...
Table 1: List of key specifications of the ECDE climate hazard derived statistics.
Data type | Regional aggregation |
Projection | - |
Horizontal coverage | Europe |
Horizontal resolution | Regionally aggregated and regular lat-lon grid for hydrological model outputs (0.05° x 0.10°) |
Vertical resolution | Surface |
Vertical coverage | Single level |
Temporal coverage | 1940-2100 |
Temporal resolution | Monthly, seasonal and yearly |
File format | NetCDF 4 |
Conventions
Climate and Forecast (CF) Metadata Convention v1.6, Attribute Convention for Dataset Discovery (ACDD) v1.3
Available versions | v2.0 |
Update frequency | Annual |
Climate indicators definition
...
Table 2: Definition of the ECDE indicators.
Main Variables | ||
Variable | Units | Description |
Heat and cold | ||
Mean temperature | °C | Air temperature at 2m above the surface, averaged over a month, season or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Growing degree days | °C day | Cumulative daily degrees above a 5 °C daily mean 2m air temperature, summed over a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Heating degree days | °C day | Cumulative daily degrees below a 15.5 °C daily mean 2m air temperature, summed over a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Cooling degree days | °C day | Cumulative daily degrees above a 22 °C daily mean 2m air temperature, summed over a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Tropical nights | day | Number of days with daily minimum 2m air temperature above 20 °C in a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
| Hot days | day | Number of days with daily maximum 2m air temperature above 30 °C (alternative thresholds of 35 °C and 40 °C are also included). Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
| Warmest three day period | °C | The highest daily mean 2m air temperature averaged over a three-day window over a year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
Heatwave days | day | Annual count of climatological heatwave days. A climatological heatwave is a period of at least three consecutive days exceeding the 99th percentile of May–September daily maximum 2m air temperatures over 1991-2020. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
High UTCI days | day | Number of days with Universal Thermal Climate Index (UTCI) above 32 °C. UTCI is an equivalent temperature (°C) representing human physiological response to meteorological conditions, accounting for clothing adaptation to outdoor temperature. It is derived from four surface variables: 2m air temperature, relative humidity, wind speed, and mean radiant temperature. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
Frost days | day | Number of days with daily minimum 2m air temperature below 0 °C in a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Daily maximum temperature | °C | Highest daily maximum 2m air temperature in a month, season, or year (i.e., the warmest day). Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Daily minimum temperature | °C | Lowest daily minimum 2m air temperature in a month, season, or year (i.e., the coldest day). Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Growing season start | 1 | First day of the year when the mean 2m air temperature consistently exceeds or equals a specific threshold of 5 °C over 5 consecutive days. above 5°C. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available annually only. |
Growing season end | 1 | First day in the second half of the year when the daily mean 2m air temperature consistently falls below a specific threshold of 5 °C over 5 consecutive days. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available annually only. |
Growing season length | day | Number of days between the growing season start and growing season end. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available annually only. |
Wet and dry | ||
Total precipitation | mm period-1 | Total precipitation is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. The cumulative sum over a month, season or year is provided. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
Maximum consecutive five-day precipitation | mm | Largest 5-day precipitation total within a month, season, or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Extreme precipitation total | mm | Sum of daily precipitation exceeding the 95th percentile of daily precipitation over 1991-2020. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
Frequency of extreme precipitations | day | Number of days in a month, season, or year with precipitation above the 95th percentile of daily precipitation over 1991-2020. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Flood recurrence | m3 s-1 | Return values of annual maximum river discharge. Data are provided as the 2, 5, 10 and 50 year return period of annual daily maximum river discharge estimated using a Gumbel distribution. The period 1971–2000 provides the baseline data and is used for anomaly calculations. The data are available on monthly or annual time spans. |
Mean river discharge | m3 s-1 | The mean annual daily river discharge over a 30 year period. The period 1971–2000 provides the baseline data and is used for anomaly calculations. The data are available on monthly or annual time spans. |
Aridity actual | Dimensionless | Yearly and monthly mean ratio of actual evapotranspiration to precipitation over a 30-year period. Actual evapotranspiration is modelled using only available water. The period 1971–2000 provides the baseline data and is used for anomaly calculations. |
