo cc_20_40_lOM_bfond_lFR_Lo WCS GeoTIFF cc_20_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_50_hOM_bfond_hFR_Lo cc_20_50_hOM_bfond_hFR_Lo WCS GeoTIFF cc_20_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_50_hOM_bfond_lFR_Lo cc_20_50_hOM_bfond_lFR_Lo WCS GeoTIFF cc_20_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_50_lOM_bfond_hFR_Lo cc_20_50_lOM_bfond_hFR_Lo WCS GeoTIFF cc_20_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_20_50_lOM_bfond_lFR_Lo cc_20_50_lOM_bfond_lFR_Lo WCS GeoTIFF cc_20_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_30_hOM_bfond_hFR_Lo cc_25_30_hOM_bfond_hFR_Lo WCS GeoTIFF cc_25_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_30_hOM_bfond_lFR_Lo cc_25_30_hOM_bfond_lFR_Lo WCS GeoTIFF cc_25_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_30_lOM_bfond_hFR_Lo cc_25_30_lOM_bfond_hFR_Lo WCS GeoTIFF cc_25_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_30_lOM_bfond_lFR_Lo cc_25_30_lOM_bfond_lFR_Lo WCS GeoTIFF cc_25_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_40_hOM_bfond_hFR_Lo cc_25_40_hOM_bfond_hFR_Lo WCS GeoTIFF cc_25_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_40_hOM_bfond_lFR_Lo cc_25_40_hOM_bfond_lFR_Lo WCS GeoTIFF cc_25_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_40_lOM_bfond_hFR_Lo cc_25_40_lOM_bfond_hFR_Lo WCS GeoTIFF cc_25_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_40_lOM_bfond_lFR_Lo cc_25_40_lOM_bfond_lFR_Lo WCS GeoTIFF cc_25_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_50_hOM_bfond_hFR_Lo cc_25_50_hOM_bfond_hFR_Lo WCS GeoTIFF cc_25_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_50_hOM_bfond_lFR_Lo cc_25_50_hOM_bfond_lFR_Lo WCS GeoTIFF cc_25_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_50_lOM_bfond_hFR_Lo cc_25_50_lOM_bfond_hFR_Lo WCS GeoTIFF cc_25_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:cc_25_50_lOM_bfond_lFR_Lo cc_25_50_lOM_bfond_lFR_Lo Legend for understanding map title names and their related configuration eg: cc_15_50_lOM_bfond_hFR_Lo_geo Each parameter is separated with an underscore (_) (1) Impact category: cc= climate change, res= resources, daly= daly, eco= ecosystem (2) Life time: 15 years vs 20 years vs 25 years (3) Number of wind turbines per farm: 30 vs 40 vs 50 (max.capacity : 50 wind turbines per farm) (4) Maintenance scenario: low Operating Maintenance (lOM) or high Operating Maintenance (hOM) (5) Foundation type: only fixed (xfond) vs floating & fixed (both: bfond) (6) Failure rate: low Failure Rate (lFR) or high Failure Rate (hFR) (7) Electricity loss: 4 % electricity loss included (Lo) vs non-included electricity loss (NoLo) (8) geo: GeoTIFF file WCS GeoTIFF cc_25_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 osm:coastlines coastlines OpenStreetMap coastlines from (http://openstreetmapdata.com/data/coastlines) features lines EPSG:4326 CRS:84 -180.0 180.0 -78.6586252 83.6664731 tmp:daily_irradiation_dni_year daily_irradiation_dni_year WCS GeoTIFF daily_irradiation_dni_year EPSG:4326 CRS:84 24.0 37.5 32.0 43.0 tmp:daily_irradiation_ghi_2005_october daily_irradiation_ghi_2005_october WCS GeoTIFF daily_irradiation_ghi_2005_october EPSG:4326 CRS:84 24.0 37.5 10.0 21.0 energeo:daly_15_30_hOM_bfond_hFR_Lo daly_15_30_hOM_bfond_hFR_Lo WCS GeoTIFF daly_15_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_30_hOM_bfond_lFR_Lo daly_15_30_hOM_bfond_lFR_Lo WCS GeoTIFF daly_15_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_30_lOM_bfond_hFR_Lo daly_15_30_lOM_bfond_hFR_Lo WCS GeoTIFF daly_15_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_30_lOM_bfond_lFR_Lo daly_15_30_lOM_bfond_lFR_Lo WCS GeoTIFF daly_15_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_40_hOM_bfond_hFR_Lo daly_15_40_hOM_bfond_hFR_Lo WCS GeoTIFF daly_15_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_40_hOM_bfond_lFR_Lo daly_15_40_hOM_bfond_lFR_Lo WCS GeoTIFF daly_15_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_40_lOM_bfond_hFR_Lo daly_15_40_lOM_bfond_hFR_Lo WCS GeoTIFF daly_15_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_40_lOM_bfond_lFR_Lo daly_15_40_lOM_bfond_lFR_Lo WCS GeoTIFF daly_15_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_50_hOM_bfond_hFR_Lo daly_15_50_hOM_bfond_hFR_Lo WCS GeoTIFF daly_15_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_50_hOM_bfond_lFR_Lo daly_15_50_hOM_bfond_lFR_Lo WCS GeoTIFF daly_15_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_50_lOM_bfond_hFR_Lo daly_15_50_lOM_bfond_hFR_Lo WCS GeoTIFF daly_15_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_15_50_lOM_bfond_lFR_Lo daly_15_50_lOM_bfond_lFR_Lo WCS GeoTIFF daly_15_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_30_hOM_bfond_hFR_Lo daly_20_30_hOM_bfond_hFR_Lo WCS GeoTIFF daly_20_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_30_hOM_bfond_lFR_Lo