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10m_bathymetry_F_5000 (MapServer)
Title 10m_bathymetry_F_5000
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99998938699997,-69.91619422299993,180.0000000000001,81.89032623900005
Layers 10m_bathymetry_F_5000
Map Name 10m_bathymetry_F_5000
Category
10m_bathymetry_G_4000 (MapServer)
Title 10m_bathymetry_G_4000
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99998938699997,-76.11980750399994,180.0000000000001,90.00000000000006
Layers 10m_bathymetry_G_4000
Map Name 10m_bathymetry_G_4000
Category
10m_bathymetry_H_3000 (MapServer)
Title 10m_bathymetry_H_3000
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99998938699997,-76.29583289499999,180.0000000000001,90.00000000000006
Layers 10m_bathymetry_H_3000
Map Name 10m_bathymetry_H_3000
Category
10m_bathymetry_I_2000 (MapServer)
Title 10m_bathymetry_I_2000
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99999999999997,-76.40313269999996,180.0000000000001,90.00000000000006
Layers 10m_bathymetry_I_2000
Map Name 10m_bathymetry_I_2000
Category
10m_bathymetry_J_1000 (MapServer)
Title 10m_bathymetry_J_1000
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99999999999997,-78.22869422299993,179.99952233200008,89.99976227400003
Layers 10m_bathymetry_J_1000
Map Name 10m_bathymetry_J_1000
Category
10m_glaciated_areas (MapServer)
Title 10m_glaciated_areas
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -179.99998938699997,-89.99993254999998,180.0000000000001,83.55756256700005
Layers 10m_glaciated_areas
Map Name 10m_glaciated_areas
Category
10m_lakes_europe (MapServer)
Title 10m_lakes_europe
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -9.597096320999981,30.52808258700003,60.19092858200008,69.51727936400005
Layers 10m_lakes_europe
Map Name 10m_lakes_europe
Category
2017_update.mxd (MapServer)
Title 2017_cityinitiatives
Author
Subject 2017 update for Cities’ participation in adaptation related international initiatives
Keywords Climate,Energy,Climate Adapt,Signatories
Copyright Text © EEA, Copenhagen 2017
Registered first time 27 Sep 2017
Service Description
Cities engaged in European and global adaptation initiatives . Many cities in Europe are engaged in European and global initiatives related to climate change adaptation. It can be assumed that cities involved in one or more of these initiatives are more aware of the issues of climate change adaptation, which leads to a greater chance of longer term commitment and action. Moreover, events and information platforms associated with the initiatives facilitate the exchange of knowledge through sharing of examples and lessons learnt. By June 2017, over 900 local authorities in the European region have signed up on adaptation to The Covenant of Mayors for Climate and Energy (including the signatories to Mayors Adapt prior to the merger with Covenant of Mayors). To find out detailed information about individual signatories, go to the Covenant of Mayors for Climate and Energy interactive map http://www.eumayors.eu/participation/covenant_map_en.html>. Other initiatives are relevant to adaptation too and add many more municipalities to the map. Such initiatives are C40 (global), Making Cities Resilient (UNISDR), the European Green Capital and the Green Leaf Award, and 100 Resilient Cities (Rockefeller Foundation). The distribution of cities shown on this map is not equal across Europe for different reasons, such as culture, national and regional support, or levels of awareness. However, there are actually many more municipalities that act on climate change adaptation, which just have not joined any of these initiatives.
Description
Cities’ participation in adaptation related international initiatives
SRS 102100
Extent -6825858.4802,1791154.3189000003,3715420.475400001,9828909.855499998
Layers Covenant of Mayors on Climate and Energy, 2017,Mayors Adapt,World Mayors Council on Climate Change,Making my citiy resilient (UNISDR),100 resilient cities,C40,European Green Capital,Green Leaf Award,Metropolis,Cities Initiatives 2017
Map Name Cities’ participation in adaptation related international initiatives 2017
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Annual_Precipitation_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean.,Annual Precipitation Change 2021-2050
Map Name Annual Precipitation Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Annual_Precipitation_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in annual precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. ,Annual Precipitation Change 2071-2100
Map Name Annual Precipitation Change 2071-2100
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Annual_Temperature_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in annual mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in annual mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean,Annual Temperature Change 2021-2050
Map Name Annual Temperature Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Annual_Temperature_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in annual mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in annual mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in annual mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. ,Annual Temperature Change 2071-2100
Map Name Annual Temperature Change 2071-2100
Category
biogeo_2005 (MapServer)
Title biogeo_2005
Author Koldo
Subject Biogeographical regions 2005
Keywords
Copyright Text Euroean Environment Agency
Registered first time 06 Oct 2014
Service Description
Biogeographical regions 2005
Description
Biogeographical regions 2005
SRS 4326
Extent -73.05360480099995,27.637802084000043,69.03025862100003,83.62359601300005
Layers geoserver.DBO.public_biogeo_2005
Map Name biogeo_2005
Category
biogeo_2008 (MapServer)
Title biogeo_2008
Author Koldo Goñi
Subject Biogeographical regions 2008
Keywords biogeo
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
biogeo_2008_simplify_1000 version is used.
Description
biogeo_2008_simplify_1000 version is used.
SRS 4326
Extent -31.275490184999967,27.639155807000066,34.594581719000075,70.09227001100004
Layers geoserver.DBO.public_biogeo_2008
Map Name biogeo_2008
Category
Casestudies (MapServer)
Title Casestudies
Author Koldo
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -8.481445311999948,5.684341886080802e-14,28.696289061000073,56.23571824100003
Layers Casestudies
Map Name Casestudies
Category
Change in annual mean number of days with extreme precipitation (> 20 mm/day) (MapServer)
Title Change_in_extreme_precipitation_LAEA
Author Lautenschlager et al., 2009. World Data Center for Climate.
Subject Annual mean num days with extreme precip(>20mm/day) between CCLM scen (2071-2100) and ref run (1961-1990) for IPCC scen A1B.
Keywords Extreme Rain,Climate Change
Copyright Text Lautenschlager et al., 2009. World Data Center for Climate.
Registered first time 06 Oct 2014
Service Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
SRS 3035
Extent 2635889.2247577887,1385857.1306917071,6525830.7614217885,5415981.703757143
Layers Change in annual mean number of days with extreme precipitation (> 20 mm/day)
Map Name Change_in_extreme_precipitation_LAEA
Category
Change in annual mean number of days with extreme precipitation (> 20 mm/day) (MapServer)
Title Change_in_extreme_precipitation_WM
Author Lautenschlager et al., 2009. World Data Center for Climate.
Subject Annual mean num days with extreme precip(>20mm/day) between CCLM scen (2071-2100) and ref run (1961-1990) for IPCC scen A1B.
