A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses

Gebrechorkos, S., Leyland, J., Slater, L., Wortmann, M., Ashworth, P. J., Bennett, G. L., Boothroyd, R., Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X, Delorme, P., Griffith, H., Hardy, R., Hawker, L., McLelland, S., Neal, J., Nicholas, A., Tatem, A. J., Vahidi, E., Parsons, D. R. and Darby, S. E. (2023) A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses. Scientific Data, 10. 611. ISSN 2052-4463 doi: 10.1038/s41597-023-02528-x

Abstract/Summary

A large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events. The globally downscaled data are available at the Centre for Environmental Data Analysis (https://dx.doi.org/10.5285/c107618f1db34801bb88a1e927b82317) for the historical (1981-2014) and future (2015-2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5). This new climate dataset will be useful for assessing future changes and variability in climate and for driving high-resolution impact assessment models.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/113348
Identification Number/DOI	10.1038/s41597-023-02528-x
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Nature Publishing Group
Download/View statistics	View download statistics for this item