Consecutive dry days | day | Longest period of consecutive days with daily precipitation below 1 mm in a month, season or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Duration of meteorological droughts | month | Number of months in a year with anomalously low precipitation, based on the 3-month Standardised Precipitation Index (SPI-3) relative to the 1991–2020 reference period. The data are available annually only. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Magnitude of meteorological droughts | Dimensionless | The cumulative severity of drought events in a year, based on the 3-month Standardised Precipitation Index (SPI-3) relative to the 1991-2020 reference period. A drought event starts when SPI-3 values fall below -1 for at least two consecutive months and ends when the index returns positive. The magnitude of the event is defined as the sum of SPI-3 absolute values in the months of the drought episodes. The magnitude of the event is defined as the sum of SPI-3 absolute values in the months of the drought episodes. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Mean soil moisture | Dimensionless | Total amount of water held in the pores between soil particles. It is generally measured and expressed in two primary ways. Here, it is defined as the monthly mean value of soil moisture in the root zone as the fraction of the field capacity volume over a 30 year period. The period 1971–2000 provides the baseline data and is used for anomaly calculations. The data are available on monthly or annual time spans. |
Fire weather index | Dimensionless | A meteorologically based index used worldwide to estimate fire danger. Developed by the Canadian Forestry Service, it combines 2m air temperature, precipitation, relative humidity, and wind speed to estimate forest fire ignition and spread conditions. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available on monthly, seasonal, or annual time spans. |
Days with high fire danger | day | Number of days with a Fire Weather Index (FWI) above 30 in a month, season, or year, per the European Forest Fire Information System (EFFIS) classification. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Wind | ||
Mean wind speed | m s-1 | Mean speed of the 10m wind averaged over a month, season or year. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Extreme wind speed days | day | Number of days in a month, season, or year with 10m wind speed above the extreme threshold defined as the 98th percentile of surface wind speed over 1991-2020. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. |
Snow and ice | ||
Snowfall amount | mm | The cumulative snowfall precipitation during the Northern Hemisphere winter sports season (November to April). The period 1981–2010 provides the baseline data and is used for anomaly calculations. The data are available annually only. |
| Health | ||
Tiger mosquito season length | day | Duration of Aedes albopictus presence in days. This is also known as the mosquito season. Outside of this period mosquitoes die off or go into diapause. Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available annually only. |
Tiger mosquito suitability index | Dimensionless | Likelihood of favourable environmental conditions for Aedes albopictus presence from 0 unsuitable (no favourable conditions) to 100 (fully suitable). Two reference periods (1991–2020 and 1981–2010) provide the baseline data and are used for anomaly calculations. The data are available annually only. |
Note on Hydrological models:
...
Table 3: Derived statistics naming convention and definition.
Derived statistic | CDS API key | Definition |
| 30-year statistics | ||
Average | average | Climatological mean over a period of 30 years. For projections the ensemble mean across all available models is considered. The projection climatological periods are 2011–2040, 2041–2070, and 2071–2100 for most data, but for some datasets the period may differ. |
Absolute change | absolute_change | For projections the changes of 30 years climatological periods (avg_period) against the reference periods (ref_period) is provided. The projection climatological periods are 2011–2040, 2041–2070, and 2071–2100 for most data, but for some datasets the period may differ. |
Relative change (%) | relative_change | Same as above but expressed in percentage instead of absolute values. |
Uncertainty quantiles | uncertainty_quantiles | Climatological mean over periods of 30 years are computed for each ensemble member and the 17th, 50th and 83rd ensemble quantiles are provided to help estimate the uncertainty for 30 year periods. The projection climatological periods are 2011–2040, 2041–2070, and 2071–2100 for most data, but for some datasets the period may differ. |
Absolute change quantiles | absolute_change_quantiles | The projected absolute change over 30 years climatological periods with respect to a reference period are computed for each ensemble member and the 17th, 50th and 83rd ensemble quantiles are provided to help estimate the uncertainty of the projected changes. The projection climatological periods are 2011–2040, 2041–2070, and 2071–2100 for most data, but for some datasets the period may differ. The references periods considered are 1981-2010 and 1991-2020. |
Relative change quantiles | relative_change_quantiles
| Same as above but expressed in percentage instead of absolute values. |
| Global Warming Level | ||
GWL | gwl | Value of the indicators in a world with global average temperature increased by 1.5, 2, 3 and 4°C relative to pre industrial levels. |
GWL absolute changes | gwl_absolute_changes | Relative change between a given warming level and a reference period (ref_period). |