daly_20_30_hOM_bfond_lFR_Lo WCS GeoTIFF daly_20_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_30_lOM_bfond_hFR_Lo daly_20_30_lOM_bfond_hFR_Lo WCS GeoTIFF daly_20_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_30_lOM_bfond_lFR_Lo daly_20_30_lOM_bfond_lFR_Lo WCS GeoTIFF daly_20_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_40_hOM_bfond_hFR_Lo daly_20_40_hOM_bfond_hFR_Lo WCS GeoTIFF daly_20_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_40_hOM_bfond_lFR_Lo daly_20_40_hOM_bfond_lFR_Lo WCS GeoTIFF daly_20_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_40_lOM_bfond_hFR_Lo daly_20_40_lOM_bfond_hFR_Lo WCS GeoTIFF daly_20_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_40_lOM_bfond_lFR_Lo daly_20_40_lOM_bfond_lFR_Lo WCS GeoTIFF daly_20_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_50_hOM_bfond_hFR_Lo daly_20_50_hOM_bfond_hFR_Lo WCS GeoTIFF daly_20_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_50_hOM_bfond_lFR_Lo daly_20_50_hOM_bfond_lFR_Lo WCS GeoTIFF daly_20_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_50_lOM_bfond_hFR_Lo daly_20_50_lOM_bfond_hFR_Lo WCS GeoTIFF daly_20_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_20_50_lOM_bfond_lFR_Lo daly_20_50_lOM_bfond_lFR_Lo WCS GeoTIFF daly_20_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_30_hOM_bfond_hFR_Lo daly_25_30_hOM_bfond_hFR_Lo WCS GeoTIFF daly_25_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_30_hOM_bfond_lFR_Lo daly_25_30_hOM_bfond_lFR_Lo WCS GeoTIFF daly_25_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_30_lOM_bfond_hFR_Lo daly_25_30_lOM_bfond_hFR_Lo WCS GeoTIFF daly_25_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_30_lOM_bfond_lFR_Lo daly_25_30_lOM_bfond_lFR_Lo WCS GeoTIFF daly_25_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_40_hOM_bfond_hFR_Lo daly_25_40_hOM_bfond_hFR_Lo WCS GeoTIFF daly_25_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_40_hOM_bfond_lFR_Lo daly_25_40_hOM_bfond_lFR_Lo WCS GeoTIFF daly_25_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_40_lOM_bfond_hFR_Lo daly_25_40_lOM_bfond_hFR_Lo WCS GeoTIFF daly_25_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_40_lOM_bfond_lFR_Lo daly_25_40_lOM_bfond_lFR_Lo WCS GeoTIFF daly_25_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_50_hOM_bfond_hFR_Lo daly_25_50_hOM_bfond_hFR_Lo WCS GeoTIFF daly_25_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_50_hOM_bfond_lFR_Lo daly_25_50_hOM_bfond_lFR_Lo WCS GeoTIFF daly_25_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_50_lOM_bfond_hFR_Lo daly_25_50_lOM_bfond_hFR_Lo WCS GeoTIFF daly_25_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:daly_25_50_lOM_bfond_lFR_Lo daly_25_50_lOM_bfond_lFR_Lo WCS GeoTIFF daly_25_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 gn:diva_gis_countries DIVA-GIS countries source: http://www.diva-gis.org/Data features countries EPSG:4326 CRS:84 -179.99999999999997 180.0 -90.00000001886963 83.6274185352932 energeo:eco_15_30_hOM_bfond_hFR_Lo eco_15_30_hOM_bfond_hFR_Lo WCS GeoTIFF eco_15_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_30_hOM_bfond_lFR_Lo eco_15_30_hOM_bfond_lFR_Lo WCS GeoTIFF eco_15_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_30_lOM_bfond_hFR_Lo eco_15_30_lOM_bfond_hFR_Lo WCS GeoTIFF eco_15_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_30_lOM_bfond_lFR_Lo eco_15_30_lOM_bfond_lFR_Lo WCS GeoTIFF eco_15_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_40_hOM_bfond_hFR_Lo eco_15_40_hOM_bfond_hFR_Lo WCS GeoTIFF eco_15_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_40_hOM_bfond_lFR_Lo eco_15_40_hOM_bfond_lFR_Lo WCS GeoTIFF eco_15_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_40_lOM_bfond_hFR_Lo eco_15_40_lOM_bfond_hFR_Lo WCS GeoTIFF eco_15_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_40_lOM_bfond_lFR_Lo eco_15_40_lOM_bfond_lFR_Lo WCS GeoTIFF eco_15_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_50_hOM_bfond_hFR_Lo eco_15_50_hOM_bfond_hFR_Lo WCS GeoTIFF eco_15_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_50_hOM_bfond_lFR_Lo eco_15_50_hOM_bfond_lFR_Lo WCS GeoTIFF eco_15_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_50_lOM_bfond_hFR_Lo eco_15_50_lOM_bfond_hFR_Lo WCS GeoTIFF eco_15_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_15_50_lOM_bfond_lFR_Lo eco_15_50_lOM_bfond_lFR_Lo WCS GeoTIFF eco_15_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_30_hOM_bfond_hFR_Lo eco_20_30_hOM_bfond_hFR_Lo WCS GeoTIFF eco_20_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_30_hOM_bfond_lFR_Lo eco_20_30_hOM_bfond_lFR_Lo WCS GeoTIFF eco_20_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_30_lOM_bfond_hFR_Lo eco_20_30_lOM_bfond_hFR_Lo WCS GeoTIFF eco_20_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_30_lOM_bfond_lFR_Lo eco_20_30_lOM_bfond_lFR_Lo