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A web-based Decision Support System, named FLIRE DSS, for combined forest fire control and planning as well as flood risk management, has been developed and is presented in this paper. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of the web based DSS without the need of local installation of complex software and their maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in such a way plan its efficient elimination. Also, during dry periods, agencies can implement “what-if” scenarios for areas that are prone to fire and thus have available plans for forest fire management in case such scenarios occur. Flood services include flood maps and flood-related warnings and become available to relevant authorities for visualization and further analysis on a daily basis. When flood warnings are issued, relevant authorities may proceed to efficient evacuation planning for the areas that are likely to flood and thus save human lives. Real-time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real-time, and a high resolution weather forecast grid supports flood modeling as well as the development of “what-if” scenarios for the fire modeling. All these can be accessed by various computer sources including PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. All these methods and tools provide the end users with the necessary information to design an operational plan for the elimination of the fire events and the efficient management of the flood events in almost real time. Concluding, the FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.

Heatwave events are of major concern in the global context, since they can significantly impact ecosystems, economies and societies. For this reason, more detailed analyses of the characteristics and trends of heatwaves represent a priority that cannot be neglected. In this study, the interannual and decadal variability of seven indices of heatwaves were investigated during the warmest period of the year (June–August) by using an enhanced resolution reanalysis model (ERA5-Land) over a 71-year period (1950–2020) for the area of Greece. Heatwaves were defined as periods where two thresholds, based on a modified version of the Excess Heat Factor index (EHF) and the 95th percentile of the maximum daily temperature, were exceeded for at least three consecutive days. Greece experiences almost yearly 0.7 heatwaves on average during the whole period of study, while this value has increased by ~80% since 1990. Trend analysis revealed that heatwaves have become more frequent, longer, and more intense since 1950. The percentage of the land area that experiences at least one heatwave per year was almost doubled in the examined period. An increasing trend in the number of heatwaves that occurred in June was identified. [ABSTRACT FROM AUTHOR]

This study examines the mechanisms of flood-risk precautionary behavior among Greek citizens. To that end, it specifies a comprehensive model in which risk perception and worry mediate the effects of awareness-raising factors and confidence attitudes on individuals' flood preparedness. Both the current preparedness and preparedness intention are assessed. Raw data were obtained via an online survey that received 1855 responses. Findings from SEM (structural equation modeling) analysis indicate that worry mediates the effects of awareness and confidence on preparedness; risk perception is limited to the activation of preparedness intention. The results also suggest that past risk perceptions might have affected prior preparedness motivations associated with current preparedness. Interestingly, citizens who had already undertaken preparedness measures in the past appear to be more willing to invest in new measures. Implications for improving flood risk management are discussed. [ABSTRACT FROM AUTHOR]

Climate-related hazards, such as wildfires and hydrogeological phenomena, cause extensive damages and casualties around the world. Despite the recent advances and technologies for risk mitigation, it is acknowledged that public risk perception is a critical factor for these tools to succeed. Greece and the broader Eastern Mediterranean is an area where, despite the diversity of natural disasters, there is a lack of understanding of the hazard types that people are most concerned with and how they measure against other groups of hazards (i.e., geophysical). This work uses an online survey targeting Greek people, aiming to provide a better understanding of their perception of different natural hazards. Statistical results show that people consider climate-related hazards less dangerous and likely to occur than earthquakes, which occur often as zero-impact events. Laymen may thus underestimate certain risks, which may inhibit appropriate preparation. Disaster experience was found to increase threat perceptions and to motivate preparedness. However, in what concerns climate-related hazards, the effect of experience may fade out over time. Awareness activities were found to associate with higher emergency response efficacy. Males exhibit lower risk perception and higher coping appraisals. However, prioritization of risks is almost identical between genders. Implications for risk management are discussed. [ABSTRACT FROM AUTHOR]

Lighting has been studied extensively in Europe in the last years as a result of the denser lightning network sensors however, few if none had studied the connection with circulation types on the continental scale. In this study we are using ZEUS lightning network (Kotroni, 2008) data available at every 3 hours per day for the period of 2005-2015. Since the atmospheric instability is more frequent during the summer season, we used six months from each year (from April to September). We extracted data at every 6 hours from Climate Forecast Reanalysis System (Saha et al, 2010) at a resolution of 0.5 degrees for 12 parameters related to atmospheric instability. In order to check their relevance in lightning occurrence, we build a linear model where we included each of them. Then, a step-wise regression was used to check their importance. Based on their statistically significance, we selected only the parameters that are relevant to the model. Finally, a Principal Component Analysis was used in order to remove the autocorrelation between the parameteres as well to reduce the data dimension. We assigned the principal scores explaining the variance of data in proportion of ~90 % to a daily classification of atmospheric circulation types obtained after using the cost733class software (Philipp et al., 2016) and check their correlation with lightning frequency upon each cell. The first results are indicating meridional circulation types as being more frequent in atmospheric instability as well in producing more lightning in central to south-eastern Europe. Also, the instability indices are linearly correlated with the lightning frequency. This work was supported by a Short Term Scientific Mission Grant COST Action 15211. The author would like to thank EU and COST funding under the EU Framework Programme Horizon 2020. [ABSTRACT FROM AUTHOR]

The applicability of GNSS (Global Navigation Satellite Systems) derived IWV (Integrated Water Vapor) data, on the nowcasting of high impact precipitation events is examined. High temporal resolution (10-min) rain gauge data provided by the automatic weather stations NOANN network of the National Observatory of Athens (NOA) are used. The analysis was performed for selected high precipitation events spanning over an 8-months period during 2018. It was shown that the IWV values present good association to the severity of the precipitation, while the nowcasting of such events may be improved with the combined use of other sources of data, like satellite images or model outputs. The present work was carried out in the frame of the project "BalkanMed real time severe weather service (BeRTISS)" which is co-funded by the European Union and national funds of the participating countries. [ABSTRACT FROM AUTHOR]