Abstract
AbstractAtmospheric circulation type classification methods were applied to an ensemble of 57 regional climate model simulations from Euro-CORDEX, their 11 boundary models from CMIP5 and the ERA5 reanalysis. We applied a field anomaly technique to focus on the departure from the domain-wide daily mean. We then compared frequencies of the different circulation types in the simulations with ERA5 and found that the regional models add value especially in the summer season. We applied three different classification methods (the subjective Grosswettertypes and the two optimisation algorithms SANDRA and distributed k-means clustering) from the cost733class software and found that the results are not particularly sensitive to choice of circulation classification method. There are large differences between models. Simulations based on MIROC-MIROC5 and CNRM-CERFACS-CNRM-CM5 show an over-representation of easterly flow and an under-representation of westerly. The downscaled results retain the large-scale circulation from the global model most days, but especially the regional model IPSL-WRF381P changes the circulation more often, which increases the error relative to ERA5. Simulations based on ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR show consistently smaller errors relative to ERA5 in all seasons. The ensemble spread is largest in summer and smallest in winter. Under the future RCP8.5 scenario, the circulation changes in the summer season, with more than half of the ensemble showing a decrease in frequency of the Central-Eastern European high, the Scandinavian low as well as south-southeasterly flow. There is in general a strong agreement in the sign of the change between the regional simulations and the data from the corresponding global model.
Funder
Norwegian Meteorological Institute
Publisher
Springer Science and Business Media LLC
Reference34 articles.
1. Bell B, Hersbach H, Berrisford P, Dahlgren P, Horányi A, Muñoz Sabater J, Nicolas J, Radu R, Schepers D, Simmons A, Soci C, Thépaut JN (2020) ERA5 hourly data on single levels from 1950 to 1978 (preliminary version). Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://cds.climate.copernicus-climate.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-preliminary-back-extension?tab=overview. Accessed 28 June 2021
2. Belleflamme A, Fettweis X, Lang C, Erpicum M (2013) Current and future atmospheric circulation at 500 hPa over Greenland simulated by the CMIP3 and CMIP5 global models. Clim Dyn 41(7):2061–2080. https://doi.org/10.1007/s00382-012-1538-2
3. Brands S (2021) A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the northern hemisphere. Geosci Model Dev Discuss 15(4):1375–1411. https://doi.org/10.5194/gmd-2020-418. https://gmd.copernicus.org/preprints/gmd-2020-418/
4. Cahynová M, Huth R (2016) Atmospheric circulation influence on climatic trends in Europe: an analysis of circulation type classifications from the COST733 catalogue. Int J Climatol 36(7):2743–2760. https://doi.org/10.1002/joc.4003. https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.4003
5. Cannon AJ (2020) Reductions in daily continental-scale atmospheric circulation biases between generations of global climate models: CMIP5 to CMIP6. Environ Res Lett 15(6):064006. https://doi.org/10.1088/1748-9326/ab7e4f. https://doi.org/10.1088/1748-9326/ab7e4f
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