| DOI: | 10.1175/JCLI-D-15-0020.1
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| Scopus记录号: | 2-s2.0-84950132447
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| 论文题名: | Need for caution in interpreting extreme weather statistics |
| 作者: | Sardeshmukh P.D.; Compo G.P.; Penland C.
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| 刊名: | Journal of Climate
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| ISSN: | 8948755
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| 出版年: | 2015
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| 卷: | 28, 期:23 | | 起始页码: | 9166
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| 结束页码: | 9187
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| 语种: | 英语
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| Scopus关键词: | Atmospheric pressure
; Atmospheric structure
; Financial data processing
; Gaussian distribution
; Gaussian noise (electronic)
; Global warming
; Markov processes
; Rain
; Risk assessment
; Stochastic systems
; Atmospheric circulation
; Extreme events
; North Atlantic oscillations
; North Pacific
; Statistical techniques
; Probability distributions
; anthropogenic effect
; climate change
; extreme event
; global warming
; Markov chain
; numerical model
; probability
; skewness
; statistical analysis
; Atlantic Ocean
; Atlantic Ocean (North)
; Pacific Ocean
; Pacific Ocean (North)
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| 英文摘要: | Given the reality of anthropogenic global warming, it is tempting to seek an anthropogenic component in any recent change in the statistics of extreme weather. This paper cautions that such efforts may, however, lead to wrong conclusions if the distinctively skewed and heavy-tailed aspects of the probability distributions of daily weather anomalies are ignored or misrepresented. Departures of several standard deviations from the mean, although rare, are far more common in such a distinctively non-Gaussian world than they are in a Gaussian world. This further complicates the problem of detecting changes in tail probabilities from historical records of limited length and accuracy. Apossible solution is to exploit the fact that the salient non-Gaussian features of the observed distributions are captured by so-called stochastically generated skewed (SGS) distributions that include Gaussian distributions as special cases. SGS distributions are associated with damped linear Markov processes perturbed by asymmetric stochastic noise and as such represent the simplest physically based prototypes of the observed distributions. The tails of SGS distributions can also be directly linked to generalized extreme value (GEV) and generalized Pareto (GP) distributions. The Markov process model can be used to provide rigorous confidence intervals and to investigate temporal persistence statistics. The procedure is illustrated for assessing changes in the observed distributions of daily wintertime indices of large-scale atmospheric variability in the North Atlantic and North Pacific sectors over the period 1872-2011. No significant changes in these indices are found from the first to the second half of the period. © 2015 American Meteorological Society. |
| 资助项目: | ORNL, Oak Ridge National Laboratory
; SC, Oak Ridge National Laboratory
; SC, Oak Ridge National Laboratory
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| Citation statistics: |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/50428
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| Appears in Collections: | 气候变化事实与影响
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作者单位: | CIRES, University of Colorado, Boulder, CO, United States; NOAA/Earth System Research Laboratory, Boulder, CO, United States
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| Recommended Citation: | |
Sardeshmukh P.D.,Compo G.P.,Penland C.. Need for caution in interpreting extreme weather statistics[J]. Journal of Climate,2015-01-01,28(23)
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