Keywords Extreme Rain,Climate Change
Copyright Text Lautenschlager et al., 2009. World Data Center for Climate.
Registered first time 06 Oct 2014
Service Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
SRS 102100
Extent -1186965.7166999988,4104612.325000003,3850226.547600001,11465970.639899999
Layers Change in annual mean number of days with extreme precipitation (> 20 mm/day)
Map Name Change_in_extreme_precipitation_WM
Category
Change in annual mean number of days with extreme precipitation (> 20 mm/day) (MapServer)
Title Change_in_extreme_precipitation_WM_EoE
Author Lautenschlager et al., 2009. World Data Center for Climate.
Subject Annual mean num days with extreme precip(>20mm/day) between CCLM scen (2071-2100) and ref run (1961-1990) for IPCC scen A1B.
Keywords Extreme Rain,Climate Change
Copyright Text Lautenschlager et al., 2009. World Data Center for Climate.
Registered first time 06 Oct 2014
Service Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
Description
Map presents changes in annual mean number of days with extreme precipitation (> 20 mm/day) between 2071–2100 and 1961–1990 period, based on CCLM regional climate model, using IPCC scenario A1B. \n\nLautenschlager et al., 2009\nLautenschlager, M., Keuler, K., Wunram, C., Keup Thiel, E., Schubert, M., Will, A., Rockel, B. and Boehm, U., 2009, Climate Simulation with CLM, Climate of the 20th Century (run no.1, 2 and 3) and Scenarios A1B and B1 (run no.1 and 2), Data Stream 3: European region MPI-M/MaD. World Data Center for Climate.
SRS 102100
Extent -1186965.7166999988,4104612.325000003,3850226.547600001,11465970.639899999
Layers Change in annual mean number of days with extreme precipitation (> 20 mm/day) for 2071-2100
Map Name Change_in_extreme_precipitation_WM_EoE
Category
cities_adapt_initiatives (MapServer)
Title cities_adapt_initiatives
Author
Subject
Keywords initiatives,climate,adapt,EEA
Copyright Text EEA 2016
Registered first time 19 Jul 2016
Service Description
Participation of European cities in European and global city initiatives related to adaptation (2015).
Description
SRS
Extent -3100966.0257972367,-2409699.769704273,13209655.171599567,12915658.459601324
Layers Cities Initiatives,Mayors Adapt,Making my citiy resilient (UNISDR),C40,European Green Capital,Green Leaf Award,World Mayors Council on Climate Change,Metropolis,100 resilient cities,background data,Lakes,lakesmall,lakemedium,lakelarge,countryborder_K_P,countryborder,coastline,outside coverage,sea,countries
Map Name cities_adapt_initiatives
Category
2017_update.mxd (MapServer)
Title cities_adapt_initiatives_2017_update
Author
Subject 2017 update for Cities’ participation in adaptation related international initiatives
Keywords Climate,Energy,Climate Adapt,Signatories
Copyright Text © EEA, Copenhagen 2017
Registered first time 12 Jul 2017
Service Description
Cities engaged in European and global adaptation initiatives . Many cities in Europe are engaged in European and global initiatives related to climate change adaptation. It can be assumed that cities involved in one or more of these initiatives are more aware of the issues of climate change adaptation, which leads to a greater chance of longer term commitment and action. Moreover, events and information platforms associated with the initiatives facilitate the exchange of knowledge through sharing of examples and lessons learnt. By June 2017, over 900 local authorities in the European region have signed up on adaptation to The Covenant of Mayors for Climate and Energy (including the signatories to Mayors Adapt prior to the merger with Covenant of Mayors). To find out detailed information about individual signatories, go to the Covenant of Mayors for Climate and Energy interactive map http://www.eumayors.eu/participation/covenant_map_en.html>. Other initiatives are relevant to adaptation too and add many more municipalities to the map. Such initiatives are C40 (global), Making Cities Resilient (UNISDR), the European Green Capital and the Green Leaf Award, and 100 Resilient Cities (Rockefeller Foundation). The distribution of cities shown on this map is not equal across Europe for different reasons, such as culture, national and regional support, or levels of awareness. However, there are actually many more municipalities that act on climate change adaptation, which just have not joined any of these initiatives.
Description
Cities’ participation in adaptation related international initiatives
SRS 102100
Extent -6825858.4802,1791154.3189000003,5165556.104899999,10244032.160377735
Layers Covenant of Mayors on Climate and Energy, 2017,Cities Initiatives 2015,Mayors Adapt,Making my citiy resilient (UNISDR),C40,European Green Capital,Green Leaf Award,World Mayors Council on Climate Change,Metropolis,100 resilient cities
Map Name cities_adapt_initiatives
Category
cities_unisdr_initiative (MapServer)
Title cities_unisdr_initiative
Author
Subject
Keywords
Copyright Text
Registered first time 19 Jul 2016
Service Description
Description
SRS
Extent 1728708.4220889825,1035021.8568380214,5284632.0135043478,4065405.9662970956
Layers UNISDR
Map Name Map 2c insert
Category
ClimateAdapt_ThermalComfort (MapServer)
Title ClimateAdapt_ThermalComfort
Author
Subject
Keywords thermal,comfort,climate,adapt
Copyright Text EEA
Registered first time 19 Jul 2016
Service Description
Average number of days and nights with thermal discomfort occurring in the period from April to September
Description
SRS
Extent 1161885.5699420739,1343266.2681664429,6437424.9999999963,5524746.6524381517
Layers FINAL_ET_Indicator
Map Name Map 2c insert
Category
ClimateAdapt_Trust (MapServer)
Title ClimateAdapt_Trust
Author
Subject
Keywords climate,adapt,trust,EEA
Copyright Text EEA
Registered first time 19 Jul 2016
Service Description
Trust in other people.
