Alpine-wide climate indices from reanalyses and EURO-CORDEX projections for different Global Warming Levels
Authors/Creators
-
Lehner, Sebastian
(Data curator)1
-
Crespi, Alice
(Project manager)2
-
Žun, Maja
(Work package leader)3
-
Haslinger, Klaus
(Supervisor)1
- Pistotnik, Georg (Project member)1
-
Maines, Elena
(Project member)2
-
Vlahović, Živa
(Project member)4
-
Campalani, Piero
(Project member)2
-
Honzak, Luka
(Project member)4
- Bertalanič, Renato (Project member)4
- Lokošek, Neža (Project member)4
Description
This data set contains calculated and aggregated climate indices for Reanalysis and EURO-CORDEX data on Global Warming Levels (GWLs) for the Alpine Space.
Data
The reanalysis data used was CERRA (Ridal, et al. 2024) and ERA5 (Hersbach, et al. 2020) on a daily basis. CERRA was used for precipitation, temperature and wind related indices, while drought and heat-drought compound indices are based on a downscaled version of ERA5 from the ADO project (https://www.alpine-space.eu/project/ado/).
EURO-CORDEX (Jacob, et al. 2014) data is listed in Tab. 1 and includes two different Regional Climate Models that are driven by 5 to 6 different Global Climate Models. Only the scenario RCP8.5 has been used, because it contains the most Global Warming Levels out of all scenarios.
All data was reprojected to the Alpine Space projection EPSG:32632. The period 1991 to 2020 has been used as historical reference for the reanalysis data. For EURO-CORDEX data, the GWL +1°C has been used as reference.
Table 1: Models from EURO-CORDEX that have been used to calculate climate indices.
|
Regional Climate Model |
Global Climate Model |
Ensemble Member |
|
COSMO-crCLIM-v1-1 |
CNRM-CM5 |
r1i1p1 |
|
COSMO-crCLIM-v1-1 |
EC-EARTH |
r1i1p1 |
|
COSMO-crCLIM-v1-1 |
EC-EARTH |
r3i1p1 |
|
COSMO-crCLIM-v1-1 |
EC-EARTH |
r12i1p1 |
|
COSMO-crCLIM-v1-1 |
HadGEM2-ES |
r1i1p1 |
|
COSMO-crCLIM-v1-1 |
MPI-ESM-LR |
r1i1p1 |
|
COSMO-crCLIM-v1-1 |
MPI-ESM-LR |
r2i1p1 |
|
COSMO-crCLIM-v1-1 |
MPI-ESM-LR |
r3i1p1 |
|
COSMO-crCLIM-v1-1 |
NorESM1-M |
r1i1p1 |
|
RCA4 |
CNRM-CM5 |
r1i1p1 |
|
RCA4 |
EC-EARTH |
r1i1p1 |
|
RCA4 |
EC-EARTH |
r3i1p1 |
|
RCA4 |
EC-EARTH |
r12i1p1 |
|
RCA4 |
HadGEM2-ES |
r1i1p1 |
|
RCA4 |
MPI-ESM-LR |
r1i1p1 |
|
RCA4 |
MPI-ESM-LR |
r2i1p1 |
|
RCA4 |
MPI-ESM-LR |
r3i1p1 |
|
RCA4 |
IPSL-CM5A-MR |
r1i1p1 |
|
RCA4 |
NorESM1-M |
r1i1p1 |
Methods
Climate indices (see Tab. 2) were first calculated on either an annual, or seasonal basis and are then averaged over different GWLs given by Hauser et al. (2022), however the therein 20-year GWL periods were extended by 5 years in each direction, such that the used GWLs here span 30 years. All projected changes for each GWL are calculated as differences, either absolute or relative, with respect to the 30-year period correspoding to GWL 1°C. Projected changes are calculated for each EURO-CORDEX simulation and are then reported as ensemble percentiles. The following percentiles are contained: 5, 25, 50, 75, 95.