WCS GeoTIFF eco_20_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_40_hOM_bfond_hFR_Lo eco_20_40_hOM_bfond_hFR_Lo WCS GeoTIFF eco_20_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_40_hOM_bfond_lFR_Lo eco_20_40_hOM_bfond_lFR_Lo WCS GeoTIFF eco_20_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_40_lOM_bfond_hFR_Lo eco_20_40_lOM_bfond_hFR_Lo WCS GeoTIFF eco_20_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_40_lOM_bfond_lFR_Lo eco_20_40_lOM_bfond_lFR_Lo WCS GeoTIFF eco_20_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_50_hOM_bfond_hFR_Lo eco_20_50_hOM_bfond_hFR_Lo WCS GeoTIFF eco_20_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_50_hOM_bfond_lFR_Lo eco_20_50_hOM_bfond_lFR_Lo WCS GeoTIFF eco_20_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_50_lOM_bfond_hFR_Lo eco_20_50_lOM_bfond_hFR_Lo WCS GeoTIFF eco_20_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_20_50_lOM_bfond_lFR_Lo eco_20_50_lOM_bfond_lFR_Lo WCS GeoTIFF eco_20_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_30_hOM_bfond_hFR_Lo eco_25_30_hOM_bfond_hFR_Lo WCS GeoTIFF eco_25_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_30_hOM_bfond_lFR_Lo eco_25_30_hOM_bfond_lFR_Lo WCS GeoTIFF eco_25_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_30_lOM_bfond_hFR_Lo eco_25_30_lOM_bfond_hFR_Lo WCS GeoTIFF eco_25_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_30_lOM_bfond_lFR_Lo eco_25_30_lOM_bfond_lFR_Lo WCS GeoTIFF eco_25_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_40_hOM_bfond_hFR_Lo eco_25_40_hOM_bfond_hFR_Lo WCS GeoTIFF eco_25_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_40_hOM_bfond_lFR_Lo eco_25_40_hOM_bfond_lFR_Lo WCS GeoTIFF eco_25_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_40_lOM_bfond_hFR_Lo eco_25_40_lOM_bfond_hFR_Lo WCS GeoTIFF eco_25_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_40_lOM_bfond_lFR_Lo eco_25_40_lOM_bfond_lFR_Lo WCS GeoTIFF eco_25_40_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_50_hOM_bfond_hFR_Lo eco_25_50_hOM_bfond_hFR_Lo WCS GeoTIFF eco_25_50_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_50_hOM_bfond_lFR_Lo eco_25_50_hOM_bfond_lFR_Lo WCS GeoTIFF eco_25_50_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_50_lOM_bfond_hFR_Lo eco_25_50_lOM_bfond_hFR_Lo WCS GeoTIFF eco_25_50_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:eco_25_50_lOM_bfond_lFR_Lo eco_25_50_lOM_bfond_lFR_Lo WCS GeoTIFF eco_25_50_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 mapserv:encours encours encours features EPSG:4326 CRS:84 -122.156 152.8419 -25.34255 47.704 energeo:environmental_performances_of_offshore_wind_energy Environmental performances associated to offshore wind energy generation in Northern Europe This Web Map Service provides maps of site-specific environmental performances associated to offshore wind energy generation in Northern Europe. These maps have been generated from dedicated algorithm combining Life Cycle Assessment (LCA) results with technical parameters and geo-dependent data having an influence on: foundation choice criteria (water depth), on electricity generation potentials (turbine power curve, wind speed distribution), on transport impact (distance to the nearest harbor), on transmission cables length (distance to shore). Final environmental impacts categories are assessed from the method IMPACT2002+focusing on climate change, resources depletion, human health and ecosystem quality. WCS GeoTIFF environmental_map EPSG:4326 CRS:84 -25.005594663681 25.044407347718998 46.097147971656995 66.008446937215 mapserv:g100_06 g100_06 g100_06 WCS GeoTIFF EPSG:3035 CRS:84 -72.8055682856281 90.38229972850304 22.21517674443605 81.72681680050277 gn:gboundaries gboundaries features gboundaries EPSG:4326 CRS:84 -1800.0 180.0 -89.0 83.0 europa:hc3map_monthly_avg_dni hc3map_monthly_avg_dni The HC3Map Web Service provides maps of 5-years average of the monthly irradiation, i.e., the mean energy received during a whole month per square meter. Irradiation is expressed in kWh/m2. Period is 2004-2008. Two maps are provided: one for the global irradiation received on a horizontal plane (GHI), the other for the direct irradiation received on a plane always facing the sun (DNI). These maps are computed from irradiances of the HelioClim 3 database. Provider: Ecole des Mines de Paris / Armines (France). WCS GeoTIFF hc3map_monthly_avg_dni EPSG:4326 CRS:84 -16.75 45.083099997400005 35.8198257264 55.9302743 europa:hc3map_monthly_avg_ghi hc3map_monthly_avg_ghi The HC3Map Web Service provides maps of 5-years average of the monthly irradiation, i.e., the mean energy received during a whole month per square meter. Irradiation is expressed in kWh/m2. Period is 2004-2008. Two maps are provided: one for the global irradiation received on a horizontal plane (GHI), the other for the direct irradiation received on a plane always facing the sun (DNI). These maps are computed from irradiances of the HelioClim 3 database. Provider: Ecole des Mines de Paris / Armines (France). WCS GeoTIFF hc3map_monthly_avg_ghi EPSG:4326 CRS:84 -16.75 45.083099997400005 35.8198257264 55.9302743 energeo-aip3:impact_00E_00 impact_00E_00 R_tilt00deg_azim00deg WCS GeoTIFF EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_00E_30 impact_00E_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_00E_45 impact_00E_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_00E_60 impact_00E_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_00E_90 impact_00E_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15E_30 impact_15E_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15E_45 impact_15E_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15E_60 impact_15E_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15E_90 impact_15E_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15W_30 impact_15W_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15W_45 impact_15W_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15W_60 impact_15W_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_15W_90 impact_15W_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30E_30 impact_30E_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30E_45 impact_30E_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30E_60 impact_30E_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30E_90 impact_30E_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30W_30 impact_30W_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30W_45 impact_30W_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30W_60 impact_30W_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_30W_90 impact_30W_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45E_30 impact_45E_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45E_45 impact_45E_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45E_60 impact_45E_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45E_90 impact_45E_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45W_30 impact_45W_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45W_45 impact_45W_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45W_60 impact_45W_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_45W_90 impact_45W_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90E_30 impact_90E_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90E_45 impact_90E_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90E_60 impact_90E_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90E_90 impact_90E_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90W_30 impact_90W_30 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90W_45 impact_90W_45 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90W_60 impact_90W_60 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 energeo-aip3:impact_90W_90 impact_90W_90 EPSG:4326 CRS:84 -60.0 60.0 -60.0 60.0 iremare:iremare-atl-voronoid-map iremare-atl-voronoid-map features iremare-atl-voronoid-map EPSG:4326 CRS:84 -8.787469014098564 4.9729186669630865 43.28916654372949 53.19456799525788 iremare:iremare-med-voronoid-map iremare-med-voronoid-map features iremare-med-voronoid-map EPSG:4326 CRS:84 -5.671106653482979 16.224081947361263 35.07663829525001 44.43041509808723 gn:land-shallow-topo land_shallow_topo_21600.geo MODIS RGB World source: https://visibleearth.nasa.gov/images/57752/blue-marble-land-surface-shallow-water-and-shaded-topography land_shallow_topo_21600.geo WCS GeoTIFF EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 merra:merra2012PostGIS merra2012PostGIS features merra2012 EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 merra_wind:merra_wind_speed merra_wind_speed Global wind intensity at 10 meters in meter per second (m/s) from MERRA for each year between 1985 year 2012 and the global average. MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The Project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. More information, including an FAQ and the file specification document that explains each of the products in detail, is available at the MERRA web site at the GMAO (http://gmao.gsfc.nasa.gov/merra/). The "Wind intensity" field in the catalog is an annual mean of the global 10-m wind field produced each 6 h at the native resolution of 0.5° in latitude x 0.625° in latitude. Annual mean values are available for each year from 1985 to 2012 as well as the global average for that period. merra_wind_speed features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1985 merra_year_1985 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1985 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1986 merra_year_1986 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1986 