Description
SRS
Extent 2660942.1210888992,1437207.960606996,6921044.6348918462,4907131.2661009543
Layers Share of survey replies that most people can be trusted, 2015 [%],Most people can be trusted, trend 2012-2015 [%]
Map Name Map 2c
Category
cta_irr_rb_base (MapServer)
Title cta_irr_rb_base
Author
Subject Ratio of irrigation water consumption to water availability (ClimWatAdapt project, baseline)
Keywords Water management,agriculture,Irrigation,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
The ratio of irrigation water consumption to water availability during June, July and August for ClimWatAdapt baseline.\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
Description
The ratio of irrigation water consumption to water availability during June, July and August for ClimWatAdapt baseline.\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers cta_irr_rb_base
Map Name cta_irr_rb_base
Category
cta_irr_rb_ecf_2025 (MapServer)
Title cta_irr_rb_ecf_2025
Author
Subject Ratio of irrigation water consumption to water availability (ClimWatAdapt project, 2025, EcF)
Keywords Water management,agricultural,irrigation,ClimWatAdapt
Copyright Text © Service Copyright EEA Copenhagen
Registered first time 06 Oct 2014
Service Description
The ratio of irrigation water consumption to water availability during June, July and August for 2025, SCENES scenario Economy First (EcF).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
Description
The ratio of irrigation water consumption to water availability during June, July and August for 2025, SCENES scenario Economy First (EcF).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers cta_irr_rb_ecf_2025
Map Name cta_irr_rb_ecf_2025
Category
cta_irr_rb_ecf_2050 (MapServer)
Title cta_irr_rb_ecf_2050
Author
Subject Ratio of irrigation water consumption to water availability (ClimWatAdapt project, 2050, EcF)
Keywords Water management,agriculture,irrigation,ClimWatAdapt
Copyright Text © Service Copyright EEA Copenhagen
Registered first time 06 Oct 2014
Service Description
The ratio of irrigation water consumption to water availability during June, July and August for 2050, SCENES scenario Economy First (EcF).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
Description
The ratio of irrigation water consumption to water availability during June, July and August for 2050, SCENES scenario Economy First (EcF).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers cta_irr_rb_ecf_2050
Map Name cta_irr_rb_ecf_2050
Category
cta_irr_rb_sue_2025 (MapServer)
Title cta_irr_rb_sue_2025
Author
Subject Ratio of irrigation water consumption to water availability (ClimWatAdapt project, 2025, SUE)
Keywords Water management,Agriculture,Irrigation,ClimWatAdapt
Copyright Text European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
The ratio of irrigation water consumption to water availability during June, July and August for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
Description
The ratio of irrigation water consumption to water availability during June, July and August for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers cta_irr_rb_sue_2025
Map Name cta_irr_rb_sue_2025
Category
cta_irr_rb_sue_2050 (MapServer)
Title cta_irr_rb_sue_2050
Author
Subject Ratio of irrigation water consumption to water availability (ClimWatAdapt project, 2050, SUE)
Keywords Water management,Agriculture,Irrigation,ClimWatAdapt
Copyright Text © Service Copyright EEA Copenhagen
Registered first time 06 Oct 2014
Service Description
The ratio of irrigation water consumption to water availability during June, July and August for 2050, SCENES scenario Sustainability Eventually (SuE). \n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
Description
The ratio of irrigation water consumption to water availability during June, July and August for 2050, SCENES scenario Sustainability Eventually (SuE). \n\nIn order to assess the vulnerability of the agricultural sector to climate change, the indicator “irrigation consumption-to-water availability” (c.t.a.) is introduced. Irrigation consumption refers to the part of the irrigation water that is really “consumed” by the crops and evapotranspirates (net irrigation requirements).\n\nThe amount of water used for irrigation has been calculated for the base year based on the baseline climate (1961-90). It must be noted that the future irrigation water requirements were calculated within SCENES, i.e. the climate change input differs from the climate data used in the ClimWatAdapt framework because another emission scenario and different GCM output were applied. The assessment is performed on the river basin level for average annual conditions as well as for the summer season (JJA). This indicator does not consider the reduction of natural flow by upstream consumptive use, thus the water resources are only available for irrigation.\n\nBy using this indicator, it is assumed that a drainage basin suffers from severe water stress if c.t.a. > 0.3 or, in other words, if irrigation consumption exceeds 40% of reliable annual (or seasonal) water availability. A c.t.a. below 0.3 indicates low to mid water stress. The thresholds are chosen arbitrarily but have been derived from EEA (2003) which shows a figure for the water consumption index ranging from (almost) zero to 30% in Europe. According to EEA (2003), the average water consumption index in Europe is 3%.
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers cta_irr_rb_sue_2050
Map Name cta_irr_rb_sue_2050
Category
espon_aggregate_potential_impact (MapServer)
Title espon_aggregate_potential_impact
Author Koldo Goñi
Subject Aggregate potential impact of climate change (ESPON Climate project)
Keywords Espon
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Weighted combination of physical (weight 0.19), environmental (weight 0.31), economic (weight 0.24) and cultural (weight 0.1) potential impacts of climate change. Weights are based on a Delphi survey of the ESPON Monitoring Committee. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Weighted combination of physical (weight 0.19), environmental (weight 0.31), economic (weight 0.24) and cultural (weight 0.1) potential impacts of climate change. Weights are based on a Delphi survey of the ESPON Monitoring Committee. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_aggregate_potential_impact
Category
espon_change_in_annual_mean_precipitation_in_summer_months (MapServer)
Title espon_change_in_annual_mean_precipitation_in_summer_months
Author Koldo Goñi
Subject Change in annual mean precipitation in summer months (ESPON climate project))
Keywords ESPON,Precipitation
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Relative change in annual mean precipitation in meteorological summer months (June - August)\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Relative change in annual mean precipitation in meteorological summer months (June - August)\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_change_in_annual_mean_precipitation_in_summer_months
Category
espon_change_in_exposure_to_coastal_flooding (MapServer)
Title espon_change_in_exposure_to_coastal_flooding
Author Koldo Goñi
Subject Change in exposure to coastal flooding (ESPON Climate project)
Keywords ESPON,Inundation depth,sea level rise
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Inundation depth changes due to a sea level rise adjusted coastal storm surge event.\nCalculated on the basis of regional coastal storm surge heights projected by the DIVA model for a 100 year return event and heightened by a 1m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Inundation depth changes due to a sea level rise adjusted coastal storm surge event.\nCalculated on the basis of regional coastal storm surge heights projected by the DIVA model for a 100 year return event and heightened by a 1m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_change_in_exposure_to_coastal_flooding
Category
espon_change_in_exposure_to_river_flooding (MapServer)
Title espon_change_in_exposure_to_river_flooding
Author Koldo Goñi
Subject Change in regional exposure to river flooding (ESPON Climate project)
Keywords ESPON,Inundation depth,river flood
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Inundation depth changes due to climate induced changes in river flooding.\nCalculated by comparing the LISFLOOD model's 1961 - 1990 and 2071 - 2100 projections for a 100 year return event based on climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Inundation depth changes due to climate induced changes in river flooding.\nCalculated by comparing the LISFLOOD model's 1961 - 1990 and 2071 - 2100 projections for a 100 year return event based on climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_change_in_exposure_to_river_flooding
Category
espon_cultural_sensitivity (MapServer)
Title espon_cultural_sensitivity
Author Koldo Goñi
Subject Cultural sensitivity (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined sensitivity to climate change of cultural World Heritage sites and museums. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined sensitivity to climate change of cultural World Heritage sites and museums. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_cultural_sensitivity
Category
espon_decrease_in_annual_mean_number_of_days_with_snow_cover (MapServer)
Title espon_decrease_in_annual_mean_number_of_days_with_snow_cover
Author Koldo Goñi
Subject Change in annual mean number of days with snow cover (ESPON Climate project)
Keywords Espon,snow cover
