Can losses caused by wind storms be predicted from meteorological observations
(2001) In Scandinavian Actuarial Journal 2001(2). p.162-175- Abstract
- This paper contains a study of the extent to which aggregate losses due to severe wind storms can be explained by wind measurements. The analysis is based on 12 years of data for a region, Ska § ne, in southern Sweden. A previous investigation indicated that wind measurements from six recording stations in Ska § ne was insufficient to obtain accurate prediction. The present study instead uses geostrophic winds calculated from pressure readings, at a regular grid of size 50 kilometres over Ska § ne. However, also this meteorological data set is seen to be insufficient for accurate prediction of insurance risk. The results indicate that currently popular methods of evaluating wind storm risks from meteorological data should not be used... (More)
- This paper contains a study of the extent to which aggregate losses due to severe wind storms can be explained by wind measurements. The analysis is based on 12 years of data for a region, Ska § ne, in southern Sweden. A previous investigation indicated that wind measurements from six recording stations in Ska § ne was insufficient to obtain accurate prediction. The present study instead uses geostrophic winds calculated from pressure readings, at a regular grid of size 50 kilometres over Ska § ne. However, also this meteorological data set is seen to be insufficient for accurate prediction of insurance risk. The results indicate that currently popular methods of evaluating wind storm risks from meteorological data should not be used uncritically by insurers or reinsurers. Nevertheless, wind data does contain some information on insurance. risks. There is a need for further research on how to use this information to improve risk assessment. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c9885185-39fb-4820-9108-8ed032fd714c
- author
- Rootzén, Holger
LU
and Tajvidi, Nader
LU
- organization
- publishing date
- 2001
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Wind Storm Claims, Meteorological Prediction, Geostrophic Winds
- in
- Scandinavian Actuarial Journal
- volume
- 2001
- issue
- 2
- pages
- 14 pages
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:24244460165
- ISSN
- 0346-1238
- DOI
- 10.1080/03461230152592791
- language
- English
- LU publication?
- yes
- id
- c9885185-39fb-4820-9108-8ed032fd714c
- date added to LUP
- 2018-03-16 16:26:59
- date last changed
- 2022-01-31 02:24:51
@article{c9885185-39fb-4820-9108-8ed032fd714c, abstract = {{This paper contains a study of the extent to which aggregate losses due to severe wind storms can be explained by wind measurements. The analysis is based on 12 years of data for a region, Ska § ne, in southern Sweden. A previous investigation indicated that wind measurements from six recording stations in Ska § ne was insufficient to obtain accurate prediction. The present study instead uses geostrophic winds calculated from pressure readings, at a regular grid of size 50 kilometres over Ska § ne. However, also this meteorological data set is seen to be insufficient for accurate prediction of insurance risk. The results indicate that currently popular methods of evaluating wind storm risks from meteorological data should not be used uncritically by insurers or reinsurers. Nevertheless, wind data does contain some information on insurance. risks. There is a need for further research on how to use this information to improve risk assessment.}}, author = {{Rootzén, Holger and Tajvidi, Nader}}, issn = {{0346-1238}}, keywords = {{Wind Storm Claims; Meteorological Prediction; Geostrophic Winds}}, language = {{eng}}, number = {{2}}, pages = {{162--175}}, publisher = {{Taylor & Francis}}, series = {{Scandinavian Actuarial Journal}}, title = {{Can losses caused by wind storms be predicted from meteorological observations}}, url = {{http://dx.doi.org/10.1080/03461230152592791}}, doi = {{10.1080/03461230152592791}}, volume = {{2001}}, year = {{2001}}, }