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1987 merra_year_1987 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1987 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1988 merra_year_1988 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1988 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1989 merra_year_1989 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1989 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1990 merra_year_1990 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1990 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1991 merra_year_1991 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1991 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1992 merra_year_1992 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1992 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1993 merra_year_1993 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1993 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1994 merra_year_1994 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1994 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1995 merra_year_1995 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_1995 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1996 merra_year_1996 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1996 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_1997 merra_year_1997 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1997 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1998 merra_year_1998 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1998 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_1999 merra_year_1999 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_1999 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2000 merra_year_2000 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2000 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_2001 merra_year_2001 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2001 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2002 merra_year_2002 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2002 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2003 merra_year_2003 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2003 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_2004 merra_year_2004 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2004 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2005 merra_year_2005 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2005 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_2006 merra_year_2006 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_2006 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2007 merra_year_2007 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_2007 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2008 merra_year_2008 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. features merra_year_2008 EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2009 merra_year_2009 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2009 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 merra_full:merra_year_2010 merra_year_2010 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2010 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2011 merra_year_2011 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2011 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.75 83.75 merra_full:merra_year_2012 merra_year_2012 The shapefile includes yearly mean fields from MERRA. Fields included in the file are: Latitude and longitude in decimal degree. t2m_k: 2-m-temperature in Kelvin ps_pa: Surface pressure in Pa. rh_percent: Relative humidity in %. tdp_k: dewpoint temperature in Kelvin ws10_mpers: wind speed at 10 m in m/s. dir10_deg : wind direction at 10 m in degree. merra_year_2012 features EPSG:4326 CRS:84 -180.0 179.66667175293 -59.25 83.75 tmp:nuts-test nuts-test features nuts-test EPSG:4326 CRS:84 -63.15119 55.83578 -21.38885 71.18416 mapserv:realise realise features realise EPSG:4326 CRS:84 -122.15 143.9098 -36.5889 54.629686 energeo:res_15_30_hOM_bfond_hFR_Lo res_15_30_hOM_bfond_hFR_Lo WCS GeoTIFF res_15_30_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_30_hOM_bfond_lFR_Lo res_15_30_hOM_bfond_lFR_Lo WCS GeoTIFF res_15_30_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_30_lOM_bfond_hFR_Lo res_15_30_lOM_bfond_hFR_Lo WCS GeoTIFF res_15_30_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_30_lOM_bfond_lFR_Lo res_15_30_lOM_bfond_lFR_Lo WCS GeoTIFF res_15_30_lOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_40_hOM_bfond_hFR_Lo res_15_40_hOM_bfond_hFR_Lo WCS GeoTIFF res_15_40_hOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_40_hOM_bfond_lFR_Lo res_15_40_hOM_bfond_lFR_Lo WCS GeoTIFF