DOI: 10.1175/JCLI-D-12-00357.1
Scopus记录号: 2-s2.0-84877823593
论文题名: Extracting subseasonal scenarios: An alternative method to analyze seasonal predictability of regional-scale tropical rainfall
作者: Moron V. ; Camberlin P. ; Robertson A.W.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 8 起始页码: 2580
结束页码: 2600
语种: 英语
Scopus关键词: Alternative methods
; Empirical Orthogonal Function
; Interannual variability
; Sea surface temperature anomalies
; Seasonal prediction
; Seasonal rainfall
; Temporal summation
; Weather variability
; Atmospheric temperature
; Climate change
; Fuzzy filters
; Rain
; accuracy assessment
; climatology
; fuzzy mathematics
; prediction
; rainfall
; regional climate
; sea surface temperature
; seasonal variation
; temperature anomaly
; weather forecasting
; Kenya
; Tanzania
英文摘要: Current seasonal prediction of rainfall typically focuses on 3-month rainfall totals at regional scale. This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall. This approach may hide potentially predictable signals when rainfall is lower: for example, near the onset or cessation of the rainy season. The authors illustrate such a case for the East African long rains (March-May) on a network of 36 stations in Kenya and north Tanzania from 1961 to 2001. Spatial coherence and potential predictability of seasonal rainfall anomalies associated with tropical sea surface temperature (SST) anomalies clearly peak during the early stage of the rainy season (in March), while the largest rainfall (in April and May) is far less spatially coherent; the latter is shown to contain a large noise component at the station scale that characterizes interannual variability of the March-May seasonal total amounts. Combining the empirical orthogonal function of both interannual and subseasonal variations with a fuzzy k-means clustering is shown to capture the most spatially coherent subseasonal "scenarios"that tend to filter out the noisier variations of the rainfall field and emphasize the most consistent signals in both time and space. This approach is shown to provide insight into the seasonal predictability of long dry spells and heavy daily rainfall events at local scale and their subseasonal modulation. © 2013 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51878
Appears in Collections: 气候变化事实与影响
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作者单位: Aix-Marseille Université, CEREGE UM 34 CNRS, Aix en Provence, France; International Research Institute for Climate and Society, Columbia University, Palisades, New York, United States; Biogéosciences, Centre de Recherches de Climatologie, Université de Bourgogne, Dijon, France
Recommended Citation:
Moron V.,Camberlin P.,Robertson A.W.. Extracting subseasonal scenarios: An alternative method to analyze seasonal predictability of regional-scale tropical rainfall[J]. Journal of Climate,2013-01-01,26(8)