| DOI: | 10.1175/JCLI-D-11-00359.1
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| Scopus记录号: | 2-s2.0-84867669242
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| 论文题名: | Large-scale diagnostics of tropical cyclogenesis potential using environment variability metrics and logistic regression models |
| 作者: | Waters J.J.; Evans J.L.; Forest C.E.
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| 刊名: | Journal of Climate
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| ISSN: | 8948755
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| 出版年: | 2012
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| 卷: | 25, 期:18 | | 起始页码: | 6092
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| 结束页码: | 6107
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| 语种: | 英语
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| Scopus关键词: | Activity-based
; Climate variability
; Dynamic fields
; Dynamic variability
; Ensemble members
; Environmental factors
; Environmental variables
; European centre for medium-range weather forecasts
; High frequency HF
; Hit rate
; Logistic models
; Logistic regression models
; North Atlantic
; Poisson regression models
; Potential indicators
; Principal components analysis
; Reanalysis
; Seasonality
; Temporal variability
; Tropical cyclogenesis
; Variability information
; Climate change
; Logistics
; Poisson distribution
; Principal component analysis
; Risk assessment
; Tropics
; Weather forecasting
; Regression analysis
; climate change
; climate modeling
; climate variation
; cyclogenesis
; ensemble forecasting
; general circulation model
; hurricane
; principal component analysis
; regression analysis
; risk assessment
; temporal variation
; typhoon
; variance analysis
; weather forecasting
; Atlantic Ocean
; Atlantic Ocean (North)
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| 英文摘要: | The authors propose that inclusion of medium- to high-frequency variability information will provide improved metrics of tropical cyclogenesis (TCG) applicable to climate GCM diagnostics. Capabilities of the CommunityAtmosphereModel version 3.1 (CAM3.1)GCMare assessed for detecting both large-scale and localized conditions for TCG in the tropical North Atlantic by comparison with the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) and observed TCG occurrences. CAM3.1 seasonality of large-scale environmental factors conducive to TCG compares favorably with the ERA-40. It is determined that most of the TCG-related high-frequency temporal variability in the ERA-40 is explained by dynamic variability; each of the CAM3.1 ensemble members has lower variability in these dynamic fields. Seventeen environmental variables are evaluated as potential indicators of TCG activity based on daily anomalous variability with respect to a 15-day base period. Principal component analysis (PCA) is employed to synthesize these into a set of uncorrelated parameters. ERA-40 PCA composite variables are used to develop logistic and Poisson regression models for TCG detection and frequency in the North Atlantic main development region. Some skill metrics for the logistic model are promising, but the threat score and hit rate signify that further development of the logistic regression model is warranted; results from the Poisson regression model based on the same inputs are weaker, implying that weighting by TCG counts does not improve the results. These findings indicate merit in incorporating medium- to highfrequency variability in TCG metrics for diagnostics of seasonal activity and for application to climate models. © 2012 American Meteorological Society. |
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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/52271
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| Appears in Collections: | 气候变化事实与影响
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作者单位: | The Pennsylvania State University, University Park, PA, United States
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| Recommended Citation: | |
Waters J.J.,Evans J.L.,Forest C.E.. Large-scale diagnostics of tropical cyclogenesis potential using environment variability metrics and logistic regression models[J]. Journal of Climate,2012-01-01,25(18)
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