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The regional climate projections in the Climate Data Store (CDS) are a quality-controlled subset of the wider ( CORDEX ) dataset over Europedataset. The CORDEX vision is to advance and coordinate the science and application of regional climate downscaling through global partnerships. It aims to evaluate regional climate model performance through a set of experiments aiming at producing regional climate projections. The goals of CORDEX are:
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A set of 26 core variables (17 for non-European domains, corresponding corresponding to surface fields, see the table below)from the CORDEX archive were identified for the CDS. These are the most used variables of the CORDEX datadatasets. These variables are provided from 5 CORDEX experiment types (evaluation, historical and 3 RCP scenarios) that are derived (downscaled) from the CMIP5 experiments. 3The temporal resolution is 3-hourly, 6-hourly, daily and , monthly or seasonal information (GL Please check), whereas only daily information is provided for . Please note that for the non-European domains only daily datasets are available.
The CDS subset of CORDEX data have been through a metadata quality control procedure which ensures a high standard of reliability of the data. It may be for example that similar data can be found in the main CORDEX archive at the ESGF (Earth System Grid Federation) however these data come with no quality assurance and may have metadata errors or omissions. The quality-control process means that the CDS subset of CORDEX data is further reduced to exclude data that have metadata errors or inconsistencies. It is important to note that passing of the quality control should not be confused with validity: for example, it will be possible for a file to have fully compliant metadata but contain gross errors in the data that have not been noted. In other words, it means that the quality control is purely technical and does not contain any scientific evaluation (for instance consistency check).
Additional efforts (and funding) were devoted to support CORDEX activities by 1) providing support to archive in the ESGF relevant simulations available from the modelling centres for non-European domains not otherwise published in the ESGF earliernodes, and 2) makingmaking new simulations for the EURO-CORDEX domains. These activities are contributing to a significant enhancement of the regional climate model matrix over different domains in terms of emission scenarios, global model forcing and regional climate models. For the non-European domains resources were put into finding simulations, which were not available before (and not published in the ESGF earlier).
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 Interactive Atlas, a new product of the IPCC allowing exploration of observed and projected climate data to complement the assessment of relevant datasets undertaken in the WG I WGI chapters of IPCC.
In 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.
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The C3S-EURO-CORDEX subset aims to fill the gaps in this matrix between GCMs (aka "driving models), RCMs and RCPs. This will ensure better representation of uncertainties coming from GCMs, RCMs and RCP scenarios and make possible to study the regional climate change signals in a more comprehensive fashion.
The driving GCM and RCM models included in the CDS-CORDEX subsets CORDEX subsets for the different domains available are detailed in the table 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 these include 8 GCMs and 13 RCMs for EURO-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.
JOSE: I see that you haven't included non-comercial datasets at COPERNICUS. I guess this would be the same for all domains (we talked about this a couple of times, but I was not aware that this decision was made; I am in favor, no problem with that, just to know). This has no implications for NAM and ARC (all are unrestricted) but might have for other domains (I will check the impact and let you know).
, while the data presented in the CDS are released without any restriction.
WE NEED THE ADDITIONAL TABLES HERE FOR THE OTHER DOMAINS, PLEASE!
| Driving Global Coupled Models | |||||||||||||||||||||||||
| HadGEM2-ES | EC-EARTH | CNRM-CM5 | NorESM1-M | MPI-ESM-LR | IPSL-CM5A-MR | CanESM2 | MIROC5 | ||||||||||||||||||
Regional Climate Models | RCA4 (SMHI) | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | ||||||||
| CCLM-8-17 (ETH) | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |||||||||||||||
| crCLIM-v1-1-1 (ETH) | 1 | 1 | 2 | ||||||||||||||||||||||
| REMO2009 (GERICS) | 2 | 2 | 2 | 1 | |||||||||||||||||||||
| REMO2015 (GERICS) | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||||||||
| RACMO22E (KNMI) | 1 | 1 | 1 | 1 | 2 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |||||||||||
| HIRHAM5 (DMI) | 1 | 2 | 2 | 2 | 4 | 1 | 2 | 2 | 1 | ||||||||||||||||
| WRF361H (UHOH) | 1 | ||||||||||||||||||||||||
| WRF381P (IPSL) | 1 | 1 | 1 | 1 | 1 | 1 | |||||||||||||||||||
| ALADIN53 (CNRM) | 1 | 1 | 1 | ||||||||||||||||||||||
| ALADIN63 (CNRM) | 1 | 1 | 1 | 1 | 1 | ||||||||||||||||||||
| RegCM4.6.1 (ICTP) | |||||||||||||||||||||||||
| HadGEM3-GA7-05 (MOHC) | 1 | 1 | |||||||||||||||||||||||
| RCP26 | RCP45 | RCP85 | [0-9] = Number of simulations | ||||||||||||||||||||||
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| Name | Short name | Units | Description |
|---|---|---|---|
