A meticulous assessment of the risk of extreme environmental events is of great necessity for populations, civil authorities as well as the insurance /reinsurance industry. Koch (2017, 2018) introduced a concept of spatial risk measure and a related set of axioms which are well-suited to analyse and quantify the risk due to events having a spatial extent, precisely such as natural disasters. In this paper, we first carry out a detailed study of the correlation (and covariance) structure of powers of the Smith and Brown-Resnick max-stable random fields  . Then, using the latter results, we thoroughly investigate spatial risk measures associated with variance and induced by powers of max-stable random fields. In addition, we show that spatial risk measures associated with several classical risk measures and induced by such cost fields satisfy (at least ) part of the previously mentioned axioms under appropriate conditions on the max-stable fields. Considering such cost fields is particularly relevant when studying the impact of extreme wind speeds on buildings and infrastructure .
A meticulous assessment of the risk of impacts associated with extreme wind events is of great necessity for populations, civil authorities as well as the insurance industry. Using the concept of spatial risk measure and related set of axioms introduced by Koch (2017, 2019), we quantify the risk of losses due to extreme wind speeds. The insured cost due to wind events is proportional to the wind speed at a power ranging typically between 2 and 12. Hence we first perform a detailed study of the correlation structure of powers of the Brown-Resnick max-stable random fields and look at the influence of the power . Then, using the latter results, we thoroughly investigate spatial risk measures associated with variance and induced by powers of max-stable random fields. In addition, we show that spatial risk measures associated with several classical risk measures and induced by such cost fields satisfy (at least part of) the previously mentioned axioms under conditions which are generally satisfied for the risk of damaging extreme wind speeds . In particular, we specify the rates of spatial diversification in different cases, which is valuable for the insurance industry .
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