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Sensitivity of the Simulated Heat Risk in Southeastern Europe to the RegCM Model Configuration—Preliminary Results

  • Vladimir IvanovEmail author
  • Georgi Gadzhev
  • Kostadin Ganev
  • Hristo Chervenkov
Conference paper
  • 9 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11958)

Abstract

The spatial distribution of the biometeorological conditions is a topic of many studies in different countries. One of the most important aspects of the weather adverse effect on the human beings is the consequences from too much exposure to the heat conditions. The human body can adapt to temperatures, but to some extent. If the air temperatures become too high, human beings at first feel uncomfortable, but the consequences can be a serious threat to health and even life. The main reasons for this threat are related to the lack of perspiration and cardiovascular problems. Atmospheric numerical models for simulating the heat stress is used in many studies. One of the most affected region in the near past, but also most likely in the future, is the Southeastern Europe, including Bulgaria. Global models are with too low resolution, but still they suggest very strong heat stress especially at the end of the 21th century. According to other studies, results from regional meteorological models suggest similar conclusions. The current research is about the heat stress conditions in the Balkan Peninsula, evaluated from ten–year simulations. They are performed with regional climate model RegCM. The model is run many times with different combinations of physics parameterization of some processes. The aim is to compare the heat stress simulated by different model configurations for the Balkan Peninsula and so to reveal the dependence of heat stress evaluation on the model configuration. That would answer the question of the sensitivity of the model to the parameterization schemes from a biometeorological point of view.

Keywords

Regional climate simulation RegCM4.4 Heat index Heat stress High performance computing 

Notes

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 was partially supported by the Bulgarian Ministry of Education and Science under the National Research Programme “Young scientists and postdoctoral students” approved by DCM №577/17.08.2018 and by the Bulgarian National Science Fund (DN–14/3 13.12.2017).

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 DO-230/06-12-2018).

Deep gratitude to the organizations and institutes (ICTP, ECMWF, NCEP–NCAR, ECA&D, Unidata, MPI–M 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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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Vladimir Ivanov
    • 1
    Email author
  • Georgi Gadzhev
    • 1
  • Kostadin Ganev
    • 1
  • Hristo Chervenkov
    • 2
  1. 1.National Institute of Geophysics, Geodesy and Geography – Bulgarian Academy of SciencesSofiaBulgaria
  2. 2.National Institute in Meteorology and HydrologySofiaBulgaria

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