| 2m temperature | tas | K | The temperature of the air near the surface (or ambient temperature). The data represents the mean over the aggregation period at 2m above the surface. |
| 200hPa temperature | ta200 | K | The temperature of the air at 200hPa. The data represents the mean over the aggregation period at 200hPa pressure level. |
| Minimum 2m temperature in the last 24 hours | tasmin | K | The minimum temperature of the air near the surface. The data represents the daily minimum at 2m above the surface. |
| Maximum 2m temperature in the last 24 hours | tasmax | K | The maximum temperature of the air near the surface. The data represents the daily maximum at 2m above the surface. |
| Mean precipitation flux | pr | kg.m-2.s-1 | The deposition of water to the Earth's surface in the form of rain, snow, ice or hail. The precipitation flux is the mass of water per unit area and time. The data represents the mean over the aggregation period. |
| 2m surface relative humidity | hurs | % | The relative humidity is the percentage ratio of the water vapour mass to the water vapour mass at the saturation point given the temperature at that location. The data represents the mean over the aggregation period at 2m above the surface. |
| 2m surface specific humidity | huss | Dimensionless | The amount of moisture in the air at 2m above the surface divided by the amount of air plus moisture at that location. The data represents the mean over the aggregation period at 2m above the surface. |
| Surface pressure | ps | Pa | The air pressure at the lower boundary of the atmosphere. The data represents the mean over the aggregation period. |
| Mean sea level pressure | psl | Pa | The air pressure at sea level. In regions where the Earth's surface is above sea level the surface pressure is used to compute the air pressure that would exist at sea level directly below given a constant air temperature from the surface to the sea level point. The data represents the mean over the aggregation period. |
| 10m Wind Speed | sfcWind | m.s-1 | The magnitude of the two-dimensional horizontal air velocity. The data represents the mean over the aggregation period at 10m above the surface. |
| Surface solar radiation downwards | rsds | W.m-2 | The downward shortwave radiative flux of energy per unit area. The data represents the mean over the aggregation period at the surface. |
| Surface thermal radiation downward | rlds | W.m-2 | The downward longwave radiative flux of energy inciding on the surface from the above per unit area. The data represents the mean over the aggregation period. |
| Surface upwelling shortwave radiation | rsus | W.m-2 | The upward shortwave radiative flux of energy from the surface per unit area. The data represents the mean over the aggregation period at the surface. |
| Total cloud cover | clt | Dimensionless | Total refers to the whole atmosphere column, as seen from the surface or the top of the atmosphere. Cloud cover refers to fraction of horizontal area occupied by clouds. The data represents the mean over the aggregation period. |
| 500hPa geopotential | zg500 | m | The gravitational potential energy per unit mass normalized by the standard gravity at 500hPa at the same latitude. The data represents the mean over the aggregation period at 500hPa pressure level. |
| 10m u-component of wind | uas | m.s-1 | The magnitude of the eastward component of the wind. The data represents the mean over the aggregation period at 10m above the surface. |
| 10m v-component of wind | vas | m.s-1 | The magnitude of the northward component of the wind. The data represents the mean over the aggregation period at 10m above the surface. |
| 200hPa u-component of the wind | ua200 | m.s-1 | The magnitude of the eastward component of the wind. The data represents the mean over the aggregation period at 200hPa above the surface. |
| 200hPa v-component of the wind | va200 | m.s-1 | The magnitude of the northward component of the wind. The data represents the mean over the aggregation period at 200hPa pressure level. |
| 850hPa U-component of the wind | ua850 | m.s-1 | The magnitude of the eastward component of the wind. The data represents the mean over the aggregation period at 850hPa pressure level. |
| 850hPa V-component of the wind | va850 | m.s-1 | The magnitude of the northward component of the wind. The data represents the mean over the aggregation period at 850hPa pressure level. |
| Total run-off flux | mrro | kg.m-2.s-1 | The mass of surface and sub-surface liquid water per unit area and time, which drains from land. The data represents the mean over the aggregation period. |
| Mean evaporation flux | evspsbl | kg.m-2.s-1 | The mass of surface and sub-surface liquid water per unit area ant time, which evaporates from land. The data includes conversion to vapour phase from both the liquid and solid phase, i.e., includes sublimation, and represents the mean over the aggregation period. |
| Land area fraction | sftlf | % | The The fraction (in percentage) of the surface model grid cell occupied by land , aka land/sea masksurface. The data data is time-independent. |
| Orography | orog | m | The surface altitude in the modelmodel height above the geoid (being 0.0 over the ocean). The data is time-independent. |
Data 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 modeling community. See the more details: What are NetCDF files and how can I read them
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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.
- 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.
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