Assessment of wind–damage relations for Norway using 36 years of daily insurance data

Ashbin Jaison, A. Sorteberg, Clio Michel, Ø. Breivik
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Abstract

Abstract. Extreme winds are by far the largest contributor to Norway’s insurance claims related to natural hazards. The predictive skills of four different damage functions are assessed for Norway at the municipality and national levels on daily and annual temporal scales using municipality-level insurance data and the high-resolution Norwegian hindcast (NORA3) wind speed data for the period 1985–2020. Special attention is given to extreme damaging events and occurrence probabilities of wind-speed-induced damage. Because of the complex topography of Norway and the resulting high heterogeneity of the population density, the wind speed is weighted with the population. The largest per capita losses and severe damage occur most frequently in the western municipalities of Norway, which are more exposed to incoming storms from the North Atlantic, whilst there are seldom any large losses further inland. There is no single damage function that outperforms others. However, a good agreement between the observed and estimated losses at municipality and national levels for a combination of damage functions suggests their usability in estimating severe damage associated with windstorms. Furthermore, the damage functions are able to successfully reconstruct the geographical pattern of losses caused by extreme windstorms with a high degree of correlation. From event occurrence probabilities, the present study devises a damage classifier that exhibits some skill at distinguishing between daily damaging and non-damaging events at the municipality level. While large-loss events are well captured, the skewness and zero inflation of the loss data greatly reduce the quality of both the damage functions and the classifier for moderate- and weak-loss events.
利用 36 年的日常保险数据评估挪威的风灾关系
摘要迄今为止,极端风力是挪威与自然灾害有关的保险理赔的最大来源。利用1985-2020年期间市级保险数据和高分辨率挪威后报(NORA3)风速数据,对挪威市级和国家级的四种不同损害函数在日和年时间尺度上的预测能力进行了评估。其中特别关注了极端破坏事件和风速引起的损害的发生概率。由于挪威地形复杂,人口密度差异较大,因此风速按人口加权计算。最大的人均损失和严重破坏最常发生在挪威西部城市,因为这些城市更容易受到来自北大西洋的风暴的影响,而内陆地区则很少发生大的损失。没有一种损害函数优于其他函数。然而,在市镇和国家层面上,对损害函数组合的观测和估计损失之间存在良好的一致性,这表明它们在估计与暴风相关的严重损害方面具有实用性。此外,损失函数还能成功地重建极端风灾造成损失的地理模式,并具有高度的相关性。根据事件发生概率,本研究设计了一种损害分类器,该分类器在区分市级日常损害事件和非损害事件方面表现出一定的技巧。虽然大损失事件得到了很好的捕捉,但损失数据的偏度和零膨胀大大降低了中度和轻度损失事件的损失函数和分类器的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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