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Introduction

Global Climate Models (GCM) can provide reliable climate information on global, continental and large regional scales covering what could be a vastly differing landscape (from very mountainous to flat coastal plains for example) with greatly varying potential for floods, droughts or other extreme events. Horizontal resolution limits the possibility to address smaller scale ranging from regional to local. Regional Climate Models (RCM) applied with higher spatial resolution over a limited area and driven by GCMs can provide more appropriate information on such smaller scales supporting more detailed impact and adaptation assessment and planning. Therefore Regional Climate Models (RCMs) have an important role to play by providing projections with much greater detail and more accurate representation of localized extreme events.

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The effort done by Copernicus to consolidate a World-wide CORDEX dataset is also contributing to the IPCC-AR6 WGI activities, providing a curated dataset to be assessed together with global climate information from CMIP experiments, in particular in the the Interactive Atlas (IPCC-IA, https://interactive-atlas.ipcc.ch/), a new product of the IPCC allowing exploration of observed and projected climate data to complement the assessment of relevant datasets undertaken in the WGI chapters of IPCC. The C3S CORDEX dataset as a contribution to the IPCC .Atlas is described in detail in Diez-Sierra et al., 2022. The data underpinning the IPCC-IA is also available in the CDS at https://cds.climate.coperni us.eu/cdsapp#!/dataset/projections-climate-atlas. 

In addition, CORDEX data for CDS includes Persistent IDentifiers (PIDIn addition, CORDEX data for CDS includes Persistent IDentifiers (PID) in their metadata which allows CDS users to report any error during the scientific analysis. The error will be at least documented on the ESGF Errata Service (http://errata.es-doc.org),  but also planned to be documented in the CDS. The CDS aims to publish only the latest versions of the datasets.

Domains

We are aiming at publishing various CORDEX domains for the entire World. The CDS-CORDEX subset at the moment consists of the Europe (EURO), Mediterranean (MED), North America (NAM), Arctic (ARC), Africa (AFR) and South America (SAM) CORDEX domains. More details of the entire list of CORDEX domains can be publish simulations for all CORDEX domains worldwide and consequently all 14 domains are available in the CDS. The dataset was aligned with the CORDEX/RCM data underpinning the AR6 report of IPCC.  More details of the entire list of CORDEX domains can be found at https://cordex.org/domains/; additionally more details for the EURO-CORDEX and NA-CORDEX activities are available at https://www.euro-cordex.net/ and https://na-cordex.org/, respectively.. 

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 As a summary, the available domains are:

*The MENA domain is sometimes referred to with the acronym MNA in the names of files retrieved from the CDS, as served from ESGF.

Experiments

The CDS-CORDEX subset consists of the following CORDEX experiments partly derived from the CMIP5 ones:

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• scenario experiments RCP2.6, RCP4.5, RCP8.5: ensemble of CORDEX climate projection experiments driven by boundary conditions from GCMs using RCP (Representative Concentration Pathways) forcing scenarios. The scenarios used here are RCP 2.6, 4.5 and 8.5, they provide different pathways of the future climate forcing. Further details on the emission scenarios used for CMIP5 can be found in Moss et al., 2010.
  

Driving Global Climate Models and Regional Climate Models

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The driving GCM and RCM models included in the CDS-CORDEX subsets for the different domains available are detailed in the tables below. Note that the ensembles for different domains are formed by different GCM and RCM combinations from the main CMIP5 and CORDEX archives, respectively: these include 8 GCMs and 13 RCMs for EURO-CORDEX, 8 GCMs and 5 RCMs for Med-CORDEX, 8 GCMs and 8 RCMs for North-America CORDEX, and 5 GCMs and 6 RCMs for the Arctic. Please note that a small number of models were not included as those data have a research-only restriction on their use, while the data presented in the CDS are released without any restriction. 

In the tables below, please see the GCM-RCM combinations for each published domains.

AFR-CORDEX:

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ANT-CORDEX:

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ARC-CORDEX:

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AUS-CORDEX:

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CAM-CORDEX:

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CAS-CORDEX:

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EAS-CORDEX:

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EURO-CORDEX:

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Med-CORDEX:

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MENA-CORDEX:

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NAM-CORDEX:

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See detailed information about the RCMs used for CORDEX at https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_AnnexII.pdf (Tables AII.1, AII.2, AII.3 and AII.4). Additionally, the dataset, including key model details, is described in Diez-Sierra et al., 2022 .

