Exploiting regional reanalysis data for assessing long-term trends of the human thermal bioclimate in Greece

The comprehensive assessment of the human bioclimate requires considering the four principal meteorological variables that affect the thermal environment (i.e. temperature, humidity, wind speed and global solar radiation). It also requires using data at spatial scales that are relevant to the population exposure. Meeting these requirements with the use of ground-based weather stations is usually unattainable at nation-wide level. This is partially due to the incomplete spatiotemporal availability of the relevant observational data (especially of global solar radiation), as well as to the fact that the monitoring stations are often present in locations (e.g. airports) that are not representative of the human-biometeorological conditions. Gridded climate data can be used to overcome the above issues. In view of this fact, here, we exploit regional reanalysis data to perform a long-term (1991-2020) analysis of the human thermal bioclimate and its trends in Greece. To this end, the Copernicus European Regional Reanalysis (CERRA) dataset, at 5.5 km spatial resolution, is used. The CERRA dataset is combined with population data to better reflect the thermal environment experienced by the people through a population-weighted approach at regional units or combinations thereof that are based on the NUTS-3 (Nomenclature of Territorial Units for Statistics-3) classification. The population data are further used to assess the thermal-related risk in terms of annual number of exposure person-days, focusing on bioclimatic extremes. The latter are expressed by an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), which is computed with the use of the RayMan Pro model. Short-term acclimatization effects are considered for mPET by adjusting the extremes’ thresholds through the application of a 30-day Gaussian filter. The present work is performed in the frame of the HEAT-ALARM project and provides preliminary results of the above described analysis, highlighting that regional reanalysis data can be valuable for climate assessments in the context of human-biometeorology, especially when combined with the consideration of population exposure aspects.