Versions Compared

Old Version 1

changes.mady.by.user Michela Giusti

Saved on

compared with

New Version 2

changes.mady.by.user Michela Giusti

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

This dataset was produced on behalf of the Copernicus Climate Change Service. This document describes version 2.0, which represents the first public release of the datasets. Regular updates will follow subsequent releases of the ECDE visualisation application.

Scope of documentation

This documentation provides a comprehensive overview of the aggregated climate indicators for Europe from 1940 to 2100, including their requirements, definitions, structure, and methodology. It first presents the requirements for the climate hazard indicators (2.1. Requirements), followed by a description of the aggregated dataset (2.2. Data Description). The definitions of the ECDE climate indicators are detailed in (2.3. Climate indicators definition), and the specific derived statistics derived from these indicators are outlined in (2.4. Derived statistics). Finally, the methodology and input datasets used for product generation are described in (2.5. Method).

...

This is the first release of the dataset, labelled as version v2.0 to align with version v2.0 of the ECDE indicators. Future updates will align with subsequent releases. 

Product description

Requirements 

...

Table 1: List of key specifications of the ECDE climate hazard derived statistics.

Data type

Regional aggregation

Projection

-

Horizontal coverage

Europe

Horizontal resolution

Regional Aggregation (NUTS 0-2)

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 lists and defines the climate indicators included in the aggregated dataset.

Table 2: Definition of the ECDE indicators.

Main Variables

Variable

Units

Description

Heat and cold

Mean temperature

°C

Mean

Air temperature

of the air

at 2m

temperature

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.

The data are available on monthly, seasonal, or annual time spans.

Growing degree days

°C day

-1The cumulative sum of

Cumulative daily degrees above a 5 °C daily mean

temperature of 5°C

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.

The data are available on monthly, seasonal, or annual time spans.

Heating degree days

°C day

-1The cumulative sum of

Cumulative daily degrees below a 15.5 °C daily mean

temperature of 15.5°C.

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.

The data are available on monthly, seasonal, or annual time spans.

Cooling degree days

°C day

-1The cumulative sum of

Cumulative daily degrees above a 22 °C daily mean

temperature of 22°C

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.

The data are available on monthly, seasonal, or annual time spans.

Tropical nights

day

The count

Number of days with daily minimum 2m air temperature above

20°C

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

. The data are available on monthly, seasonal, or annual time spans

.

Hot daysday
The count

Number of days with daily maximum 2m air temperature above

a 30°C threshold (also 35°C or 40°C

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

The

Annual count of climatological

hot

heatwave days

in a year

. A climatological

heat wave

heatwave is a period of at least three consecutive days exceeding the 99th percentile of

the

May–September daily maximum

temperatures of the May to September season during a reference period (

2m air temperatures 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 annual time span only.

High UTCI days

day

The count

Number of days

when

with Universal Thermal Climate Index (UTCI)

remains

above

32°C

32 °C. UTCI is an equivalent

to

temperature (°C)

corresponding to a measure of the

representing human physiological response to meteorological conditions

that also takes into consideration the

, accounting for clothing adaptation

of the population in response

to outdoor temperature. It is

based on

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

The count

Number of days with daily minimum 2m air temperature below

0°C

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

. The data are available on monthly, seasonal, or annual time spans

.

Maximum

Daily maximum temperature

°C

The maximum value of

Highest daily maximum 2m air temperature

of a period

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

. The data are available on monthly, seasonal, or annual time spans

.

Minimum

Daily minimum temperature

°C

The minimum value of

Lowest daily minimum 2m air temperature

of a period

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.

The data are available on monthly, seasonal, or annual time spans.

Growing season start

1

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

First day in a year with 5 consecutive days with a mean daily temperature above 278.15 K (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

with

when the daily mean 2m air temperature consistently falls below a specific threshold of 5 °C over 5 consecutive days

with a mean daily temperature below 278

.

15 K (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 length

day

Number of days between the first day in a year with 5 consecutive days with a mean daily temperature above 278.15 K (5°C) and the subsequent first day of the same year with 5 consecutive days with a mean daily temperature below 278.15 K (5°C).

.

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

-days

-

1Maximum five

day precipitation

totals over a

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.

The data are available on monthly, seasonal, or annual time spans.

Extreme precipitation total 

mm

The total sum

Sum of daily precipitation

values in a year which exceed the 99th percentile of the reference period (

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

The count

Number of days in a month, season, or year with precipitation above

the extreme precipitation threshold defined as

the 95th percentile of

total

daily precipitation

of rainy days

over

a reference period (

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.

Flood recurrence 

m3 s-1

Ensemble mean and distribution of flood recurrence. The River Flood index is defined as the 50-year flood recurrence. Other values from several recurrence periods (10, 5 and 2 years) are also shown as complementary information

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

The

Yearly and monthly mean

value

ratio of

the ratio between

actual evapotranspiration

and

to precipitation over a 30-year period.

Here actual

Actual evapotranspiration is

the

modelled

evapotranspiration computed

using only

with

available water. The period 1971–2000 provides the baseline data and is used for anomaly calculations.

