Global Bias-Corrected CORDEX Datasets at Half Degree Resolution
Bibliographic record
Abstract
<strong>Abstract:</strong> This dataset provides globally consistent, bias-corrected climate data at 0.5° spatial resolution, consisting of a set of seven climate variables derived from three General Circulation Models (GCMs) participating in CMIP5, downscaled by 10 CORDEX Regional Climate Model (RCM) simulations and bias-corrected globally for the period 1950/1960–2099. It includes data from three climate change scenarios, namely RCP2.6, RCP4.5 and RCP8.5. The three GCMs are: ICHEC-EC-EARTH, MPI-M-MPI-ESM-LR, NOAA-GFDL-GFDL-ESM2M. Data are originally available as one netCDF file per GCM (3) per variable (7, NOAA-GFDL-GFDL-ESM2M: 5) per run (4, NOAA-GFDL-GFDL-ESM2M: 3). Available here are netCDF files per quantity (see <strong>TableOfContents</strong>), run (historical, rcp26, rcp45, rcp85), and GCM (see <strong>Size</strong> for the overall sum per GCM). <strong>TableOfContents:</strong> daily mean 2m-air temperature (tas); daily minimum 2m-air temperature (tasmin), daily maximum 2m-air temperature (tasmax); daily sum of precipitation (pr); daily mean surface downwelling longwave radiation (rlds)*; daily mean 10m wind speed (sfcWind)*; daily mean relative humidity (hurs) *: These variables are NOT included in the NOAA-GFDL-GFDL-ESM2M driven data. <strong>TechnicalInfo:</strong> dimension: 720 columns x 360 rows; temporalExtent_startDate_Historlcal: 1950-01-01 00:00:00; temporalExtent_endDate_Historical: 2019-12-31 23:59:59; temporalDuration_Historical: 70; temporalDurationUnit_Historical: a; temporalExtent_startDate_RCPs: 2020-01-01 00:00:00; temporalExtent_endDate_RCPs: 2099-12-31 23:59:59; temporalDuration_RCPs: 80; temporalDurationUnit_RCPs: a; temporalResolution: 1; temporalResolutionUnit: d; spatialResolution: 0.5; spatialResolutionUnit: degree; horizontalResolutionXdirection: 0.5; horizontalResolutionXdirectionUnit: degree; horizontalResolutionYdirection: 0.5; horizontalResolutionYdirectionUnit: degree; verticalResolution: none; verticalResolutionUnit: none *) For MPI-M-MPI-ESM-LR: temporalExtent_startDate_Historlcal: 1960-01-01 00:00:00; temporalExtent_endDate_Historical: 2019-12-31 23:59:59; temporalDuration_Historical: 60; <strong>Methods: </strong> The ISIMIP3BASD v2.5 bias correction method (see Lange [2019; 2021]) was applied to adjust systematic biases using the GSWP3-W5E5 observational dataset. The regional climate models (RCMs) used are: (listed are Institution/working group, RCM Model, Driving GCM): Climate Service Center Germany (GERICS), REMO2009, MPI-ESM-LR Swedish Meteorological and Hydrological Institute (SMHI), RCA4, MPI-ESM-LR Climate Limited-area Modelling Community (CLMcom), CCLM4-8-17-CLM3-5, MPI-ESM-LR Climate Limited-area Modelling Community (CLMcom), CCLM5-0-2, MPI-ESM-LR Universite du Quebec a Montreal, CRCM5, MPI-ESM-LR Swedish Meteorological and Hydrological Institute (SMHI), RCA4, ICHEC-EC-EARTH Climate Limited-area Modelling Community (CLMcom), CCLM4-8-17-CLM3-5, ICHEC-EC-EARTH Climate Limited-area Modelling Community (CLMcom), CCLM5-0-2, ICHEC-EC-EARTH Swedish Meteorological and Hydrological Institute (SMHI), RCA4, NOAA-GFDL-GFDL-ESM2M National Center for Atmospheric Research, WRF, NOAA-GFDL-GFDL-ESM2M The historical runs begin 1950-01-01 (ICHEC-EC-EARTH and NOAA-GFDL-GFDL-ESM2M) or 1960-01-01 (MPI-M-MPI-ESM-LR) and end 2005-12-31. Historical runs are appended by rcp85 runs for years 2006-01-01 to 2019-12-31. All projection runs begin 2020-01-01 and end 2099-12-31. The routines (python) used to create and work with the data sets are available from this web page as well: Discontinuity_Analysis_GlobCORD-HC.py; IBICUS-BIAS-CORRECTION.py For more information please take a look at this publication: Yakubu et al., 2025. <strong>Quality:</strong> Not all of the domains have been downscaled by CORDEX RCMs. Therefore, data files for scenario rcp26 only contain 7 CORDEX domains; all other files contain 8 domains (see also https://cordex.org/domains/cordex-domain-description/) <strong>Units</strong> (see TableOfContents): K; K; K; kg m-2 s-1; W m-2; m s-1; percent <strong>GeoLocation:</strong> westBoundCoordinate: -167.0; westBoundCoordinateUnit: degrees East; eastBoundCoordinate: 180.0; eastBoundCoordinateUnit: degrees East; southBoundCoordinate: -56.0; southBoundCoordinateUnit: degrees North; northBoundCoordinate: 76.0; northBoundCoordinateUnit: degrees North <strong>Size:</strong> ICHEC-EC-EARTH: 137.7 GByte, MPI-M-MPI-ESM-LR: 130.6 GByte, NOAA-GFDL-GFDL-ESM2M: 55.5 GByte <strong>Format:</strong> netCDF <strong>DataSources:</strong> See the file "GloBCORD-HD_ESMs-RCMs.pdf" <strong>Contact:</strong> fuseini.yakubu (at) uni-hamburg.de; shabeh.hasson (at) uni-hamburg.de <strong>Webpage:</strong> https://www.geo.uni-hamburg.de/geographie/abteilungen/physische-geographie/arbeitsgruppen/ag-hareme.html
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".