Abstract
The influence of the environment on the human beings in the aspect of different weather conditions is one of the main problems in the modern science. The degree of sultriness and coldness are decisive for the regular and stable work of the human thermoregulatory system. That affects the ability of the human beings to doing their work and everyday activities, and more important to the possible advent of different heat and cold related diseases. The weather influence is manifested in different ways, but the most notable one is the sensation to the thermal properties of the environment. That means how cold or how hot the human individual feels it is. Our research is focused on the calculation of three characteristics of the human thermal sensation called biometeorological indices. They are Predicted Mean Vote, Physiological Equivalent Temperature and Universal Thermal Climate Index. The RayMan model, which simulates the short- and long-wave radiation flux densities from the three-dimensional surroundings in simple and complex environment calculates also these indexes. A model setup is configured for Bulgaria and some adjacent territories and the computations are performed in fine-spaced grid on hourly basis. Assimilated ground measurements from the operative system ProData and data from the meteorological reanalyses ERA5 are used as weather input. The calculations are performed for four typical for each season months and the output is in form of three-dimensional digital maps of the considered indices. The results, which are spatially and temporally consistent, show either high and low spatial variability in different regions of the domain.
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Acknowledgements
We acknowledge the RayMan model vendors and the other organizations (ECMWF, UNI-DATA, MPI-M), which provides free of charge software and data. Without their innovative data services and tools this study would be not possible. The research work is supported by the Project “NATIONAL GEO-INFORMATION CENTER”, subject of the National Road Map for Scientific Infrastructure 2017–2023, funded by Contr. No D01-161/28.08.2018.
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Ivanov, V., Chervenkov, H. (2021). Modelling Human Biometeorological Conditions Using Meteorological Data from Reanalysis and Objective Analysis—Preliminary Results. In: Georgiev, I., Kostadinov, H., Lilkova, E. (eds) Advanced Computing in Industrial Mathematics. BGSIAM 2018. Studies in Computational Intelligence, vol 961. Springer, Cham. https://doi.org/10.1007/978-3-030-71616-5_16
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