Abstract
We present the first evaluation of the wind field from the ensemble of kilometer-scale simulations from the CORDEX-Flagship Pilot Study on convection, with focus on the Adriatic region. Kilometer-scale climate models, also known as convection-permitting models (CPMs), produce a good representation of small-scale topographic features and consequently a more detailed depiction of dynamical and thermal circulations. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic region. We investigate the (potential) added value introduced by CPMs compared to classical “cumulus-parametrized” regional climate models (RCMs), reanalysis and station observations. For this purpose, wind components at 10 m level are used at 3-hourly frequency. All simulations cover a 10-year period, extending from 2000 to 2009. In terms of the standard statistical parameters such as correlation coefficient and temporal standard deviation, CPMs are very dependent on their parent RCM performance. However, the orographic forcing emphasizes the potential added value and CPMs contain some fine spatial scale variability (i.e., stronger extremes by 25% and more accurate wind direction) that is absent in coarser RCMs and reanalysis. The potential added value is higher in the cold season compared to the warm season due to the proportion of severe wind events. CPMs reproduce well the typical wind regimes along the Adriatic coast, namely Bora and Sirocco. The benefit of using CPMs is especially pronounced in simulating Bora maximum wind speeds in northern Adriatic and Sirocco frequencies in southern Adriatic. Based on our overall analysis, we conclude that CPMs provide added value compared to coarser models, especially in the complex coastal terrain.
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Data availability
The datasets analyzed during the current study are available via the data exchange infrastructure and services provided by the Jülich Supercomputing Centre, Germany, as part of the Helmholtz Data Federation initiative.
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Acknowledgements
All authors gratefully acknowledge the WCRP-CORDEX-FPS on Convective phenomena at high resolution over Europe and the Mediterranean (FPSCONVALP- 3) and the research data exchange infrastructure and services provided by the Jülich Supercomputing Centre, Germany, as part of the Helmholtz Data Federation initiative. The ETH, IPSL, ICTP, SMHI, CMCC, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https:// www. eucp- project.eu, grant agreement No. 776613). IPSL’s work was granted access to the HPC resources of TGCC under the allocations 2019-A0030106877 and 2020-A0030106877 made by GENCI. DB acknowledges funding from the FORMAS project EDUCAS (grant no. 2019-00829). MED acknowledges the Partnership for advanced computing in Europe (PRACE) for awarding access to Piz Daint at ETH Zürich at the Swiss National Supercomputing Centre (CSCS, Switzerland). MED also acknowledges the Federal Office for Meteorology and Climatology (MeteoSwiss), CSCS, the Center for Climate Systems Modeling (C2SM) and ETH Zürich for their contributions to the development and maintenance of the GPU-accelerated version of COSMO. ØH has received support from the project GREAT, funded by the Research Council of Norway (grant no. 275589), and acknowledge computing resources from Notur (NN9188K). SK acknowledges the support of the Greek Research and Technology Network (GRNET) High Performance Computing (HPC) infrastructure for providing the computational resources of AUTH-simulations (under project IDs pr003005 and pr009020) and the AUTH Scientific Computing Center for technical support. JM acknowledges the support from the Spanish Agencia Estatal de Investigación through the Unidad de Excelencia María de Maeztu with reference MDM-2017-0765, the projects CORDyS (PID2020-116595RB-I00) and ATLAS (PID2019-111481RB-I00), both funded by MCIN/AEI/10.13039/501100011033. EP acknowledges the Consorzio Inter-universitario per il Calcolo Automatico dell’Italia Nord Orientale (CINECA) super-computing center (Bologna, Italy) for computing resources dedicated to ICTP simulations. HT is thankful for the computational resources granted by the John von Neumann Institute for Computing (NIC) and provided on the supercomputer JURECA at the Jülich Supercomputing Centre (JSC) through the grant JJSC39 and for the computational resources at the Vienna Scientific Cluster (VSC) through the grants 70992 and 71193, the long-term storage provided by the cooperation project GEOCLIM Data Infrastructure Austria, funded by the Austrian Education, Science and Research Ministry (BMBWF), as well as for the support received via the project “reclip:convex”, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (no. B769999).
Funding
The ETH, IPSL, ICTP, SMHI, CMCC, KNMI was supported by the HORIZON 2020 EUCP (European Climate Prediction System) project (https:// www. eucp- project.eu, grant agreement No. 776613). DB was supported by the FORMAS project EDUCAS (grant no. 2019–00829). HT was supported by the John von Neumann Institute for Computing (NIC) through the grant JJSC39 and by Vienna Scientific Cluster (VSC) through the grants 70992 and 71193, the long-term storage provided by the cooperation project GEOCLIM Data Infrastructure Austria, funded by the Austrian Education, Science and Research Ministry (BMBWF). HT was supported via the project “reclip:convex”, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (no. B769999). JM was supported from the Spanish Agencia Estatal de Investigación through the Unidad de Excelencia María de Maeztu with reference MDM-2017–0765, the projects CORDyS (PID2020-116595RB-I00) and ATLAS (PID2019-111481RB-I00), both funded by MCIN/AEI/10.13039/501100011033. ØH has received support from the project GREAT, funded by the Research Council of Norway (grant no. 275589).
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ABV, DB, MTP and IG contributed to the study conception and design. Material preparation, data collection and analysis were performed by ABV. The authors DB and from SB to KWS performed the simulations. The first draft of the manuscript was written by ABV and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Belušić Vozila, A., Belušić, D., Telišman Prtenjak, M. et al. Evaluation of the near-surface wind field over the Adriatic region: local wind characteristics in the convection-permitting model ensemble. Clim Dyn (2023). https://doi.org/10.1007/s00382-023-06703-z
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DOI: https://doi.org/10.1007/s00382-023-06703-z