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Evaluation of thermal bioclimate based on observational data and numerical simulations: an application to Greece

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Abstract

The evaluation of thermal bioclimate can be conducted employing either observational or modeling techniques. The advantage of the numerical modeling approach lies in that it can be applied in areas where there is lack of observational data, providing a detailed insight on the prevailing thermal bioclimatic conditions. However, this approach should be exploited carefully since model simulations can be frequently biased. The aim of this paper is to examine the suitability of a mesoscale atmospheric model in terms of evaluating thermal bioclimate. For this, the numerical weather prediction Weather Research and Forecasting (WRF) model and the radiation RayMan model are employed for simulating thermal bioclimatic conditions in Greece during a 1-year time period. The physiologically equivalent temperature (PET) is selected as an index for evaluating thermal bioclimate, while synoptic weather station data are exploited for verifying model performance. The results of the present study shed light on the strengths and weaknesses of the numerical modeling approach. Overall, it is shown that model simulations can provide a useful alternative tool for studying thermal bioclimate. Specifically for Greece, the WRF/RayMan modeling system was found to perform adequately well in reproducing the spatial and temporal variations of PET.

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Authors and Affiliations

  1. Laboratory of Atmospheric Physics, School of Physics, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece

    Theodore M. Giannaros & Dimitrios Melas

  2. Chair of Meteorology and Climatology, Albert-Ludwigs University of Freiburg, Werthmannstrasse 10, 79085, Freiburg, Germany

    Andreas Matzarakis

Authors
  1. Theodore M. Giannaros
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  2. Dimitrios Melas
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  3. Andreas Matzarakis
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Correspondence to Theodore M. Giannaros.

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Giannaros, T.M., Melas, D. & Matzarakis, A. Evaluation of thermal bioclimate based on observational data and numerical simulations: an application to Greece. Int J Biometeorol 59, 151–164 (2015). https://doi.org/10.1007/s00484-014-0832-6

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  • DOI: https://doi.org/10.1007/s00484-014-0832-6

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