In the tables below, please see the GCM-RCM and experiment combinations available for each published domain.

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The 13 Regional Climate Models that ran simulations over the European domain will be documented through the Earth-System Documentation (ES-DOC) which provides a standardised and easy way to document climate models.

Ensembles

The boundary conditions used to run a RCM are also identified by the model member if the CMIP5 simulation used. Each modelling centre typically run the same experiment using the same GCM several times to confirm the robustness of results and inform sensitivity studies through the generation of statistical information. A model and its collection of runs is referred to as an ensemble. Within these ensembles, three different categories of sensitivity studies are done, and the resulting individual model runs are labelled by three integers indexing the experiments in each category. 

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The table below lists the variables provided (the bold face items are available for all domains, the rest is only for Europe) at 3-hourly, 6-hourly, daily, monthly and seasonal temporal scale (for non-European domains only daily data are available). Note that orography

Note: on the data update of the 27th of May, 2021 for some non-European simulations only the six most demanded variables are published, which are 2m specific humidity, mean precipitation flux, 10m wind speed, 2m temperature, minimum and maximum temperature in the last 24 hours. The additional variables (indicated in bold face below) will be added in the next batch (anticipated latest in September, 2021).

Data

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format

The CDS subset of CORDEX data are provided as NetCDF files. NetCDF (Network Common Data Form) is a file format that is freely available and commonly used in the climate modelling community. See the more details: What are NetCDF files and how can I read them

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The metadata provided in NetCDF files adhere to the Climate and Forecast (CF) conventions. The rules within the CF-conventions ensure consistency across data files, for example ensuring that the naming of variables is consistent and that the use of variable units is consistent.

File naming conventions

When you download a CORDEX file from the CDS it will have a naming convention that is as follows:

<variable>_<domain>_<driving-model>_<experiment>_<ensemble_member>_<rcm-model>_<rcm-run>_<time-frequency>_<temporal-range>.nc

Where

• <variable> is a short variable name, e.g. “tas” for ”temperature at the surface”
• <driving-model> is the name of the model that produced the boundary conditions
• <experiment> is the name of the experiment used to extract the boundary conditions
• <ensemble-member> is the ensemble identifier in the form “r<X>i<Y>p<Z>”, X, Y and Z are integers
• <rcm-model> is the name of the model that produced the data
• <rcm-run> is the version run of the model in the form of "vX" where X is integer
• <time-frequency> is the time series frequency (e.g., monthly, daily, seasonal) 
• the <temporal-range> is in the form YYYYMM[DDHH]-YYYY[MMDDHH], where Y is year, M is the month, D is day and H is hour. Note that day and hour are optional (indicated by the square brackets) and are only used if needed by the frequency of the data. For example daily data from the 1st of January 1980 to the 31st of December 2010 would be written 19800101-20101231.

Quality control of the CDS-CORDEX subset 

The CDS subset of the CORDEX data have been through a set of quality control checks before being made available through the CDS. The objective of the quality control process is to ensure that all files in the CDS meet a minimum standard. Data files were required to pass all stages of the quality control process before being made available through the CDS. Data files that fail the quality control process are excluded from the CDS-CORDEX subset or if possible the error is corrected and a note made in the history attribute of the file. The quality control of the CDS-CORDEX subset checks for metadata errors or inconsistencies against the Climate and Forecast (CF) Conventions and a set of CORDEX specific file naming and file global metadata conventions.

Various software tools have been used to check the metadata:

• The Quality Assurance compliance checking tool from DKRZ is used to check that: 
• the file name adheres to the CORDEX file naming convention, 
• the global attributes of the NetCDF file are consistent with filename,
• there are no omissions of required CORDEX metadata.
• The CF-Checker Climate and Forecast (CF) conventions checker (included in the QA-DKRZ) ensures that any metadata that is provided is consistent with the CF conventions. 

The figure below shows a scheme that classifies the tests performed by the QA-DKRZ tool in twelve categories (in green) showing the specific tests/checks in each case.

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• When possible (i.e., optional),  the Time Axis checker developed by the IPSL is used to check the temporal dimension of the data:
• for individual files the time dimension of the data is checked to ensure it is valid and is consistent with the temporal information in the filename, 
• where more than one file is required to generate a time-series of data, the files have been checked to ensure there are no temporal gaps or overlaps between the files.

