The benefits of increasing resolution in global and regional climate simulations for European climate extremes

Carley E. Iles*, Robert Vautard, Jane Strachan, Sylvie Joussaume, Bernd R. Eggen, Chris D. Hewitt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Many climate extremes, including heatwaves and heavy precipitation events, are projected to worsen under climate change, with important impacts for society. Future projections required for adaptation are often based on climate model simulations. Given finite resources, trade-offs must be made concerning model resolution, ensemble size, and level of model complexity. Here we focus on the resolution component. A given resolution can be achieved over a region using either global climate models (GCMs) or at lower cost using regional climate models (RCMs) that dynamically downscale coarser GCMs. Both approaches to increasing resolution may better capture small-scale processes and features (downscaling effect), but increased GCM resolution may also improve the representation of the large-scale atmospheric circulation (upscaling effect). The size of this upscaling effect is therefore important for deciding modelling strategies. Here we evaluate the benefits of increased model resolution for both global and regional climate models for simulating temperature, precipitation, and wind extremes over Europe at resolutions that could currently be realistically used for coordinated sets of climate projections at the pan-European scale. First we examine the benefits of regional downscaling by comparing EURO-CORDEX simulations at 12.5 and 50 km resolution to their coarser CMIP5 driving simulations. Secondly, we compare global-scale HadGEM3-A simulations at three resolutions (130, 60, and 25 km). Finally, we separate out resolution-dependent differences for HadGEM3-A into downscaling and upscaling components using a circulation analogue technique. Results suggest limited benefits of increased resolution for heatwaves, except in reducing hot biases over mountainous regions. Precipitation extremes are sensitive to resolution, particularly over complex orography, with larger totals and heavier tails of the distribution at higher resolution, particularly in the CORDEX vs. CMIP5 analysis. CMIP5 models underestimate precipitation extremes, whilst CORDEX simulations overestimate compared to E-OBS, particularly at 12.5 km, but results are sensitive to the observational dataset used, with the MESAN reanalysis giving higher totals and heavier tails than E-OBS. Wind extremes are somewhat stronger and heavier tailed at higher resolution, except in coastal regions where large coastal grid boxes spread strong ocean winds further over land. The circulation analogue analysis suggests that differences with resolution for the HadGEM3-A GCM are primarily due to downscaling effects.

Original languageEnglish
Article number247
Pages (from-to)5583-5607
Number of pages25
JournalGeoscientific Model Development
Volume13
Issue number11
DOIs
Publication statusPublished - 18 Nov 2020
Externally publishedYes

Bibliographical note

Funding Information:
Acknowledgements. This work is published in the name of the European Commission, with funding from the European Union through the Copernicus Climate Change Service project C3S_34a Lot 3 (Copernicus Roadmap for European Climate Projections). The European Commission is not responsible for any use that many be made of the information contained. We acknowledge the WCRP’s Working Group on Regional Climate and the Working Group on Coupled Modelling – the coordinating body of CORDEX and the panel responsible for CMIP5, respectively. We thank the climate modelling groups for producing and making available the model output listed in Supplement Table S1, which is available at http://pcmdi9.llnl.gov (last access” 1 December 2017). For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System science portals. We thank the modelling team that produced the UPSCALE simulations and acknowledge the JASMIN and IPSL mesocentre computing clusters on which this analysis was performed. We thank Tomas Landelius from SMHI for making the DYNAD wind data available. We also acknowledge helpful input from the CRECP project scientific advisory board and useful discussions with UK Met Office scientists, in particular Malcolm Roberts and Carol McSweeney. We thank Ab-hishekh Srivastava and three other anonymous reviewers for their helpful comments and suggestions.

Publisher Copyright:
© Author(s) 2020. This work is distributed under

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