DOI: 10.5194/cp-8-265-2012
Scopus记录号: 2-s2.0-84857704267
论文题名: Inferences on weather extremes and weather-related disasters: A review of statistical methods
作者: Visser H. ; Petersen A.C.
刊名: Climate of the Past
ISSN: 18149324
出版年: 2012
卷: 8, 期: 1 起始页码: 265
结束页码: 286
语种: 英语
Scopus关键词: anthropogenic effect
; climate change
; climate modeling
; data set
; database
; disaster
; extreme event
; literature review
; probability density function
; reconstruction
; tree ring
; uncertainty analysis
英文摘要: The study of weather extremes and their impacts, such as weather-related disasters, plays an important role in research of climate change. Due to the great societal consequences of extremes - historically, now and in the future - the peer-reviewed literature on this theme has been growing enormously since the 1980s. Data sources have a wide origin, from century-long climate reconstructions from tree rings to relatively short (30 to 60 yr) databases with disaster statistics and human impacts. When scanning peer-reviewed literature on weather extremes and its impacts, it is noticeable that many different methods are used to make inferences. However, discussions on these methods are rare. Such discussions are important since a particular methodological choice might substantially influence the inferences made. A calculation of a return period of once in 500 yr, based on a normal distribution will deviate from that based on a Gumbel distribution. And the particular choice between a linear or a flexible trend model might influence inferences as well. In this article, a concise overview of statistical methods applied in the field of weather extremes and weather-related disasters is given. Methods have been evaluated as to stationarity assumptions, the choice for specific probability density functions (PDFs) and the availability of uncertainty information. As for stationarity assumptions, the outcome was that good testing is essential. Inferences on extremes may be wrong if data are assumed stationary while they are not. The same holds for the block-stationarity assumption. As for PDF choices it was found that often more than one PDF shape fits to the same data. From a simulation study the conclusion can be drawn that both the generalized extreme value (GEV) distribution and the log-normal PDF fit very well to a variety of indicators. The application of the normal and Gumbel distributions is more limited. As for uncertainty, it is advisable to test conclusions on extremes for assumptions underlying the modelling approach. Finally, it can be concluded that the coupling of individual extremes or disasters to climate change should be avoided. © Author(s) 2012. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49619
Appears in Collections: 气候变化与战略
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Recommended Citation:
Visser H.,Petersen A.C.. Inferences on weather extremes and weather-related disasters: A review of statistical methods[J]. Climate of the Past,2012-01-01,8(1)