Abstract
The RegCM is a regional climate model used in many studies. There are simulation runs in different domains, time periods, and regions in the world on all continents. The research works in our group are related to the historical and future climate, and its influence on the human sensation over Southeast Europe. We used the model versions 4.4 and 4.7. The main model components are the initial and boundary condition module, the physics processes parametrization module, and the dynamical core. Concerning the last one, we used the default one – the hydrostatic option corresponding to the MM5 model dynamical core. We run simulations with different combinations of parametrization schemes on the Bulgarian supercomputer Avitohol. The newer versions of the model have an additional option for using a non-hydrostatic dynamical core. The running of model simulations with different input configurations depends highly on the available computing resources. Several main factors influence the simulation times and storage requirements. They could vary much depending on the particular set of input parameters, domain area, land cover, processing cores characteristics, and their number in parallel processing simulations. The objective of that study is to analyse the RegCM model performance with hydrostatic core, and non–hydrostatic core, on the High–Performance Computing platform Avitohol.
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Acknowledgments
This work has been accomplished thanks to the computational capabilities, created in the framework of the MES Grant No. D01–221/03.12.2018 for NCDSC—part of the Bulgarian National Roadmap on RIs.
This work has been carried out in the framework of the National Science Program “Environmental Protection and Reduction of Risks of Adverse Events and Natural Disasters”, approved by the Resolution of the Council of Ministers №577/17.08.2018 and supported by the Ministry of Education and Science (MES) of Bulgaria (Agreement №D01-363/17.12.2020).
Deep gratitude to the organizations and institutes (ICTP, ECMWF, ECA&D, Unidata, Copernicus Climate Data Store and all others), which provide free of charge software and data. Without their innovative data services and tools this study would not be possible.
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Ivanov, V., Gadzhev, G. (2022). Behavior and Scalability of the Regional Climate Model RegCM4 on High Performance Computing Platforms. In: Lirkov, I., Margenov, S. (eds) Large-Scale Scientific Computing. LSSC 2021. Lecture Notes in Computer Science, vol 13127. Springer, Cham. https://doi.org/10.1007/978-3-030-97549-4_14
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