globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-15-0566.1
Scopus记录号: 2-s2.0-84974782890
论文题名:
Evaluating simulated fraction of attributable risk using climate observations
作者: Lott F.C.; Stott P.A.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2016
卷: 29, 期:12
起始页码: 4565
结束页码: 4575
语种: 英语
Scopus关键词: Climate change ; Climatology ; Error analysis ; Errors ; Estimation ; Forecasting ; Reliability ; Risk assessment ; Anthropogenic climate ; Attributable risks ; Climate observations ; Climate simulation ; Extreme events ; Forecast verification/skill ; Probabilistic forecasts ; Statistical techniques ; Climate models ; atmospheric structure ; climate change ; climate modeling ; climatology ; error analysis ; extreme event ; weather forecasting
英文摘要: Although it is critical to assess the accuracy of attribution studies, the fraction of attributable risk (FAR) cannot be directly assessed from observations since it involves the probability of an event in a world that did not happen, the "natural" world where there was no human influence on climate. Instead, reliability diagrams (usually used to compare probabilistic forecasts to the observed frequencies of events) have been used to assess climate simulations employed for attribution and by inference to evaluate the attribution study itself. The Brier score summarizes this assessment of a model by the reliability diagram. By constructing a modeling framework where the true FAR is already known, this paper shows that Brier scores are correlated to the accuracy of a climate model ensemble's calculation of FAR, although only weakly. This weakness exists because the diagram does not account for accuracy of simulations of the natural world. This is better represented by two reliability diagrams from early and late in the period of study, which would have, respectively, less and greater anthropogenic climate forcing. Two new methods are therefore proposed for assessing the accuracy of FAR, based on using the earlier observational period as a proxy for observations of the natural world. It is found that errors from model-based estimates of these observable quantities are strongly correlated with errors in the FAR estimated in the model framework. These methods thereby provide new observational estimates of the accuracy in FAR. © 2016 American Meteorological Society.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49905
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作者单位: Met Office Hadley Centre, Exeter, United Kingdom

Recommended Citation:
Lott F.C.,Stott P.A.. Evaluating simulated fraction of attributable risk using climate observations[J]. Journal of Climate,2016-01-01,29(12)
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