The data are available on monthly or annual time spans.

Consecutive dry days

day

The longest

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

. The data are available on monthly, seasonal, or annual time spans

.

Duration of meteorological droughts

month

The count

Number of months in a year with anomalously low precipitation

conditions

, based on the 3-month Standardised Precipitation Index (SPI-3) relative to

a

the 1991–2020 reference period

, here 1991-2020

.

 

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

a reference period, here

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 data are available annually only

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

Soil moisture is the water stored in the soil and is affected by precipitation, temperature, soil characteristics, and more. The mean soil moisture

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

values

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

The Fire Weather Index (FWI) is a

A meteorologically based index used worldwide to estimate fire danger.

It is developed

Developed by the Canadian Forestry Service

to estimate forest fire ignition and spread conditions based on several weather variables (temperature

, it combines 2m air temperature, precipitation, relative humidity, and wind speed

). Two

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

The count

Number of days

in a period

with a Fire Weather Index (FWI)

value greater than 30 (Number of days) based upon

above 30 in a month, season, or year, per the European Forest Fire Information System (EFFIS) classification.

 Two

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.

 

Wind

Mean wind speed

m s-1

Mean speed of the 10m wind

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.

The data are available on monthly, seasonal, or annual time spans.

Extreme wind speed days 

day

The count

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

a reference period (

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

.

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

that the area has

of favourable environmental conditions for Aedes albopictus presence

with

from 0

not suitable

unsuitable (no favourable conditions)

and

to 100

totally

(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.

Derived statistics

The derived statistics refer to the aggregated and multi-model product that can be dowloaded through the catalogue entry. Instead of downloading row time series of an indicator for a single model, the derived statistics provide multi-model climatologies, anomalies, uncertainties etc. The following sections present the categories in which the products have been grouped and the definition of every single derived statistic.

...

Figure 3: Example plot showing time series of the median and likely range of temperature as an envelope based on quantile values.

Climatology

The products in the climatology category contain data expressed as monthly climatologies. These data can be represented in a plot showing 30-year averages and standard deviations of observed and projected monthly values for three time horizons. Likely values (66% probability of occurrence) are represented as an uncertainty envelope derived from an ensemble of climate models.

Figure 4: Example plot showing averaged monthly temperature values (climatologies) over the 2011-240, 2041-2070, and 2071–2100 period.

...

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.
For reanalysis the average is provided for two reference periods (ref_period): 1981 – 2010 and 1991 – 2020.

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.
The smoothing corresponds to a 30-year moving average (e.g. year 1996 is the average of 1981 to 2010) to focus on the 30 year trend.

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
scenario

Absolute change

ref_period
avg_period
ref_period
avg_period
scenario

Relative change

ref_period
avg_period
ref_period
avg_period
scenario

Uncertainty quantiles

avg_period
avg_period
scenario
quantile

 Absolute change quantiles

ref_period
avg_period

ref_period
avg_period
scenario
quantile

Relative change quantiles

ref_period
avg_period

ref_period
avg_period
scenario
quantile

GWL

-

gwl

GWL changes

-

gwl
ref_period

GWL percent changes

-

gwl
ref_period

Anomaly

ref_period
time

-

Anomaly quantiles

-

ref_period
scenario
quantile
time

Ensemble quantiles

-

scenario
quantile
time

Climatology

clim_period
stat
month
clim_period
stat
quantile
month

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. 

Calculation

Computing hazard products primarily involves temporal aggregations, simple calculations and statistics (e.g., anomalies, relative changes, ensemble quantiles). The most complex component concerns the estimation of GWLs. The methodology and time frames used to compute these levels are described in Appendix 1.

...

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

Coastal

Relative sea level rise

First release

Extreme sea level 

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, wind, and coastal impacts, 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.

...

The tables focus on RCP4.5/SSP2-4.5 and RCP8.5/SSP5-8.5 scenarios, as these are used in the underlying climate indicators and derived statistics datasets. The +4°C warming level appears exclusively in the RCP8.5/SSP5-8.5 scenario because this represents the only emission pathway that reaches this threshold—an approach consistent with the "Simple" version of the IPCC Atlas. The "Extended" Atlas provides GWLs for each SSP, but not all warming levels are available for every scenario (e.g., SSP1-2.6 attains only +1.5 °C, SSP2-4.5 reaches +1.5 °C and +2.0 °C, SSP3-7.0 goes up to +3.0 °C, and SSP5-8.5 up to +4 °C).

...

Table 6: List of CMIP5 driving Earth System Models of the EURO-CORDEX experiment used by each project and corresponding dataset. 


