RESUMEN

The identification of the large-scale atmospheric circulation patterns which are associated with extreme fire weather is of great importance for developing early warning systems, management strategies, and for increasing awareness and preparedness of all the involved entities, including both the public and practitioners. Such a forecasting approach is currently missing in Greece and many other countries. Furthermore, considering climate projections over the Mediterranean, which indicate an environment more conducive to wildfire activity, the need for timely forecasting of extreme fire weather becomes increasingly urgent. Here, we present an alternative fire weather forecasting framework using ERA5 reanalysis data of atmospheric variables and fire weather indices of the Canadian Forest Fire Weather Index System (CFFWIS) during the period June-October from 1979 to 2019. Within this framework, we define the critical fire weather patterns (CFWPs) of Greece associated with different levels of fire weather severity by applying Self-Organizing-Maps (SOMs) on mid-tropospheric geopotential height. We quantify the fire weather conditions associated with each CFWP. Using a set of CFFWIS indices and key fire weather variables, our SOM-based analysis reveals five distinct CFWPs linked to different levels and characteristics of fire weather severity. The lowest fire weather severity is associated with lower than average geopotential heights, and anomalous cold and moist weather. The highest fire weather severity is associated with higher than average geopotential heights, and anomalous hot, dry, and windy conditions, suggesting the potential for wind-driven wildfires. Our analysis yields elevated fire weather severity linked to a CFWP, when hot and dry conditions are accompanied by atmospheric instability, suggesting the potential for plume-driven wildfires and the potential for pyroconvection. The main advantage of this forecasting framework is that it could be used for providing valuable information regarding the upcoming fire weather conditions even up to 7-12 days in advance depending on the atmospheric predictability.

RESUMEN

Existing assessments of the thermal-related impact of the environment on humans are often limited by the use of data that are not representative of the population exposure and/or not consider a human centred approach. Here, we combine high resolution regional retrospective analysis (reanalysis), population data and human energy balance modelling, in order to produce a human thermal bioclimate dataset capable of addressing the above limitations. The dataset consists of hourly, population-weighted values of an advanced human-biometeorological index, namely the modified physiologically equivalent temperature (mPET), at fine-scale administrative level and for 10 different population groups. It also includes the main environmental drivers of mPET at the same spatiotemporal resolution, covering the period from 1991 to 2020. The study area is Greece, but the provided code allows for the ease replication of the dataset in countries included in the domains of the climate reanalysis and population data, which focus over Europe. Thus, the presented data and code can be exploited for human-biometeorological and environmental epidemiological studies in the European continent.

RESUMEN

Greece was affected by a prolonged and extreme heat wave (HW) event (July 28-August 05) during the abnormally hot summer of 2021, with the maximum temperature in Athens, the capital of the country, reaching up to 43.9 °C in the city center. This observation corresponds to the second highest maximum temperature recorded since 1900, based on the historical temperature time series of the National Observatory of Athens weather station at Thissio. In the present study, a multi-scale numerical modeling system is used to analyze the urban climate and thermal bioclimate in the Athens urban area (AUA) in the course of the HW event, as well as during 3 days prior to the heat wave and 3 days after the episode. The system consists of the Weather Research and Forecasting model, the advanced urban scheme BEP/BEM (Building Energy Parameterization/Building Energy Model) and the human-biometeorological model RayMan Pro, and incorporates the local climate zone (LCZ) classification scheme. The system's validation results demonstrated a robust modeling set-up, characterized by high capability in capturing the observed magnitude and diurnal variation of the urban meteorological and heat stress conditions. The analysis of two- and three-dimensional fields of near-surface air temperature, humidity and wind unraveled the interplay of geographical factors (surface relief and proximity to the sea), background atmospheric circulations (Etesians and sea breeze) and HW-related synoptic forcing with the AUA's urban form. These interactions had a significant impact on the LCZs heat stress responsiveness, expressed using the modified physiologically equivalent temperature (mPET), between different regions of the study area, as well as at inter- and intra-LCZ level (statistically significant differences at 95 % confidence interval), providing thus, urban design and health-related implications that can be exploited in human thermal discomfort mitigation strategies in AUA.

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RESUMEN

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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