The data within the files were not individually checked, therefore it is important to note that passing of these quality control tests should not be confused with validity: for example, it will be possible for a file to be fully CF compliant and have fully compliant metadata but contain gross errors in the data that have not been revealed.

Known issues

All known issues about CORDEX data are documented through the ES-DOC Errata Service : https://errata.es-doc.org/. The Errata Service also includes a command-line interface and an API to request the issue database for a specific dataset or file.

In addition:

• Please have a look on the Errata Service to be warned about deprecated CORDEX runs that will be retracted in the future.
• Please not that not all combinations of models and domains exists. This feature is due to the different CORDEX initiatives/consortiums that do not involved the same data producers using the same RCMs.
• Please note that not all the combinations of models and variables exist. This feature is inherited from the ESGF system, where the main target is to publish as much as possible data and even publish incomplete datasets, which might be of use. This allows to have more data available with the price that not everything is fully complete. 

EURO-CORDEX background documents and user guides

There is a very useful User Guide prepared by the EURO-CORDEX community which is providing guidance how to use EURO-CORDEX climate projection data. Please note that the data download part of this document at this stage refers only to access the data from the ESGF directly. Certainly the data can be also downloaded from the CDS and this information will be soon provided in that document. This EURO-CORDEX User Guide is available at https://www.euro-cordex.net/imperia/md/content/csc/cordex/guidance_for_euro-cordex_climate_projections_data_use__2021-02_1_.pdf

The spatial overlaps of the different CORDEX domains provides an opportunity for building grand ensembles by pulling together all the existing simulations from the different domains. Although this could in principle create some heterogeneity and/or duplication, there are recent studies that use and support this option (https://doi.org/10.1175/JCLI-D-19-0084.1), although further research is still needed to assess the resulting grand ensembles (see for instance https://doi.org/10.1029/2019GL086799).

The documents below were provided by the data supplier as background information on the creation of the EURO-CORDEX data stored in the Climate Data Store (CDS) for the benefit of the CORDEX data users.

• Experimental design for the GCM/RCM Matrix (29/06/2018)

This report documents how the new EURO-CORDEX experiment is designed in terms of which GCM-RCM-RCP combinations to run in the project. This was produced quite some time ago, therefore the presented information is not fully up-to-date, but nevertheless provides a fairly good idea about the concept for designing new experiments. 

• Documentation for the use of pattern scaling with particular focus on Europe (25/04/2019)

This report documents results from the 34 EURO-CORDEX RCP8.5 simulations. For a number of European subregions we present patterns describing the regional climate change in relation to the change in global mean temperature. These patterns are derived as the linear fit between regional climate change and change in global mean temperature. This is a commonly used method and can be seen as the standard definition of pattern scaling used in the scientific literature. For the calculation of these patterns the climate change signal was derived for three different time windows (2011-2040, 2041-2070 and 2071-2100) w.r.t. the control climate (1971-2000)

• Decide on experimental setup for internal variability (28/02/2018)

Internal variability is an intrinsic character of the climate system and it is also present in climate models. The design to run new RCM experiments took into account the intention that the internal variability can be studied. This report present some early investigations on these aspects for the EURO-CORDEX domain. 

• Synthesis report (28/02/2020)

In this report we review the state of the EURO-CORDEX ensemble as valid at the beginning of 2020. The report indicates climate change findings what can be deduced with the help of the larger RCM ensemble available. Regular updates of such reports are planned and the document will be updated here.

• Proposed method to assess the usability of the RCP-GCM-RCM modelling setup and description of the first results

C3S is aiming to build a EURO-CORDEX ensemble which is as complete as possible. By doing this, C3S will fill some of the missing elements of the EURO-CORDEX GCM-RCM-RCP uncertainty matrix. As we will have more simulations available (and these being complete sub-matrices, for instance), we are in a better position to assess how the full matrix can be reproduced when based on fewer available model simulations. In addition, we can determine how the missing model elements can be built. This unique study gives valuable insights into the optimal design of such ensemble systems in the future.

References

of variable units is consistent.