SIS Energy

SIS Op. Water Service

SIS Tourism (FWI)

SIS Tourism (Snow)

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_run1.5_rcp452_rcp453_rcp454_rcp451.5_rcp852_rcp853_rcp854_rcp85
ACCESS1-0_r1i1p120332053NANA2028204120622081
ACCESS1-3_r1i1p120392056NANA2031204220622082
bcc-csm1-1_r1i1p120212043NANA2019203620592083
bcc-csm1-1-m_r1i1p120112035NANA2010202820592085
BNU-ESM_r1i1p1NANANANANANANANA
CanESM2_r1i1p1201720312075NA2013202620492068
CCSM4_r1i1p120172039NANA2014203020572078
CESM1-BGC_r1i1p120182044NANA2017203320592080
CMCC-CM_r1i1p120342050NANA2029204120612078
CMCC-CMS_r1i1p120372055NANA2029204120612077
CNRM-CM5_r1i1p120362057NANA2030204520672087
CSIRO-Mk3-6-0_r1i1p120352048NANA2034204420652082
EC-EARTH_r12i1p120222044NANA2018203420602082
EC-EARTH_r3i1p120222044NANA2020203820612081
GFDL-CM3_r1i1p199999999999999992022203420542070
GFDL-ESM2G_r1i1p12050NANANA203720542080NA
GFDL-ESM2M_r1i1p12046NANANA203620512082NA
HadGEM2-CC_r1i1p120362052NANA2027203920562072
HadGEM2-ES_r1i1p1202820432078NA2023203520542071
inmcm4_r1i1p12060NANANA204420572083NA
IPSL-CM5A-LR_r1i1p1201320302069NA2009202520472065
IPSL-CM5A-MR_r1i1p1201620332077NA2015203020502066
IPSL-CM5B-LR_r1i1p120262048NANA2022203720612084
MIROC-ESM_r1i1p1202020332068NA2020203020522069
MIROC-ESM-CHEM_r1i1p1202220362073NA2018203020502067
MIROC5_r1i1p120392071NANA203320482072NA
MPI-ESM-LR_r1i1p120222044NANA2017203720612081
MPI-ESM-MR_r1i1p120232045NANA2019203920602082
MRI-CGCM3_r1i1p120542084NANA204120522076NA
NorESM1-M_r1i1p120392072NANA203220482072NA

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_run1.5_ssp2452_ssp2453_ssp2454_ssp2451.5_ssp5852_ssp5853_ssp5854_ssp585
ACCESS-CM2_r1i1p1f1202820402070NA2025203820552071
ACCESS-ESM1-5_r1i1p1f120292045NANA2027203920602078
AWI-CM-1-1-MR_r1i1p1f120202039NANA2019203620592079
BCC-CSM2-MR_r1i1p1f120352057NANA203120432065NA
CAMS-CSM1-0_r2i1p1f120552088NANA204720642088NA
CanESM5_r1i1p1f120122023204920832011202220402054
CESM2_r4i1p1f1202820422078NA2023203420552071
CESM2-WACCM_r1i1p1f1202420392075NA2020203320532068
CMCC-CM2-SR5_r1i1p1f1202420382066NA2021203320522069
CNRM-CM6-1_r1i1p1f2203020482084NA2028204020582072
CNRM-CM6-1-HR_r1i1p1f2201920332062NA2018202920512066
CNRM-ESM2-1_r1i1p1f2203720552088NA2032204520642079
EC-Earth3_r1i1p1f1202220442085NA2024203520572073
EC-Earth3-Veg_r1i1p1f1201020332067NA2011202720502067
EC-Earth3-Veg-LR_r1i1p1f120262049NANA9999999999999999
FGOALS-g3_r1i1p1f120302063NANA202720462072NA
GFDL-CM4_r1i1p1f120312050NANA2029204120592079
GFDL-ESM4_r1i1p1f120462072NANA203920522075NA
HadGEM3-GC31-LL_r1i1p1f3201920332061NA2020203020472063
IITM-ESM_r1i1p1f120362061NANA203520482075NA
INM-CM4-8_r1i1p1f120352063NANA203020462069NA
INM-CM5-0_r1i1p1f120362072NANA203020452074NA
IPSL-CM6A-LR_r1i1p1f1201820332065NA2018203420502066
KACE-1-0-G_r2i1p1f1201020212052NA2009202120422063
KIOST-ESM_r1i1p1f120202039NANA201620372063NA
MIROC-ES2L_r1i1p1f220412063NANA203420472070NA
MIROC6_r1i1p1f120462073NANA204020532076NA
MPI-ESM1-2-HR_r1i1p1f120372063NANA203320492073NA
MPI-ESM1-2-LR_r1i1p1f120362057NANA203420482071NA
MRI-ESM2-0_r1i1p1f120302049NANA2026203820642083
NESM3_r1i1p1f120242042NANA2020203320542072
NorESM2-LM_r1i1p1f120552085NANA204220562077NA
NorESM2-MM_r1i1p1f120462078NANA203920542076NA
TaiESM1_r1i1p1f199999999999999992028203620522067
UKESM1-0-LL_r1i1p1f2202320342059NA2023203120462060

Source https://github.com/IPCC-WG1/Atlas/blob/main/warming-levels/CMIP6_Atlas_WarmingLevels.csv.

Appendix 2: Regional layers

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

...