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Change in annual mean number of days with snow covering the surface in the reference area.\nClimatic changes derived from comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Change in annual mean number of days with snow covering the surface in the reference area.\nClimatic changes derived from comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_decrease_in_annual_mean_number_of_days_with_snow_cover
Category
espon_economic_sensititvity (MapServer)
Title espon_economic_sensititvity
Author Koldo Goñi
Subject Economic sensitivity (ESPON Climate project)
Keywords economy
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined sensitivity to climate change of agriculture, forestry, summer and winter tourism, energy supply and demand. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined sensitivity to climate change of agriculture, forestry, summer and winter tourism, energy supply and demand. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_economic_sensititvity
Category
espon_environmental_sensitivity (MapServer)
Title espon_environmental_sensitivity
Author Koldo Goñi
Subject Environmental sensitivity (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Combined sensitivity to climate change of agriculture, forestry, summer and winter tourism, energy supply and demand. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined sensitivity to climate change of agriculture, forestry, summer and winter tourism, energy supply and demand. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_environmental_sensitivity
Category
espon_european_climate_change_regions (MapServer)
Title espon_european_climate_change_regions
Author Koldo Goñi
Subject European climate change regions (ESPON Climate project)
Keywords ESPON,Climate change regions
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Regions with similar climate change characteristics.\nClimate change regions derived from a cluster analysis of eight climate change variables (change in annual mean temperature, summer days, frost days, snow cover days, winter precipitation, summer precipitation, heavy rainfall days and annual mean evaporation).\nClimatic Changes calculated on the basis of a comparison of 1961 - 1990 and 2071 - 2100 climate projections from the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Regions with similar climate change characteristics.\nClimate change regions derived from a cluster analysis of eight climate change variables (change in annual mean temperature, summer days, frost days, snow cover days, winter precipitation, summer precipitation, heavy rainfall days and annual mean evaporation).\nClimatic Changes calculated on the basis of a comparison of 1961 - 1990 and 2071 - 2100 climate projections from the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_european_climate_change_regions
Category
espon_increase_in_annual_mean_number_of_summer_days (MapServer)
Title espon_increase_in_annual_mean_number_of_summer_days
Author Koldo Goñi
Subject Change in annual mean number of summer days (ESPON Climate project)
Keywords ESPON,Summer days
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Change in annual mean number of summer days with maximum air temperature above 25 degrees Celcius.\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Change in annual mean number of summer days with maximum air temperature above 25 degrees Celcius.\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_increase_in_annual_mean_number_of_summer_days
Category
espon_increase_in_annual_mean_temperature (MapServer)
Title espon_increase_in_annual_mean_temperature
Author Koldo Goñi
Subject Change in annual mean temperature (ESPON Climate project)
Keywords Espon,temperature
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Change in annual mean temperature in 2 metres above surface.\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.
Description
Change in annual mean temperature in 2 metres above surface.\nClimatic changes derived from a comparison of 1961 - 1990 and 2071 - 2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_increase_in_annual_mean_temperature
Category
espon_nuts3 (MapServer)
Title espon_nuts3
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -17.96619075899997,26.460017336000078,66.21055722200003,71.13495636000005
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_nuts3
Category
espon_physical_sensitivity (MapServer)
Title espon_physical_sensitivity
Author Koldo Goñi
Subject Physical sensitivity (ESPON Climate project)
Keywords
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined sensitivity to climate change of settlements, major roads, railways, airports, harbours, thermal power stations and refineries. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined sensitivity to climate change of settlements, major roads, railways, airports, harbours, thermal power stations and refineries. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_physical_sensitivity
Category
espon_potential_cultural_impact (MapServer)
Title espon_potential_cultural_impact
Author Koldo Goñi
Subject Potential cultural impact (ESPON climate project)
Keywords ESPON,world heritage sites
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined potential impacts of changes in inundation depths of a 100 year river flood event and a sea level rise adjusted 100 year coastal storm surge event on registered World Heritage sites and museums. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Fluvial inundation depths changes calculated by comparing 1961-1990 and 207102100 projections of the LISFLOOD model based on climate projections by the CCLM model for the IPCC SRES A1B scenario. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined potential impacts of changes in inundation depths of a 100 year river flood event and a sea level rise adjusted 100 year coastal storm surge event on registered World Heritage sites and museums. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Fluvial inundation depths changes calculated by comparing 1961-1990 and 207102100 projections of the LISFLOOD model based on climate projections by the CCLM model for the IPCC SRES A1B scenario. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_cultural_impact
Category
espon_potential_economic_impact (MapServer)
Title espon_potential_economic_impact
Author Koldo Goñi
Subject Potential economic impact (ESPON Climate project)
Keywords ESPON,Economy
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_economic_impact
Category
espon_potential_environmental_impact (MapServer)
Title espon_potential_environmental_impact
Author Koldo Goñi
Subject Potential environmental impact (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined potential impacts of changes in summer and winter precipitation, heavy rainfall days, annual mean temperature, summer days, frost days, snow cover days and annual mean evaporation on soil erosion, soil organic content, protected natural areas and forest fire sensitivity. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined potential impacts of changes in summer and winter precipitation, heavy rainfall days, annual mean temperature, summer days, frost days, snow cover days and annual mean evaporation on soil erosion, soil organic content, protected natural areas and forest fire sensitivity. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_environmental_impact
Category
espon_potential_physical_impact (MapServer)
Title espon_potential_physical_impact
Author Koldo
Subject Potential physical impact (ESPON Climate project)
Keywords ESPOON,Inundation depth,river flood,sea level rise,coastal storm
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_physical_impact
Category
espon_potential_social_impact (MapServer)
Title espon_potential_social_impact
Author Koldo Goñi
Subject Potential social impact (ESPON Climate project)
Keywords ESPO
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined potential impacts of change in inundation depths of a 100 year river flood and a sea level rise adjusted 100 year coastal storm event as well as changes in flash flood potential and summer heat on population. Impact calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario. Fluvial inundation depths changes based on LISFLOOD projections. Regional coastal storm surge heights projected by DIVA model were adjusted with 1 m sea level rise.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_social_impact
Category
espon_potential_vulnerability (MapServer)
Title espon_potential_vulnerability
Author Koldo Goñi
Subject Potential vulnerability of European regions to climate change (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Vulnerability calculated as the combination of regional potential impacts of climate change and regional capacity to adapt to climate change. The potential impacts were calculated as a combination of regional exposure to climate change (difference between 1961-1990 and 2071-2100 climate projections of eight climatic variables of the CCLM model for the IPCC SRES A1B scenario as well as the resulting inundation depth changes for a 100 year return flood event based on river flooding projections of the LSFLOOD model and coastal storm surge =height projections of the DIVA model adjusted with a 1 m sea level rise and most recent data on the weighted dimensions of physical, economic, social, environmental and cultural sensitivity to climate change. Adaptive capacity was calculated as a weighted combination of most recent data on economic, infrastructural, technological and institutional capacity as well as knowledge and awareness of climate change.
