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Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

机译:利用太平洋和印度洋海表温度指数预测东非春季干旱

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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 stronger Walker 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 (r(cv) approximate to 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.
机译:在东非东部(埃塞俄比亚南部,肯尼亚东部和索马里南部地区),1999年,2000年,2004年,2007年,2008年,2009年和2011年的北方春季降雨(雨季长)降雨不足,造成了严重的粮食不安全和营养不良。在季节和十年时间框架内预测该地区的降雨不足,可以帮助决策者实施减少灾害风险的措施,同时指导气候智能适应和农业发展。基于最近的研究,该研究将印度太平洋太平洋暖池的变暖和西太平洋东西向海表温度(SST)梯度增加所导致的东非旱灾与更频繁的沃克环流联系起来,我们发现,东非北部春季春季降雨变化的两种主要模式分别与中西部太平洋和中部印度洋的海表温度波动有关。因此,可以使用两个SST指数-西太平洋梯度(WPG)和中部印度洋指数(CIO)来预测这两种降雨模式的变化,我们的统计预测显示出合理的交叉验证技巧(r(cv)大约为0.6) 。相反,当前的耦合预测模型在长雨中没有任何技巧。我们的SST指数似乎也反映了最近的大部分主要干旱事件,例如2000、2009和2011。基于这些简单指数的预测可用于支持区域预报工作和对地表数据进行同化,以帮助提供预警和指导气候展望。

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