欧洲的风灾损失--从损失数据集中获得什么

IF 6.1 1区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Julia Moemken , Gabriele Messori , Joaquim G. Pinto
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引用次数: 0

摘要

风灾是影响西欧和中欧最严重的自然灾害之一。相关影响和损失的信息对于风险评估以及制定适应和缓解战略至关重要。在这项研究中,我们比较了属于三个类别的五个数据集所报告和估计的风灾损失:气象和保险综合指数、自然灾害数据库和保险公司的损失报告。我们分析了 21 个欧洲国家在 1999 年 10 月至 2022 年 3 月期间报告的事件、每个数据集的风暴数量以及特定风暴事件的排名等方面数据集之间的异同。共记录了 94 个单独的暴风事件。其中只有 11 次在所有五个数据集中都有报告,而绝大多数(约 60%)仅在单个数据集中有记录。结果显示,不同数据集的风暴总数是不同的,尽管气象指数的风暴总数是先验固定的。此外,各数据集在每个冬季的风暴频率上也经常存在分歧。此外,各数据集根据报告/估计损失对风暴的排序也不尽相同。不过,如果根据不同数据集中常见的风暴事件来计算排序,这些差异就会减小。这些结果在欧洲和国家层面的损失汇总中基本成立。总体而言,这些数据集对风灾影响提供了不同的看法。因此,为避免得出误导性结论,我们没有将任何数据集作为 "基本事实",而是将所有数据集一视同仁。我们建议,可以利用这些不同的观点来测试哪些特征与校准特定地区的暴风模型相关。此外,它还能让用户为风灾损失指定一个不确定性范围。我们的结论是,不同数据集的组合对于获得与风灾相关影响的代表性图景至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Windstorm losses in Europe – What to gain from damage datasets

Windstorm losses in Europe – What to gain from damage datasets

Windstorms are among the most impacting natural hazards affecting Western and Central Europe. Information on the associated impacts and losses are essential for risk assessment and the development of adaptation and mitigation strategies. In this study, we compare reported and estimated windstorm losses from five datasets belonging to three categories: Indices combining meteorological and insurance aspects, natural hazard databases, and loss reports from insurance companies. We analyse the similarities and differences between the datasets in terms of reported events, the number of storms per dataset and the ranking of specific storm events for the period October 1999 to March 2022 across 21 European countries. A total of 94 individual windstorms were documented. Only 11 of them were reported in all five datasets, while the large majority (roughly 60%) was solely recorded in single datasets. Results show that the total number of storms is different in the various datasets, although for the meteorological indices such number is fixed a priori. Additionally, the datasets often disagree on the storm frequency per winter season. Moreover, the ranking of storms based on reported/estimated losses varies in the datasets. However, these differences are reduced when the ranking is calculated relative to storm events that are common in the various datasets. The results generally hold for losses aggregated at European and at country level. Overall, the datasets provide different views on windstorm impacts. Thus, to avoid misleading conclusions, we use no dataset as “ground truth” but treat all of them as equal. We suggest that these different views can be used to test which features are relevant for calibrating windstorm models in specific regions. Furthermore, it could enable users to assign an uncertainty range to windstorm losses. We conclude that a combination of different datasets is crucial to obtain a representative picture of windstorm associated impacts.

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来源期刊
Weather and Climate Extremes
Weather and Climate Extremes Earth and Planetary Sciences-Atmospheric Science
CiteScore
11.00
自引率
7.50%
发文量
102
审稿时长
33 weeks
期刊介绍: Weather and Climate Extremes Target Audience: Academics Decision makers International development agencies Non-governmental organizations (NGOs) Civil society Focus Areas: Research in weather and climate extremes Monitoring and early warning systems Assessment of vulnerability and impacts Developing and implementing intervention policies Effective risk management and adaptation practices Engagement of local communities in adopting coping strategies Information and communication strategies tailored to local and regional needs and circumstances
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