Description
Vulnerability calculated as the combination of regional potential impacts of climate change and regional capacity to adapt to climate change. The potential impacts were calculated as a combination of regional exposure to climate change (difference between 1961-1990 and 2071-2100 climate projections of eight climatic variables of the CCLM model for the IPCC SRES A1B scenario as well as the resulting inundation depth changes for a 100 year return flood event based on river flooding projections of the LSFLOOD model and coastal storm surge =height projections of the DIVA model adjusted with a 1 m sea level rise and most recent data on the weighted dimensions of physical, economic, social, environmental and cultural sensitivity to climate change. Adaptive capacity was calculated as a weighted combination of most recent data on economic, infrastructural, technological and institutional capacity as well as knowledge and awareness of climate change.
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_potential_vulnerability
Category
espon_response_capacity (MapServer)
Title espon_response_capacity
Author Koldo Goñi
Subject Response capacity of European regions in regard to climate (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
A total of 15 indicators were used to calculate the adaptive capacity index, while 10 indicators were used for the mitigative capacity index. The indices are calculated as weighted averages of normalized indicator values.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
A total of 15 indicators were used to calculate the adaptive capacity index, while 10 indicators were used for the mitigative capacity index. The indices are calculated as weighted averages of normalized indicator values.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_response_capacity
Category
espon_social_sensitivity (MapServer)
Title espon_social_sensitivity
Author Koldo Goñi
Subject Social sensitivity (ESPON Climate project)
Keywords ESPON
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Combined sensitivity to climate change of population in river flooding prone areas, in coastal storm surge prone areas, population prone to flash floods and heat sensitive population in urban heat islands. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Combined sensitivity to climate change of population in river flooding prone areas, in coastal storm surge prone areas, population prone to flash floods and heat sensitive population in urban heat islands. Regional sensitivities calculated on the basis of most recent statistical data.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_social_sensitivity
Category
espon_summer_heat_2100_population_impact (MapServer)
Title espon_summer_heat_2100_population_impact
Author Koldo Goñi
Subject Impact of summer heat on 2100 population (ESPON Climate project)
Keywords ESPON,Summer days,Population,urban heat islands,DEMIFER
Copyright Text European Environment Agency, Eurogeographics
Registered first time 06 Oct 2014
Service Description
Impacts of changes in summer days above 25oC on heat sensitive population in urban heat islands, using DEMIFER population projections for the year 2100. Impacts calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
Description
Impacts of changes in summer days above 25oC on heat sensitive population in urban heat islands, using DEMIFER population projections for the year 2100. Impacts calculated as combination of regional exposure to climatic changes and recent data on regional sensitivity. Climatic changes derived from a comparison of 1961-1990 and 2071-2100 climate projections by the CCLM model for the IPCC SRES A1B scenario.\n\nData source: http://www.eea.europa.eu/data-and-maps/data/external/espon-climate-project
SRS 4326
Extent -63.15345394999997,-21.38921974899995,55.83676905000004,71.18541724900007
Layers geoserver.DBO.public_espon_nuts3_02
Map Name espon_summer_heat_2100_population_impact
Category
Increase in the number of combined tropical nights and hot days under present and future climate conditions (MapServer)
Title HotDaysWarmNights_1971_2000
Author Fischer and Shaer, 2010
Subject Increase in the number of combined tropical nights (minimum temperature exceeding 20'C) and hot days (maximum temperature exceeding 35'C)
Keywords Climate change,temperature
Copyright Text EEA
Registered first time 06 Oct 2014
Service Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
SRS 4326
Extent -34.540000000000006,26.400000000000006,59.40000000000002,71.72000000000001
Layers Number of combined tropical nights (> 20C) and hot days (>35C) 1971-2000
Map Name HotDaysWarmNights_1971_2000
Category
Increase in the number of combined tropical nights and hot days under present and future climate conditions (MapServer)
Title HotDaysWarmNights_2021_2050
Author Fischer and Shaer, 2010
Subject Increase in the number of combined tropical nights (minimum temperature exceeding 20'C) and hot days (maximum temperature exceeding 35'C)
Keywords Climate change,temperature
Copyright Text EEA
Registered first time 06 Oct 2014
Service Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
SRS 4326
Extent -34.540000000000006,26.400000000000006,59.40000000000002,71.72000000000001
Layers Number of combined tropical nights (> 20C) and hot days (>35C) 2021-2050
Map Name HotDaysWarmNights_2021_2050
Category
Increase in the number of combined tropical nights and hot days under present and future climate conditions (MapServer)
Title HotDaysWarmNights_2071_2100
Author Fischer and Shaer, 2010
Subject Increase in the number of combined tropical nights (minimum temperature exceeding 20'C) and hot days (maximum temperature exceeding 35'C)
Keywords Climate change,temperature
Copyright Text EEA
Registered first time 06 Oct 2014
Service Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
Description
Climate-change projections suggest that European summer heatwaves will become more frequent and severe during this century, consistent with the observed trend of the past decades. The most severe impacts arise from multi-day heatwaves, associated with warm night-time temperatures and high relative humidity.\n\nData source: http://www.eea.europa.eu/data-and-maps/indicators/global-and-european-temperature-1/assessment
SRS 4326
Extent -34.540000000000006,26.400000000000006,59.40000000000002,71.72000000000001
Layers Number of combined tropical nights (> 20C) and hot days (>35C) 2071-2100
Map Name HotDaysWarmNights_2071_2100
Category
hydroelec_dams_rb_2025 (MapServer)
Title hydroelec_dams_rb_2025
Author Koldo
Subject Risk of losses in power production by hydroelectric dams (ClimWatAdapt project, 2025)
Keywords Water management,Hydropower,electricity,infraestructure,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Vulnerability of the hydropower sector, reservoir hydropower stations approach for 2025.\n\nReservoir stations are located below reservoirs and depend on the volume and on the difference in\nheight between the source and the water's outflow. Changes in quantity and timing of river runoff,\ntogether with increased reservoir evaporation will have a number of effects on the production of\nhydroelectric power. As we have no information on dams and reservoirs, we analysed the impact of\nclimate change on seasonal water availability on a river basin level, i.e. for winter (DJF) and summer\n(JJA) months. Especially the winter water storage is seen to be important. \n\nThere are 5 classes to describe the risk of losses in power production:\n1. high risk: winter availability and summer availability decrease (>5%) \n2. medium risk: winter availability decreases and summer availability increases\n3. low risk: winter availability increases and summer availability decreases\n4. very low: winter availability and summer availability increase\n5. ambiguous: no or small changes (+/- 5%)
Description