File naming conventions

When you download a CORDEX file from the CDS it will have a naming convention that is as follows:

<variable>_<domain>_<driving-model>_<experiment>_<ensemble_member>_<rcm-model>_<rcm-run>_<time-frequency>_<temporal-range>.nc

Where

• <variable> is a short variable name, e.g. “tas” for ”temperature at the surface”
• <driving-model> is the name of the model that produced the boundary conditions
• <experiment> is the name of the experiment used to extract the boundary conditions
• <ensemble-member> is the ensemble identifier in the form “r<X>i<Y>p<Z>”, X, Y and Z are integers
• <rcm-model> is the name of the model that produced the data
• <rcm-run> is the version run of the model in the form of "vX" where X is integer
• <time-frequency> is the time series frequency (e.g., monthly, daily, seasonal) 
• the <temporal-range> is in the form YYYYMM[DDHH]-YYYY[MMDDHH], where Y is year, M is the month, D is day and H is hour. Note that day and hour are optional (indicated by the square brackets) and are only used if needed by the frequency of the data. For example daily data from the 1st of January 1980 to the 31st of December 2010 would be written 19800101-20101231.

Quality control of the CDS-CORDEX subset 

The CDS subset of the CORDEX data have been through a set of quality control checks before being made available through the CDS. The objective of the quality control process is to ensure that all files in the CDS meet a minimum standard. Data files were required to pass all stages of the quality control process before being made available through the CDS. Data files that fail the quality control process are excluded from the CDS-CORDEX subset or if possible the error is corrected and a note made in the history attribute of the file. The quality control of the CDS-CORDEX subset checks for metadata errors or inconsistencies against the Climate and Forecast (CF) Conventions and a set of CORDEX specific file naming and file global metadata conventions.

Various software tools have been used to check the metadata:

• The Quality Assurance compliance checking tool from DKRZ is used to check that: 
• the file name adheres to the CORDEX file naming convention, 
• the global attributes of the NetCDF file are consistent with filename,
• there are no omissions of required CORDEX metadata.
• The CF-Checker Climate and Forecast (CF) conventions checker (included in the QA-DKRZ) ensures that any metadata that is provided is consistent with the CF conventions. 

The figure below shows a scheme that classifies the tests performed by the QA-DKRZ tool in twelve categories (in green) showing the specific tests/checks in each case.

Image Added

• When possible (i.e., optional),  the Time Axis checker developed by the IPSL is used to check the temporal dimension of the data:
• for individual files the time dimension of the data is checked to ensure it is valid and is consistent with the temporal information in the filename, 
• where more than one file is required to generate a time-series of data, the files have been checked to ensure there are no temporal gaps or overlaps between the files.

The data within the files were not individually checked, therefore it is important to note that passing of these quality control tests should not be confused with validity: for example, it will be possible for a file to be fully CF compliant and have fully compliant metadata but contain gross errors in the data that have not been revealed.

Citation and PID information

The users can decide on what level they want to refer to the CORDEX datasets. 

The highest level is the one provided by the CDS with the use of the following DOI (Digital Object Identifier): 10.24381/cds.bc91edc3 (available also at the right-hand-side of the entry). The users can refer to any data with this DOI, which are available in the CORDEX catalogue entry in the CDS.

Citations might be manually found by using the WDCC user interface at https://www.wdc-climate.de/, however it is not ensured that this information is up-to-date and relevant for the CORDEX datasets published in the CDS.

The CORDEX datasets are also labelled by the so called Persistent Identifiers (PIDs). PIDs are assigned to each version of every file and dataset. These are unique identifiers of the data and they are available in the header of the netcdf datafiles. The PIDs are also provided on dataset and file levels (please note that these files are csv files, which can be looked at after downloading them).

Known issues

All known issues about CORDEX data are documented through the ES-DOC Errata Service: https://errata.es-doc.org/. The Errata Service also includes a command-line interface and an API to request the issue database for a specific dataset or file.

Please note that we have updated the catalogue entry on 14/12/2022 and we have removed some old, obsolete datasets and replaced them by their latest versions. This concerns the following models and simulations: 

• EUR-11 domain:
  • GERICS/ICHEC-EC-EARTH/rcp45/REMO2015
  • DMI/ICHEC-EC-EARTH/historical/DMI-HIRHAM5
  • DMI/ICHEC-EC-EARTH/rcp26/r3i1p1/DMI-HIRHAM5 
  • DMI/ICHEC-EC-EARTH/rcp45/DMI-HIRHAM5
  • DMI/ICHEC-EC-EARTH/rcp85/DMI-HIRHAM5

