| 项目编号: | 1349827
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| 项目名称: | CAREER: Temporal Clustering of Hydrometeorological Extremes |
| 作者: | Gabriele Villarini
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| 承担单位: | University of Iowa
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| 批准年: | 2013
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| 开始日期: | 2014-05-01
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| 结束日期: | 2019-04-30
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| 资助金额: | USD508405
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Geosciences - Atmospheric and Geospace Sciences
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| 英文关键词: | temporal clustering
; extreme event
; extreme hydrometeorological event
; low temperature extreme
; career proposal
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| 英文摘要: | The main goal of this CAREER proposal is to examine whether extreme hydrometeorological events cluster in time. Temporal clustering refers to the tendency of events to occur together in time, with the occurrence of an extreme event affecting the likelihood of a subsequent event. The proposed work is delineated in three phases, with research motivated by the following main questions: Do extreme hydrometeorological events exhibit temporal clustering, and, if so, which key physical processes explain this behavior? Can outputs from General Circulation Models (GCMs) reproduce observed clustered behavior? Is it possible to take advantage of temporal clustering to improve the forecasting of hydrometeorological extreme events? The underlying hypothesis is that extreme hydrometeorological events exhibit temporal clustering that is controlled by climate processes.
The continental United States will be the focus as this area is plagued by a large array of natural hazards yielding extensive socio-economic impacts. Some of the most damaging hazards in this general area will be included: flooding and heavy rainfall, high and low temperature extremes, and tropical and extra-tropical storms. Cox regression models will be developed to examine the dependence of extreme events on climate processes. The methodologies build on analysis tools and data sets that the PI has used extensively.
This research represents a comprehensive step forward in the understanding of the frequency and causes of extreme events; this has substantial broader impacts. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/96935
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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| Recommended Citation: | |
Gabriele Villarini. CAREER: Temporal Clustering of Hydrometeorological Extremes. 2013-01-01.
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