DOI: 10.5194/hess-18-4965-2014
Scopus记录号: 2-s2.0-84916613440
论文题名: Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices
作者: Funk C ; , Hoell A ; , Shukla S ; , Bladé I ; , Liebmann B ; , Roberts J ; B ; , Robertson F ; R ; , Husak G
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 12 起始页码: 4965
结束页码: 4978
语种: 英语
Scopus关键词: Atmospheric temperature
; Decision making
; Drought
; Forecasting
; Rain
; Risk assessment
; Submarine geophysics
; Surface properties
; Surface waters
; Agricultural development
; Current generation
; Disaster risk reductions
; Pacific warm pool
; Rainfall variability
; Regional forecasting
; Sea surface temperature (SST)
; Sea Surface Temperature gradients
; Oceanography
; climate prediction
; drought
; marine atmosphere
; rainfall
; sea surface temperature
; spring (season)
; Walker circulation
; warm pool
; Ethiopia
; Indian Ocean
; Kenya
; Pacific Ocean
; Somali
英文摘要: In eastern East Africa (the southern Ethiopia, eastern Kenya and southern Somalia region), poor boreal spring (long wet season) rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent East African droughts to a strongerWalker circulation, resulting from warming in the Indo-Pacific warm pool and an increased east-to-west sea surface temperature (SST) gradient in the western Pacific, we show that the two dominant modes of East African boreal spring rainfall variability are tied to SST fluctuations in the western central Pacific and central Indian Ocean, respectively. Variations in these two rainfall modes can thus be predicted using two SST indices - the western Pacific gradient (WPG) and central Indian Ocean index (CIO), with our statistical forecasts exhibiting reasonable cross-validated skill (rcv ≈ 0.6). In contrast, the current generation of coupled forecast models show no skill during the long rains. Our SST indices also appear to capture most of the major recent drought events such as 2000, 2009 and 2011. Predictions based on these simple indices can be used to support regional forecasting efforts and land surface data assimilations to help inform early warning and guide climate outlooks. © Author(s) 2014. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78049
Appears in Collections: 气候变化事实与影响
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作者单位: US Geological Survey, University of California Santa Barbara Geography, Santa Barbara, CA, United States; University of California Santa Barbara Geography, Santa Barbara, CA, United States; Universitat de Barcelona, Institut Català de Ciències del Clima, Barcelona, Spain; University of Colorado, NOAA Earth Systems Research Laboratory, Boulder, United States; NASA Marshall Space Flight Center, Huntsville, United States
Recommended Citation:
Funk C,, Hoell A,, Shukla S,et al. Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices[J]. Hydrology and Earth System Sciences,2014-01-01,18(12)