res_15_40_hOM_bfond_lFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_40_lOM_bfond_hFR_Lo res_15_40_lOM_bfond_hFR_Lo WCS GeoTIFF res_15_40_lOM_bfond_hFR_Lo EPSG:4326 CRS:84 -25.043782837128 25.043782837304 45.976133651709006 66.023866348449 energeo:res_15_40_lOM_bfond_lFR_Lo res_15_40_lOM_bfond_lFR_Lo WCS GeoTIFF res_15_40_lOM_bfond_lFR_Lo 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yearly_nasa_sse_derived_irradiation_tilt_045_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_045_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_045_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_045_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 050 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_050_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 055 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_055_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 060 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_060_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 065 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_065_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 070 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_070_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 075 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_075_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 080 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_080_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 085 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_085_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, 090 tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045E yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045W yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_090_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_derived_irradiation_tilt_lat_azim_Eq Yearly irradiation on tilted panel derived from NASE SSE, lat tilt, Eq WCS GeoTIFF yearly_nasa_sse_derived_irradiation_tilt_lat_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_000_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 000 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_000_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 005 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_005_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 010 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_010_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 015 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_015_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 020 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_020_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 025 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_025_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 030 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_030_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 035 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_035_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 040 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_040_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 045 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_045_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 050 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_050_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 055 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_055_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 060 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_060_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 065 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_065_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 070 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_070_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 075 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_075_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 080 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_080_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 085 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045E EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045W yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045W WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_085_azim_Eq045W EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_090_azim_Eq Yearly surface per irradiation on tilted panel derived from NASE SSE, 090 tilt, Eq WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_090_azim_Eq EPSG:4326 CRS:84 -180.0 180.0 -90.0 90.0 project_iea:yearly_nasa_sse_inv_irradiation_tilt_090_azim_Eq045E yearly_nasa_sse_inv_irradiation_tilt_090_azim_Eq045E WCS GeoTIFF yearly_nasa_sse_inv_irradiation_tilt_090_azim_Eq045E EPSG:4326 CRS:84 -180.0 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