Vulnerability of the hydropower sector, reservoir hydropower stations approach for 2025.\n\nReservoir stations are located below reservoirs and depend on the volume and on the difference in\nheight between the source and the water's outflow. Changes in quantity and timing of river runoff,\ntogether with increased reservoir evaporation will have a number of effects on the production of\nhydroelectric power. As we have no information on dams and reservoirs, we analysed the impact of\nclimate change on seasonal water availability on a river basin level, i.e. for winter (DJF) and summer\n(JJA) months. Especially the winter water storage is seen to be important. \n\nThere are 5 classes to describe the risk of losses in power production:\n1. high risk: winter availability and summer availability decrease (>5%) \n2. medium risk: winter availability decreases and summer availability increases\n3. low risk: winter availability increases and summer availability decreases\n4. very low: winter availability and summer availability increase\n5. ambiguous: no or small changes (+/- 5%)
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers hydroelec_dams_rb_2025
Map Name hydroelec_dams_rb_2025
Category
hydroelec_dams_rb_2050 (MapServer)
Title hydroelec_dams_rb_2050
Author Koldo
Subject Risk of losses in power production by hydroelectric dams (ClimWatAdapt project, 2050)
Keywords Water management,Hydropower,electricity,infraestructure,ClimWatAdapt
Copyright Text European Environmentl Agency
Registered first time 06 Oct 2014
Service Description
Vulnerability of the hydropower sector, reservoir hydropower stations approach for 2050.\n\nReservoir stations are located below reservoirs and depend on the volume and on the difference in\nheight between the source and the water's outflow. Changes in quantity and timing of river runoff,\ntogether with increased reservoir evaporation will have a number of effects on the production of\nhydroelectric power. As we have no information on dams and reservoirs, we analysed the impact of\nclimate change on seasonal water availability on a river basin level, i.e. for winter (DJF) and summer\n(JJA) months. Especially the winter water storage is seen to be important. \n\nThere are 5 classes to describe the risk of losses in power production:\n1. high risk: winter availability and summer availability decrease (>5%) \n2. medium risk: winter availability decreases and summer availability increases\n3. low risk: winter availability increases and summer availability decreases\n4. very low: winter availability and summer availability increase\n5. ambiguous: no or small changes (+/- 5%)
Description
Vulnerability of the hydropower sector, reservoir hydropower stations approach for 2050.\n\nReservoir stations are located below reservoirs and depend on the volume and on the difference in\nheight between the source and the water's outflow. Changes in quantity and timing of river runoff,\ntogether with increased reservoir evaporation will have a number of effects on the production of\nhydroelectric power. As we have no information on dams and reservoirs, we analysed the impact of\nclimate change on seasonal water availability on a river basin level, i.e. for winter (DJF) and summer\n(JJA) months. Especially the winter water storage is seen to be important. \n\nThere are 5 classes to describe the risk of losses in power production:\n1. high risk: winter availability and summer availability decrease (>5%) \n2. medium risk: winter availability decreases and summer availability increases\n3. low risk: winter availability increases and summer availability decreases\n4. very low: winter availability and summer availability increase\n5. ambiguous: no or small changes (+/- 5%)
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers hydroelec_dams_rb_2050
Map Name hydroelec_dams_rb_2050
Category
ne_10m_lakes (MapServer)
Title ne_10m_lakes
Author Koldo Goñi
Subject
Keywords
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Description
SRS 4326
Extent -183.0685913511,-73.90643526503536,193.19680171510015,105.19208797203547
Layers ne_10m_lakes
Map Name ne_10m_lakes
Category
Relative_change_in_the_extreme_river_discharge (MapServer)
Title Relative_change_in_the_extreme_river_discharge
Author
Subject Relative change in 100-year return level of river discharge
Keywords Heavy precipitation, river discharge
Copyright Text EC JRC/IES
Registered first time 06 Oct 2014
Service Description
Relative change in the river discharge for flood events that have a probability to occur once every hundred years between the scenario run (2071-2100) and the control run (1961-1990). Simulations with LISFLOOD model driven by HIRHAM - HadAM3H/HadCM3 and IPCC SRES scenario A2. Only rivers with a catchment area of 1000 km2 or more are shown. Map elaboration by EC JRC/IES. Data source: http://www.eea.europa.eu/data-and-maps/data/external/global-runoff-database
Description
SRS
Extent 2672542.6757732444,1568097.0268093827,5977883.3715993706,5460032.4647003449
Layers Relative change in the river discharge for flood events that have a probability to occur once every hundred years between the scenario run (2071-2100) and the control run (1961-1990) (%)
Map Name Layers
Category
rtq95_rb_baseline (MapServer)
Title rtq95_rb_baseline
Author Koldo
Subject Maintenance of environmental minimum flows, summer (ClimWatAdapt project, baseline)
Keywords Water management,ClimatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Maintenance of the environmental minimum water requirements (environmental flows) for ClimWatAdapt baseline.\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3642
Description
Maintenance of the environmental minimum water requirements (environmental flows) for ClimWatAdapt baseline.\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3642
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers rtq95_rb_baseline
Map Name rtq95_rb_baseline
Category
rtq95_rb_ecf_2025 (MapServer)
Title rtq95_rb_ecf_2025
Author Koldo
Subject Maintainance of environmental minimum flows, summer (ClimWatAdapt project 2025, EcF)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2025, SCENES scenario Economy First (EcF).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3637
Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2025, SCENES scenario Economy First (EcF).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3637
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers rtq95_rb_ecf_2025
Map Name rtq95_rb_ecf_2025
Category
rtq95_rb_ecf_2050 (MapServer)
Title rtq95_rb_ecf_2050
Author Koldo
Subject Maintainance of environmental minimum flows, summer (ClimWatAdapt project, 2050, EcF)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2050, SCENES scenario Economy First (EcF).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3646
Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2050, SCENES scenario Economy First (EcF).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3646
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers rtq95_rb_ecf_2050
Map Name rtq95_rb_ecf_2050
Category
rtq95_rb_sue_2025 (MapServer)
Title rtq95_rb_sue_2025
Author Koldo
Subject Maintainance of environmental minimum flows, summer (ClimWatAdapt project, 2025, SUE)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2025, SCENES scenario Sustainability Eventually (SUE).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3637
Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2025, SCENES scenario Sustainability Eventually (SUE).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3637
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers rtq95_rb_sue_2025
Map Name rtq95_rb_sue_2025
Category
rtq95_rb_sue_2050 (MapServer)
Title rtq95_rb_sue_2050
Author Koldo
Subject Maintainance of environmental minimum flows, summer (ClimWatAdapt project, 2050, SUE)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3646
Description
Maintenance of the environmental minimum water requirements (environmental flows) for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nThe assessment is performed according to three classes:\nEnv. Flows depleted = residual flow equals 0-100% of baseline Q95\nEnv. Flows at risk = residual flow is 2-4 times larger than baseline Q95\nEnv. Flows maintained= residual flow is more than four times larger than baseline Q95.\n\nData source: http://climate-adapt.eea.europa.eu/viewaceitem?aceitem_id=3646
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers rtq95_rb_sue_2050
Map Name rtq95_rb_sue_2050
Category
Share_of_urbanised_area_potentially_flooded (MapServer)
Title Share_of_urbanised_area_potentially_flooded
Author
Subject Percentage of the city that would be flooded in case rivers rise one metre.