GWL relative changes | gwl_relative_changes | Relative change between a given warming level and a reference period (ref_period) expressed in percent. |
GWL quantiles | gwl_quantiles | The climatological mean over the GWL period are computed for each ensemble member (see GWL period in Appendix 1) and the 17th, 50th and 83rd ensemble quantiles are provided to help estimate the uncertainty for each GWL level. |
GWL absolute change quantiles | gwl_absolute_change_quantiles | The absolute change over the GWL period with respect to a reference period are computed for each ensemble member (see GWL period in Appendix 1) and the 17th, 50th and 83rd ensemble quantiles are provided to help estimate the uncertainty for each GWL level. |
GWL relative changes quantiles (%) | gwl_relative_change_quantiles | The relative change over the GWL period are computed for each ensemble member (see GWL period in Appendix 1) and the 17th, 50th and 83rd ensemble quantiles are provided to help estimate the uncertainty for each GWL level. |
| Anomalies | ||
Anomaly | anomaly | Historical anomaly time series. The “anomaly” is simply the difference from average conditions defined as the 30 year mean over a reference period (ref_period). Anomalies are provided with respect to both 1981 – 2010 and 1991 – 2020. |
Anomaly quantiles | anomaly_quantiles | Time series of the projected anomalies and smoothed anomalies. The values correspond to the 17th, 50th and 83rd ensemble quantiles of the anomalies. |
| Projected time series | ||
Quantiles time series | quantiles_time_series | Time series of the projected 17th, 50th and 83rd ensemble quantiles. |
| Climatology | ||
Climatology | climatology | Monthly mean and standard deviation of the indicators over 30 years periods allowing to plot the classic monthly climatology plots. |
File structure
Each derived statistic is distributed as a multidimensional NetCDF file. Table 4 specifies the available dimensions for each product type, facilitating consistent interpretation and use of the datasets. The possible dimensions are:
...
Table 4: Dimensions of each derived statistic.
Derived statistic | Dimensions | |
Reanalysis | Projections | |
Average | avg_period | avg_period |
Absolute change | ref_period | ref_period |
Relative change | ref_period | ref_period |
Uncertainty quantiles | avg_period | avg_period |
Absolute change quantiles | ref_period | ref_period |
Relative change quantiles | ref_period | ref_period |
GWL | - | gwl |
GWL changes | - | gwl |
GWL percent changes | - | gwl |
Anomaly | ref_period | - |
Anomaly quantiles | - | ref_period |
Ensemble quantiles | - | scenario |
Climatology | clim_period | clim_period |
Method
Input dataset
The hazard products are based on the indicators published in the Climate indicators for Europe from 1940 to 2100 derived from reanalysis and climate projections dataset, available in the Copernicus Climate Data Store (CDS). Detailed descriptions of these indicators are provided in the corresponding Product User Guide, while documentation of the underlying datasets can be found here.
...
Table 5: List of the ECDE indicators dataset versions.
Main Variables | |
Variable | v2.0 |
Heat and cold | |
Mean temperature | First release |
Growing degree days | First release |
Heating degree days | First release |
Cooling degree days | First release |
Tropical nights | First release |
Hot days | First release |
Warmest three-day period | First release |
Heatwave days - Climatological | First release |
High UTCI days | First release |
Frost days | First release |
Growing season start | First release |
Growing season end | First release |
Growing season length | First release |
Maximum temperature | First release |
Minimum temperature | First release |
Wet and dry | |
Total precipitation | First release |
Maximum consecutive five-day precipitation | First release |
Extreme precipitation total | First release |
Frequency of extreme precipitation | First release |
Flood recurrence | First release |
Mean river discharge | First release |
Aridity actual | First release |
Consecutive dry days | First release |
Duration of meteorological droughts | First release |
Magnitude of meteorological droughts | First release |
Mean soil moisture | First release |
Fire weather index | First release |
Days with high fire danger | First release |
Mean wind speed | First release |
Extreme wind speed days | First release |
Snow and ice | |
Snowfall amount | First release |
Health | |
Tiger mosquito season length | First release |
Tiger mosquito suitability index | First release |
Concluding remarks
The derived statistics presented in this documentation, derived from the underlying climate indicators dataset, offer harmonised user-ready information on key climate-related hazards across Europe covering the 1940-2100 period. These products are available for exploration and analysis through the interactive visualisation application on the European Climate Data Explorer hosted on the EEA’s Climate-ADAPT site. They are provided as a dataset to support further analysis by climate change adaptation practitioners that wish to have access to the underlying data of the ECDE. Designed to support adaptation planning and risk assessment, the products provide regionally aggregated data on hazards such as heat, cold, drought, flooding, and wind, building on established climate indicators. As climate data and scientific understanding evolve, these hazard products will continue to be updated and expanded, ensuring ongoing support for climate resilience planning across Europe.