  • DMI/MOHC-HadGEM2-ES/historical/DMI-HIRHAM5

  • DMI/MOHC-HadGEM2-ES/rcp85/DMI-HIRHAM5

  • DMI/NCC-NorESM1-M/historical/DMI-HIRHAM5

  • DMI/NCC-NorESM1-M/rcp45/DMI-HIRHAM5

  • DMI/NCC-NorESM1-M/rcp85/DMI-HIRHAM5

• AFR-44 domain:
  • AFR-44/DMI/ECMWF-ERAINT/evaluation/DMI-HIRHAM5
• MED-44 domain:
  • ICTP/ECMWF-ERAINT/evaluation/ICTP-RegCM4-3
  • ICTP/MOHC-HadGEM2-ES/historical/ICTP-RegCM4-3

In addition:

• Please have a look on the Errata Service to be warned about deprecated CORDEX runs that will be retracted in the future.
• Please note that not all combinations of models and domains exists. This feature is due to the different CORDEX initiatives/consortiums that do not involve the same data producers using the same RCMs.
• Please note that not all the combinations of models and variables exist. This feature is inherited from the ESGF system, where the main target is to publish as much as possible data and even publish incomplete datasets, which might be of use. This allows to have more data available with the price that not everything is fully complete. 
• There is a metadata inconsistency issue for the CCCMA_CANESM2/CCCMA_CANRCM4 model for the NAM-22 domain. The geospatial metadata available in the file is incorrect, which results in a shift of the data values with respect to the continent contours while plotting. A new errata note was created, see at https://errata.ipsl.fr/static/view.html?uid=6493a0cc-f2ab-130b-95d2-6aa2a36dd2cf and simultaneously the problem was reported back to the data producers.

Some additional minor points which are useful to note:

• For some GCM-RCM combinations, due to the nature of the model configuration, the data surrounding the RCM domain is still included by the files served from ESGF (which would mean that even a global domain might be provided). This will be apparent from the latitude and longitude coverage of the file obtained, and the high resolution domain needs to be extracted (for example LMDZ4NEMOMED8). 

Background documents and user guides

There is a very useful User Guide prepared by the EURO-CORDEX community which is providing guidance how to use EURO-CORDEX climate projection data. This EURO-CORDEX User Guide is available at  https://www.euro-cordex.net/imperia/md/content/csc/cordex/guidance_for_euro-cordex_climate_projections_data_use__2021-02_1_.pdf. 

The spatial overlaps of the different CORDEX domains provides an opportunity for building grand ensembles by pulling together all the existing simulations from the different domains. Although this could in principle create some heterogeneity and/or duplication, there are recent studies that use and support this option (https://doi.org/10.1175/JCLI-D-19-0084.1 ), though further research is still needed to assess the resulting grand ensembles (see for instance  https://doi.org/10.1029/2019GL086799 ). 

The documents below were provided by the data supplier as background information on the creation of the EURO-CORDEX data stored in the Climate Data Store (CDS) for the benefit of the CORDEX data users.

1. Description and user guide of the worldwide CORDEX C3S dataset assessing potential conflicts due to overlaps

    This document provides some guidelines how to use worldwide CORDEX data in overlapping regions.

    
2. Experimental design for the GCM/RCM Matrix (29/06/2018)

   This report documents how the new EURO-CORDEX experiment is designed in terms of which GCM-RCM-RCP combinations to run in the project. This was produced quite some time ago, therefore the presented information is not fully up-to-date, but nevertheless provides a fairly good idea about the concept for designing new experiments.
   

   
   

3. Documentation for the use of pattern scaling with particular focus on Europe (25/04/2019)

   This report documents results from the 34 EURO-CORDEX RCP8.5 simulations. For a number of European subregions we present patterns describing the regional climate change in relation to the change in global mean temperature. These patterns are derived as the linear fit between regional climate change and change in global mean temperature. This is a commonly used method and can be seen as the standard definition of pattern scaling used in the scientific literature. For the calculation of these patterns the climate change signal was derived for three different time windows (2011-2040, 2041-2070 and 2071-2100) w.r.t. the control climate (1971-2000)

   
   

4. Decide on experimental setup for internal variability (28/02/2018)

   Internal variability is an intrinsic character of the climate system and it is also present in climate models. The design to run new RCM experiments took into account the intention that the internal variability can be studied. This report present some early investigations on these aspects for the EURO-CORDEX domain. 
   