Keywords Heavy precipitation, flooded cities
Copyright Text EEA 2012
Registered first time 06 Oct 2014
Service Description
Percentage of the city that would be flooded in case rivers rise one metre. The potential flooded area is based on a 'volume model'. This model is based on water level and subsequent difference between modelled water level and the digital elevation model. The city is defined by its morphological form (Urban Morphological Zone) inside the core city boundaries derived Urban Audit (Eurostat, 2012). Data source: http://www.eea.europa.eu/data-and-maps/data/urban-morphological-zones-2006
Description
SRS
Extent 2649629.2219472895,1437219.8817599954,5793233.275792514,5190827.1346198553
Layers Percentage of the city that would be flooded in case rivers rise one metre
Map Name Layers
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Summer_Precipitation_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. ,Summer Precipitation Change 2021-2050
Map Name Summer Precipitation Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Summer_Precipitation_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in summer precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. ,Summer Precipitation Change 2071-2100
Map Name Summer Precipitation Change 2071-2100
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Summer_Temperature_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. ,Summer Temperature Change 2021-2050
Map Name Summer Temperature Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Summer_Temperature_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text Terms and conditions of use ENSEMBLES data held in the main ENSEMBLES data centres are made available over the internet without charge for use in research, education and commercial work. Users of ENSE
Registered first time 06 Oct 2014
Service Description
Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in summer mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. ,Summer Temperature Change 2071-2100
Map Name Summer Temperature Change 2071-2100
Category
wei_rb_base_ann (MapServer)
Title wei_rb_base_ann
Author Koldo
Subject Annual average water stress (ClimWatAdapt project, base line)
Keywords Water management,Water stress,WEI,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Annual average water stress indicator WEI on river basin level for ClimWatAdapt baseline.\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Annual average water stress indicator WEI on river basin level for ClimWatAdapt baseline.\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_base_ann
Map Name wei_rb_base_ann
Category
wei_rb_base_jja (MapServer)
Title wei_rb_base_jja
Author Koldo
Subject Water stress, summer (ClimWatAdapt project, base line)
Keywords Water management,Water stress,WEI,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for ClimWatAdapt base line.\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for ClimWatAdapt base line.\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_base_jja
Map Name wei_rb_base_jja
Category
wei_rb_ecf_2025_ann. (MapServer)
Title wei_rb_ecf_2025_ann
Author
Subject Annual average water stress (ClimWatAdapt project, 2025, EcF)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text © Service Copyright EEA Copenhagen
Registered first time 06 Oct 2014
Service Description
Annual average water stress indicator WEI on river basin level for 2025, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Annual average water stress indicator WEI on river basin level for 2025, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_ecf_2025_ann
Map Name wei_rb_ecf_2025_ann
Category
wei_rb_ecf_2025_jja (MapServer)
Title wei_rb_ecf_2025_jja
Author Koldo
Subject Water stress, summer (ClimWatAdapt project, 2025, EcF)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2025, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2025, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_ecf_2025_jja
Map Name wei_rb_ecf_2025_jja
Category
wei_rb_ecf_2050_ann (MapServer)
Title wei_rb_ecf_2050_ann
Author Koldo
Subject Annual average water stress (ClimWatAdapt project, 2050, EcF)
Keywords Water management,Water Stress,WEI,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Annual average water stress indicator WEI on river basin level for 2050, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Annual average water stress indicator WEI on river basin level for 2050, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_ecf_2050
Map Name wei_rb_ecf_2050_ann
Category
wei_rb_ecf_2050_jja (MapServer)
Title wei_rb_ecf_2050_jja
Author Koldo
Subject Water stress, summer (ClimWatAdapt project, 2050, EcF)
Keywords Water management,Water stress,WEI,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2050, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2050, SCENES scenario Economy First (EcF).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_ecf_2050
Map Name wei_rb_ecf_2050_jja
Category
wei_rb_sue_2025_ann (MapServer)
Title wei_rb_sue_2025_ann
Author Koldo
Subject Annual average water stress (ClimWatAdapt project, 2025, SUE)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Annual average water stress indicator WEI on river basin level for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Annual average water stress indicator WEI on river basin level for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_sue_2025_ann
Map Name wei_rb_sue_2025_ann
Category
wei_rb_sue_2025_jja (MapServer)
Title wei_rb_sue_2025_jja
Author Koldo
Subject Water stress, summer (ClimWatAdapt project, 2025, SUE)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_sue_2025_jja
Map Name wei_rb_sue_2025_jja
Category
wei_rb_sue_2050_ann (MapServer)
Title wei_rb_sue_2050_ann
Author Koldo
Subject Annual average water stress (ClimWatAdapt project, 2050, SUE)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Annual average water stress indicator WEI on river basin level for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. This indicator is widely used in scenario studies to address water shortage issues (Alcamo et al. 2007, Vorosmarty et al. 2000).\n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Annual average water stress indicator WEI on river basin level for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. This indicator is widely used in scenario studies to address water shortage issues (Alcamo et al. 2007, Vorosmarty et al. 2000).\n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability. Annual WEI is calculated on a river basin level for the baseline and the 2050s. Here, baseline conditions are defined as water availability averaged over the climate normal period 1961-90 and water withdrawals for the year 2005. For the 2050s, water availability is averaged over the period 2041-2070 (2050s) and calculated as the median of the hydrological simulations. Total water withdrawals are represented by two different socio-economic scenarios, the SCENES scenarios “Economy First” (EcF) and “Sustainability Eventually” (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_sue_2050_ann
Map Name wei_rb_sue_2050_ann
Category
wei_rb_sue_2050_jja (MapServer)
Title wei_rb_sue_2050_jja
Author Koldo
Subject Water stress, summer (ClimWatAdapt project, 2050, SUE)
Keywords Water management,WEI,Water stress,ClimWatAdapt
Copyright Text Eurpean environment Agency
Registered first time 06 Oct 2014
