Assessment of wind–damage relations for Norway using 36 years of daily insurance data
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 da...
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Online Access: | https://doi.org/10.5194/nhess-24-1341-2024 https://nhess.copernicus.org/articles/24/1341/2024/ |
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ftcopernicus:oai:publications.copernicus.org:nhess115988 2024-09-15T18:23:51+00:00 Assessment of wind–damage relations for Norway using 36 years of daily insurance data Jaison, Ashbin Sorteberg, Asgeir Michel, Clio Breivik, Øyvind 2024-04-23 application/pdf https://doi.org/10.5194/nhess-24-1341-2024 https://nhess.copernicus.org/articles/24/1341/2024/ eng eng doi:10.5194/nhess-24-1341-2024 https://nhess.copernicus.org/articles/24/1341/2024/ eISSN: 1684-9981 Text 2024 ftcopernicus https://doi.org/10.5194/nhess-24-1341-2024 2024-08-28T05:24:15Z 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. Text North Atlantic Copernicus Publications: E-Journals Natural Hazards and Earth System Sciences 24 4 1341 1355 |
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Copernicus Publications: E-Journals |
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English |
description |
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. |
format |
Text |
author |
Jaison, Ashbin Sorteberg, Asgeir Michel, Clio Breivik, Øyvind |
spellingShingle |
Jaison, Ashbin Sorteberg, Asgeir Michel, Clio Breivik, Øyvind Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
author_facet |
Jaison, Ashbin Sorteberg, Asgeir Michel, Clio Breivik, Øyvind |
author_sort |
Jaison, Ashbin |
title |
Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
title_short |
Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
title_full |
Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
title_fullStr |
Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
title_full_unstemmed |
Assessment of wind–damage relations for Norway using 36 years of daily insurance data |
title_sort |
assessment of wind–damage relations for norway using 36 years of daily insurance data |
publishDate |
2024 |
url |
https://doi.org/10.5194/nhess-24-1341-2024 https://nhess.copernicus.org/articles/24/1341/2024/ |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
eISSN: 1684-9981 |
op_relation |
doi:10.5194/nhess-24-1341-2024 https://nhess.copernicus.org/articles/24/1341/2024/ |
op_doi |
https://doi.org/10.5194/nhess-24-1341-2024 |
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Natural Hazards and Earth System Sciences |
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24 |
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4 |
container_start_page |
1341 |
op_container_end_page |
1355 |
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1810464129106837504 |