   
   

5. Synthesis report (15/10/2021)

   In this report we review the  EURO-CORDEX ensemble, which now contains altogether around 130 members (from which around half of them was prepared by the support of C3S). The report provides information about model biases and climate change trends what can be deduced with the help of the this particularly large RCM ensemble .
   

   
   

6. Proposed method to assess the usability of the RCP-GCM-RCM modelling setup and description of the first results (28/02/2021)

   C3S is aiming to build a EURO-CORDEX ensemble which is as complete as possible. By doing this, C3S will fill some of the missing elements of the EURO-CORDEX GCM-RCM-RCP uncertainty matrix. As we will have more simulations available (and these being complete sub-matrices, for instance), we are in a better position to assess how the full matrix can be reproduced when based on fewer available model simulations. In addition, we can determine how the missing model elements can be built. This unique study gives valuable insights into the optimal design of such ensemble systems in the future.
   

   
   

7. Documentation for the role of internal variability for Europe (31/03/2021)

   This report describes the regional and local effects of internal climate variability as described by two sets of downscaled data for two different three-member GCM ensembles and two downscaled single-model multi-member ensembles.
   

   
   

8. A scientific assessment of the usability of the RCP-GCM-RCM setup (11/07/2021)

   This report outlines a scientific assessment of the usability of the experimental setup for the choice of forcing scenarios (RCPs), global (GCMs) and regional climate models (RCMs), which has been used to decide what additional EURO-CORDEX simulations were performed for C3S.
   

   
   

9. Differences between CMIP5 GCMs downscaled by EURO-CORDEX RCMs and the full CMIP5 and CMIP6 ensembles, with focus on Europe (29/06/2021)

   This report analyses Global Climate Models (GCMs) for Europe covering the entire set of CMIP5 models, the CMIP5 models used for driving EURO-CORDEX Regional Climate Models (RCMs) and the available CMIP6 ensemble.

   
   

10. Evaluation reports per domain and user guide (20/07/2021)

    This report summarises the evaluation framework used for the worldwide CORDEX simulations. It explains the model diagnostic and evaluation tools and give a short summary how the provided plots can be interpreted. 

    
    

11. Validation framework (30/06/2021)

    This report summarises the validation diagnostics deployed for the worldwide CORDEX simulations. It helps in the interpretation of the validation plots produced. 

Additional resources

A training resource in python is available via a Jupyter Notebook on the C3S data tutorials page here: https://ecmwf-projects.github.io/copernicus-training-c3s/projections-cordex.html

Frequently Asked Questions (FAQs) 

There is a C3S regional climate projections User Forum that contains a number of FAQs related to CORDEX data. These questions and answers cover a wide range of topics and may be of interest to both any CORDEX data users and general climate projection data users.

References

THE ENTIRE C3S CORDEX GRAND-ENSEMBLE DATASET:

• Diez-Sierra, J., et al. (2022): The Worldwide C3S CORDEX Grand Ensemble: A Major Contribution to Assess Regional Climate Change in the IPCC AR6 Atlas. Bull. Amer. Meteor. Soc., 103, E2804–E2826, https://doi.org/10.1175/BAMS-D-22-0111.1.

AFR-CORDEX:

• Nikulin G, Lennard C, Dosio A, et al. (2018) The effects of 1.5 and 2 degrees of global warming on Africa in the CORDEX ensemble, Environ. Res. Lett., doi:10.1088/1748-9326/aab2b4,  http://iopscience.iop.org/article/10.1088/1748-9326/aab1b1
• Nikulin G., Jones, C. , Giorgi, F., et al. (2013)  Precipitation Climatology in An Ensemble of CORDEX-Africa Regional Climate Simulations,  J. Climate, 25, 6057–6078. http://doi.org/10.1175/JCLI-D-11-00375.1

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• Teichmann, C., Jacob, D., Remedio, A.R. et al. (2020) Assessing mean climate change signals in the global CORDEX-CORE ensemble. Clim Dyn.  https://doi.org/10.1007/s00382-020-05494-x
• Coppola, E., Raffaele, F., Giorgi, F. et al. (2021) Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble. Clim Dyn. https://doi.org/10.1007/s00382-021-05640-z

GENERAL REFERENCES:

• Moss, R., Edmonds, J., Hibbard, K. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010). https://doi.org/10.1038/nature08823

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