Service Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2050, SCENES scenario Sustainability Eventually (SuE). \n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Water stress indicator WEI for summer (June, July, and August) on river basin level for 2050, SCENES scenario Sustainability Eventually (SuE). \n\nA water stress indicator is defined as the total withdrawal of freshwater resources in relation to the long-term average availability of the freshwater water resources within a river (sub)basin. One of the most important indicators for water scarcity or water stress is the water exploitation index (WEI) or water stress indicator (w.t.a.), which is defined as the total water withdrawals-to-water availability ratio within a river basin. Water scarcity can be the result of intensive water use, low water availability (climate driven) or a combination of these pressures. The indicator provides to policy makers a quick overview of areas that may encounter water shortage problems. \n\nWEI or a w.t.a.-value between 0.0 and 0.2 is considered a low water stress, WEI between 0.2 and 0.4\nmedium water stress, and a value greater than 0.4 severe water stress. \n\nThis variant of the water exploitation index is defined as the ratio of water withdrawals in all sectors to water availability during June, July and August. Summer WEI is calculated for the summer season (June, July, August) on a river basin level forthe baseline and the 2050s. Water availability is averaged over the summer season from the climate normal period and the future time slice (2050s). As in 1), the median of the hydrological model simulations is used. Total water withdrawals are computed for the summer season of the years 2005 and 2050 (EcF and SuE). Here, annual values for the domestic, industry and livestock sectors are equally distributed to every month; irrigation water withdrawals are simulated on a monthly basis and aggregated to seasonal values.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wei_rb_sue_2050_jja
Map Name wei_rb_sue_2050_jja
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Winter_Precipitation_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in winter precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in winter precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in winter precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2021-2050 relative to 1961-1990 mean. ,Winter Precipitation Change 2021-2050
Map Name Winter Precipitation Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Winter_Precipitation_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in winter precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in winter precipitation in percentages under A1B scenario, multi-model ensemble mean for the time periods 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. ,Winter Precipitation Change 2071-2100
Map Name Winter Precipitation Change 2071-2100
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Winter_Temperature_changes_2021_2050
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2021-2050 relative to 1961-1990 mean. ,Winter Temperature Change 2021-2050
Map Name Winter Temperature Change 2021-2050
Category
Projected Changes in Temperature and Precipitation using the multimodal ENSEMBLE mean for 2021-2050 and 2071-2100 under A1B scenario (MapServer)
Title Winter_Temperature_changes_2071_2100
Author The 'ENSEMBLES' project
Subject Maps present changes in precipitation and temperature for two different future periods using ENSEMBLE mean of several RCMs
Keywords ENSEMBLES,climate change,precipitation,temperature
Copyright Text The 'ENSEMBLES' project, European Envrionment Agency
Registered first time 06 Oct 2014
Service Description
Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km. Data source: http://www.eea.europa.eu/data-and-maps/data/external/ensembles-fp6-project
Description
Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. Map presents changes using ensemble mean of several regional climate models (RCMs), run by different climate modelling communities in the frame of the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Data are presented as changes in relative terms (according to 1961-1990 period) in spatial resolution of approximately 25 km.
SRS 102100
Extent -2657752.8426894075,3391325.3802613253,5051439.164567381,11566675.033136608
Layers Projected changes in winter mean surface temperature (in K) under A1B scenario, multi-model ensemble mean for the time period 2071-2100 relative to 1961-1990 mean. ,Winter Temperature Change 2071-2100
Map Name Winter Temperature Change 2071-2100
Category
wu_to_lowflow_el_rb_base (MapServer)
Title wu_to_lowflow_el_rb_base
Author Koldo
Subject Cooling water stress during low flow conditions (ClimWatAdapt project, baseline)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Ratio of cooling water abstractions to Q90 for ClimWatAdapt baseline.\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Ratio of cooling water abstractions to Q90 for ClimWatAdapt baseline.\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wu_to_lowflow_el_rb_base
Map Name wu_to_lowflow_el_rb_base
Category
wu_to_lowflow_el_rb_ecf_2025 (MapServer)
Title wu_to_lowflow_el_rb_ecf_2025
Author Koldo
Subject Cooling water stress during low flow conditions (ClimWatAdapt project, 2025, EcF)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Ratio of cooling water abstractions to Q90 for 2025, SCENES scenario Economy First (EcF).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Ratio of cooling water abstractions to Q90 for 2025, SCENES scenario Economy First (EcF).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wu_to_lowflow_el_rb_ecf_2025
Map Name wu_to_lowflow_el_rb_ecf_2025
Category
wu_to_lowflow_el_rb_ecf_2050 (MapServer)
Title wu_to_lowflow_el_rb_ecf_2050
Author
Subject Cooling water stress during low flow conditions (ClimWatAdapt project, 2050, EcF)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Ratio of cooling water abstractions to Q90 for 2050, SCENES scenario Economy First (EcF).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Ratio of cooling water abstractions to Q90 for 2050, SCENES scenario Economy First (EcF).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wu_to_lowflow_el_rb_ecf_2050
Map Name wu_to_lowflow_el_rb_ecf_2050
Category
wu_to_lowflow_el_rb_sue_2025 (MapServer)
Title wu_to_lowflow_el_rb_sue_2025
Author Koldo
Subject Cooling water stress during low flow conditions (ClimWatAdapt project, 2025, SUE)
Keywords Water management,ClimWatAdapt
Copyright Text European Environment Agency
Registered first time 06 Oct 2014
Service Description
Ratio of cooling water abstractions to Q90 for for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Ratio of cooling water abstractions to Q90 for for 2025, SCENES scenario Sustainability Eventually (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wu_to_lowflow_el_rb_sue_2025
Map Name wu_to_lowflow_el_rb_sue_2025
Category
wu_to_lowflow_el_rb_sue_2050 (MapServer)
Title wu_to_lowflow_el_rb_sue_2050
Author Koldo
Subject Cooling water stress during low flow conditions (ClimWatAdapt project, 2050, SUE)
Keywords Water management,ClimWatAdapt
Copyright Text European environment Agency
Registered first time 06 Oct 2014
Service Description
Ratio of cooling water abstractions to Q90 for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
Description
Ratio of cooling water abstractions to Q90 for 2050, SCENES scenario Sustainability Eventually (SuE).\n\nData source: http://climate-adapt.eea.europa.eu/
SRS 4326
Extent -23.2506103515625,34.99969482421875,37.99908447265625,70.8328857421875
Layers wu_to_lowflow_el_rb_sue_2050
Map Name wu_to_lowflow_el_rb_sue_2050
Category