Table 2: Climate indices calculated, containing the name, abbreviation and use-case:
|
Climate index name |
Abbreviation |
Use-case |
|
Maximum 1-day precipitation |
Rx1d |
Extreme 1-day precipitation intensity |
|
Maximum 3-day precipitation |
Rx3d |
Extreme multi-day precipitation intensity |
|
Number of days with 1-day precipitation exceeding the 97th percentile |
R97pN_1d |
Extreme 1-day precipitation frequency |
|
Sum of 1-day precipitation exceeding the 97th percentile |
R97pTOT_1d |
Extreme 1-day precipitation cumulative intensity |
|
Number of days with 3-day precipitation exceeding the 97th percentile |
R97pN_3d |
Extreme multi-day precipitation frequency |
|
Sum of 3-day precipitation exceeding the 97th percentile |
R97pTOT_3d |
Extreme multi-day precipitation cumulative intensity |
|
Convective indicator orange warning |
conv_ind_orange |
Extreme convective precipitation |
|
Convective indicator red warning |
conv_ind_red |
Very extreme convective precipitation |
|
Maximum 1-day wind speed |
WSx1d |
Extreme wind speed intensity |
|
Number of days with 1-day wind speed exceeding the 97th percentile |
WS97pN_1d |
Extreme wind speed frequency |
|
Mean of maximum wind speed for days exceeding the 97th percentile |
WS97pMEAN_1d |
Wind speed on very windy days |
|
Number of days with extreme 3-day precipitation and 1-day wind speed maximum |
RWS97pN_3d |
Compound extreme precipitation and wind frequency |
|
One-month drought peak intensity |
SPEI1_int |
Peak intensity of one-month drought |
|
One-month drought frequency |
SPEI1_freq |
Frequency of one-month severe drought conditions |
|
Three-month drought peak intensity |
SPEI3_int |
Peak intensity of three-month drought |
|
Three-month drought frequency |
SPEI3_freq |
Frequency of three-month severe drought conditions |
|
Heatwave days |
HWD |
Heatwave frequency |
|
Heatwave magnitude |
HWM |
Heatwave intensity |
|
Magnitude of compound one-month drought and heatwave events |
CDHW_1 |
Compound heatwave and one-month drought magnitude |
|
Magnitude of compound three-month drought and heatwave events |
CDHW_3 |
Compound heatwave and three-month drought magnitude |
Visualization and more detailed information
The data can be viewed interactively via a WebGIS platform, which also contains more information about data processing and index definitions: https://cct.eurac.edu/x-risk-cc
Acknowledgements
The research leading to these results has received funding from Interreg Alpine Space Program 2021-27 under the project number ASP0100101, “How to adapt to changing weather eXtremes and associated compound and cascading RISKs in the context of Climate Change” (X-RISK-CC).
References
Hauser, M., Engelbrecht, F., & Fischer, E. M. (2022). Transient global warming levels for CMIP5 and CMIP6 (v0.3.0). Zenodo. https://doi.org/10.5281/zenodo.7390473
Hersbach, H., Bell, B., Berrisford, P., et al. (2020). The ERA5 global reanalysis. Q. J. R. Meteorol. Soc., 146, 1999–2049. https://doi.org/10.1002/qj.3803
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O.B., Bouwer, L.M., Braun, A., Colette, A., Déqué, M., Georgievski, G. and Georgopoulou, E., (2014). EURO-CORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, 14, 563-578. https://doi.org/10.1007/s10113-013-0499-2
Ridal, M., Bazile, E., Le Moigne, P., Randriamampianina, R., Schimanke, S., Andrae, U., et al. (2024). CERRA, the Copernicus European Regional Reanalysis system, Quarterly Journal of the Royal Meteorological Society, 150(763), 3385–3411. https://doi.org/10.1002/qj.4764
Changelog
Version 1.0.1: The convective indicator files were reuploaded with rescaled values and updated units. In this version the values have been divided by 100 and are hence provided as "Expected number of events per year" instead of cumulative [%] values per year.
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Additional details
Funding
- European Commission
- Interreg Alpine Space Program 2021-27 ASP0100101
Dates
- Created
-
2025-01-31Creation/Publication of data