Advanced

Extreme value modelling of storm damage in Swedish forests

Bengtsson, Anders LU and Nilsson, Carin LU (2007) In Natural Hazards and Earth System Sciences 7(5). p.515-521
Abstract
Forests cover about 56% of the land area in Sweden and forest damage due to strong winds has been a recurring problem. In this paper we analyse recorded storm damage in Swedish forests for the years 1965-2007. During the period 48 individual storm events with a total damage of 164 Mm(3) have been reported with the severe storm on 8 to 9 January 2005, as the worst with 70 Mm(3) damaged forest. For the analysis, storm damage data has been normalised to account for the increase in total forest volume over the period. We show that, within the framework of statistical extreme value theory, a Poisson point process model can be used to describe these storm damage events. Damage data supports a heavy-tailed distribution with great variability in... (More)
Forests cover about 56% of the land area in Sweden and forest damage due to strong winds has been a recurring problem. In this paper we analyse recorded storm damage in Swedish forests for the years 1965-2007. During the period 48 individual storm events with a total damage of 164 Mm(3) have been reported with the severe storm on 8 to 9 January 2005, as the worst with 70 Mm(3) damaged forest. For the analysis, storm damage data has been normalised to account for the increase in total forest volume over the period. We show that, within the framework of statistical extreme value theory, a Poisson point process model can be used to describe these storm damage events. Damage data supports a heavy-tailed distribution with great variability in damage for the worst storm events. According to the model, and in view of available data, the return period for a storm with damage in size of the severe storm of January 2005 is approximately 80 years, i.e. a storm with damage of this magnitude will happen, on average, once every eighty years. To investigate a possible temporal trend, models with time-dependent parameters have been analysed but give no conclusive evidence of an increasing trend in the normalised storm damage data for the period. Using a non-parametric approach with a kernel based local-likelihood method gives the same result. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Natural Hazards and Earth System Sciences
volume
7
issue
5
pages
515 - 521
publisher
Copernicus Gesellschaft Mbh
external identifiers
  • wos:000250554000003
ISSN
1684-9981
language
English
LU publication?
yes
id
bc8fe9d0-0bc2-4b64-96e0-f71ad0b3e431 (old id 653058)
alternative location
http://www.nat-hazards-earth-syst-sci.net/7/515/2007/nhess-7-515-2007.pdf
date added to LUP
2007-12-07 15:17:54
date last changed
2016-04-15 19:47:55
@article{bc8fe9d0-0bc2-4b64-96e0-f71ad0b3e431,
  abstract     = {Forests cover about 56% of the land area in Sweden and forest damage due to strong winds has been a recurring problem. In this paper we analyse recorded storm damage in Swedish forests for the years 1965-2007. During the period 48 individual storm events with a total damage of 164 Mm(3) have been reported with the severe storm on 8 to 9 January 2005, as the worst with 70 Mm(3) damaged forest. For the analysis, storm damage data has been normalised to account for the increase in total forest volume over the period. We show that, within the framework of statistical extreme value theory, a Poisson point process model can be used to describe these storm damage events. Damage data supports a heavy-tailed distribution with great variability in damage for the worst storm events. According to the model, and in view of available data, the return period for a storm with damage in size of the severe storm of January 2005 is approximately 80 years, i.e. a storm with damage of this magnitude will happen, on average, once every eighty years. To investigate a possible temporal trend, models with time-dependent parameters have been analysed but give no conclusive evidence of an increasing trend in the normalised storm damage data for the period. Using a non-parametric approach with a kernel based local-likelihood method gives the same result.},
  author       = {Bengtsson, Anders and Nilsson, Carin},
  issn         = {1684-9981},
  language     = {eng},
  number       = {5},
  pages        = {515--521},
  publisher    = {Copernicus Gesellschaft Mbh},
  series       = {Natural Hazards and Earth System Sciences},
  title        = {Extreme value modelling of storm damage in Swedish forests},
  volume       = {7},
  year         = {2007},
}