...
Table 6: List of CMIP5 driving Earth System Models of the EURO-CORDEX experiment used by each project and corresponding dataset.
CNRM-CM5_r1i1p1 | ✔ | ✔ | ||
EC-EARTH_r3i1p1 | ✔ | ✔ | ✔ | |
GFDL-CM4_r1i1p1f1 | ||||
HadGEM2-ES_r1i1p1 | ✔ | ✔ | ✔ | ✔ |
IPSL-CM5A-MR_r1i1p1 | ✔ | ✔ | ✔ | |
MPI-ESM-LR_r1i1p1 | ✔ | ✔ | ✔ | ✔ |
NorESM1-M_r1i1p1 | ✔ |
Table 7: Central year of GWLs in CMIP5 simulations under RCP4.5 and RCP8.5. ESM's used in SIS Energy are highlighted in yellow.
| CMIP5 model_run | 1.5_rcp45 | 2_rcp45 | 3_rcp45 | 4_rcp45 | 1.5_rcp85 | 2_rcp85 | 3_rcp85 | 4_rcp85 |
|---|---|---|---|---|---|---|---|---|
| ACCESS1-0_r1i1p1 | 2033 | 2053 | NA | NA | 2028 | 2041 | 2062 | 2081 |
| ACCESS1-3_r1i1p1 | 2039 | 2056 | NA | NA | 2031 | 2042 | 2062 | 2082 |
| bcc-csm1-1_r1i1p1 | 2021 | 2043 | NA | NA | 2019 | 2036 | 2059 | 2083 |
| bcc-csm1-1-m_r1i1p1 | 2011 | 2035 | NA | NA | 2010 | 2028 | 2059 | 2085 |
| BNU-ESM_r1i1p1 | NA | NA | NA | NA | NA | NA | NA | NA |
| CanESM2_r1i1p1 | 2017 | 2031 | 2075 | NA | 2013 | 2026 | 2049 | 2068 |
| CCSM4_r1i1p1 | 2017 | 2039 | NA | NA | 2014 | 2030 | 2057 | 2078 |
| CESM1-BGC_r1i1p1 | 2018 | 2044 | NA | NA | 2017 | 2033 | 2059 | 2080 |
| CMCC-CM_r1i1p1 | 2034 | 2050 | NA | NA | 2029 | 2041 | 2061 | 2078 |
| CMCC-CMS_r1i1p1 | 2037 | 2055 | NA | NA | 2029 | 2041 | 2061 | 2077 |
| CNRM-CM5_r1i1p1 | 2036 | 2057 | NA | NA | 2030 | 2045 | 2067 | 2087 |
| CSIRO-Mk3-6-0_r1i1p1 | 2035 | 2048 | NA | NA | 2034 | 2044 | 2065 | 2082 |
| EC-EARTH_r12i1p1 | 2022 | 2044 | NA | NA | 2018 | 2034 | 2060 | 2082 |
| EC-EARTH_r3i1p1 | 2022 | 2044 | NA | NA | 2020 | 2038 | 2061 | 2081 |
| GFDL-CM3_r1i1p1 | 9999 | 9999 | 9999 | 9999 | 2022 | 2034 | 2054 | 2070 |
| GFDL-ESM2G_r1i1p1 | 2050 | NA | NA | NA | 2037 | 2054 | 2080 | NA |
| GFDL-ESM2M_r1i1p1 | 2046 | NA | NA | NA | 2036 | 2051 | 2082 | NA |
| HadGEM2-CC_r1i1p1 | 2036 | 2052 | NA | NA | 2027 | 2039 | 2056 | 2072 |
| HadGEM2-ES_r1i1p1 | 2028 | 2043 | 2078 | NA | 2023 | 2035 | 2054 | 2071 |
| inmcm4_r1i1p1 | 2060 | NA | NA | NA | 2044 | 2057 | 2083 | NA |
| IPSL-CM5A-LR_r1i1p1 | 2013 | 2030 | 2069 | NA | 2009 | 2025 | 2047 | 2065 |
| IPSL-CM5A-MR_r1i1p1 | 2016 | 2033 | 2077 | NA | 2015 | 2030 | 2050 | 2066 |
| IPSL-CM5B-LR_r1i1p1 | 2026 | 2048 | NA | NA | 2022 | 2037 | 2061 | 2084 |
| MIROC-ESM_r1i1p1 | 2020 | 2033 | 2068 | NA | 2020 | 2030 | 2052 | 2069 |
| MIROC-ESM-CHEM_r1i1p1 | 2022 | 2036 | 2073 | NA | 2018 | 2030 | 2050 | 2067 |
| MIROC5_r1i1p1 | 2039 | 2071 | NA | NA | 2033 | 2048 | 2072 | NA |
| MPI-ESM-LR_r1i1p1 | 2022 | 2044 | NA | NA | 2017 | 2037 | 2061 | 2081 |
| MPI-ESM-MR_r1i1p1 | 2023 | 2045 | NA | NA | 2019 | 2039 | 2060 | 2082 |
| MRI-CGCM3_r1i1p1 | 2054 | 2084 | NA | NA | 2041 | 2052 | 2076 | NA |
| NorESM1-M_r1i1p1 | 2039 | 2072 | NA | NA | 2032 | 2048 | 2072 | NA |
Source https://github.com/IPCC-WG1/Atlas/blob/main/warming-levels/CMIP5_Atlas_WarmingLevels.csv.
...
Table 8: Central year of GWLs for CMIP6 simulations under SSP2_4.5 and SSP5-8.5.
| CMIP6 model_run | 1.5_ssp245 | 2_ssp245 | 3_ssp245 | 4_ssp245 | 1.5_ssp585 | 2_ssp585 | 3_ssp585 | 4_ssp585 |
|---|---|---|---|---|---|---|---|---|
| ACCESS-CM2_r1i1p1f1 | 2028 | 2040 | 2070 | NA | 2025 | 2038 | 2055 | 2071 |
| ACCESS-ESM1-5_r1i1p1f1 | 2029 | 2045 | NA | NA | 2027 | 2039 | 2060 | 2078 |
| AWI-CM-1-1-MR_r1i1p1f1 | 2020 | 2039 | NA | NA | 2019 | 2036 | 2059 | 2079 |
| BCC-CSM2-MR_r1i1p1f1 | 2035 | 2057 | NA | NA | 2031 | 2043 | 2065 | NA |
| CAMS-CSM1-0_r2i1p1f1 | 2055 | 2088 | NA | NA | 2047 | 2064 | 2088 | NA |
| CanESM5_r1i1p1f1 | 2012 | 2023 | 2049 | 2083 | 2011 | 2022 | 2040 | 2054 |
| CESM2_r4i1p1f1 | 2028 | 2042 | 2078 | NA | 2023 | 2034 | 2055 | 2071 |
| CESM2-WACCM_r1i1p1f1 | 2024 | 2039 | 2075 | NA | 2020 | 2033 | 2053 | 2068 |
| CMCC-CM2-SR5_r1i1p1f1 | 2024 | 2038 | 2066 | NA | 2021 | 2033 | 2052 | 2069 |
| CNRM-CM6-1_r1i1p1f2 | 2030 | 2048 | 2084 | NA | 2028 | 2040 | 2058 | 2072 |
| CNRM-CM6-1-HR_r1i1p1f2 | 2019 | 2033 | 2062 | NA | 2018 | 2029 | 2051 | 2066 |
| CNRM-ESM2-1_r1i1p1f2 | 2037 | 2055 | 2088 | NA | 2032 | 2045 | 2064 | 2079 |
| EC-Earth3_r1i1p1f1 | 2022 | 2044 | 2085 | NA | 2024 | 2035 | 2057 | 2073 |
| EC-Earth3-Veg_r1i1p1f1 | 2010 | 2033 | 2067 | NA | 2011 | 2027 | 2050 | 2067 |
| EC-Earth3-Veg-LR_r1i1p1f1 | 2026 | 2049 | NA | NA | 9999 | 9999 | 9999 | 9999 |
| FGOALS-g3_r1i1p1f1 | 2030 | 2063 | NA | NA | 2027 | 2046 | 2072 | NA |
| GFDL-CM4_r1i1p1f1 | 2031 | 2050 | NA | NA | 2029 | 2041 | 2059 | 2079 |
| GFDL-ESM4_r1i1p1f1 | 2046 | 2072 | NA | NA | 2039 | 2052 | 2075 | NA |
| HadGEM3-GC31-LL_r1i1p1f3 | 2019 | 2033 | 2061 | NA | 2020 | 2030 | 2047 | 2063 |
| IITM-ESM_r1i1p1f1 | 2036 | 2061 | NA | NA | 2035 | 2048 | 2075 | NA |
| INM-CM4-8_r1i1p1f1 | 2035 | 2063 | NA | NA | 2030 | 2046 | 2069 | NA |
| INM-CM5-0_r1i1p1f1 | 2036 | 2072 | NA | NA | 2030 | 2045 | 2074 | NA |
| IPSL-CM6A-LR_r1i1p1f1 | 2018 | 2033 | 2065 | NA | 2018 | 2034 | 2050 | 2066 |
| KACE-1-0-G_r2i1p1f1 | 2010 | 2021 | 2052 | NA | 2009 | 2021 | 2042 | 2063 |
| KIOST-ESM_r1i1p1f1 | 2020 | 2039 | NA | NA | 2016 | 2037 | 2063 | NA |
| MIROC-ES2L_r1i1p1f2 | 2041 | 2063 | NA | NA | 2034 | 2047 | 2070 | NA |
| MIROC6_r1i1p1f1 | 2046 | 2073 | NA | NA | 2040 | 2053 | 2076 | NA |
| MPI-ESM1-2-HR_r1i1p1f1 | 2037 | 2063 | NA | NA | 2033 | 2049 | 2073 | NA |
| MPI-ESM1-2-LR_r1i1p1f1 | 2036 | 2057 | NA | NA | 2034 | 2048 | 2071 | NA |
| MRI-ESM2-0_r1i1p1f1 | 2030 | 2049 | NA | NA | 2026 | 2038 | 2064 | 2083 |
| NESM3_r1i1p1f1 | 2024 | 2042 | NA | NA | 2020 | 2033 | 2054 | 2072 |
| NorESM2-LM_r1i1p1f1 | 2055 | 2085 | NA | NA | 2042 | 2056 | 2077 | NA |
| NorESM2-MM_r1i1p1f1 | 2046 | 2078 | NA | NA | 2039 | 2054 | 2076 | NA |
| TaiESM1_r1i1p1f1 | 9999 | 9999 | 9999 | 9999 | 2028 | 2036 | 2052 | 2067 |
| UKESM1-0-LL_r1i1p1f2 | 2023 | 2034 | 2059 | NA | 2023 | 2031 | 2046 | 2060 |
Source https://github.com/IPCC-WG1/Atlas/blob/main/warming-levels/CMIP6_Atlas_WarmingLevels.csv.
...
The table below lists all the regional layers available and the corresponding code to use in the file naming conventions.
Regions | Region | Code |
NUTS | NUTS0 2024 | nuts_0 |
NUTS1 2024 | nuts_1 | |
NUTS2 2024 | nuts_2 | |
NUTS 3 | nuts_3 | |
Europe Zones
| EEA EU 27 | eea_eu_27 |
EEA EU 32 | eea_eu_32 | |
EEA EU 38 | eea_eu_38 | |
Transnational Regions
| Interreg VI-B Adriatic-Ionian | eea_trans_adriatic_ionian |
Interreg VI-B Alpine Space | eea_trans_alpine_space | |
Interreg VI-B Northern Periphery and Arctic | eea_trans_northern_periphery_and_arctic | |
Interreg VI-B Atlantic Area | eea_trans_atlantic_area | |
Interreg VI-B Baltic Sea Region | eea_trans_baltic_sea_region | |
Interreg VI-B Central Europe | eea_trans_central_europe | |
Interreg VI-B Danube | eea_trans_danube | |
Interreg VI-B Mediterranean (EURO MED) | eea_trans_mediterranean | |
Interreg VI-B North Sea | eea_trans_north_sea | |
Interreg VI-B North West Europe | eea_trans_north_west_europe | |
Interreg VI-B South West Europe (SUDOE) | eea_trans_south_west_europe |
References
[1] Crespi A., Terzi S., Cocuccioni S., Zebisch M., Berckmans J., Füssel H-M (2020) “Climate-related hazard indices for Europe”. European Topic Centre on Climate Change impacts, Vulnerability and Adaptation (ETC/CCA) Technical Paper 2020/1. DOI: https://doi.org/10.25424/cmcc/climate_related_hazard_indices_europe_2020
...