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Explaining and forecasting interannual variability in the flow of the Nile River

机译:解释和预测尼罗河流量的年际变化

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This study analyzes extensive data sets collected during the twentieth century and defines four modes of natural variability in the flow of the Nile River, identifying a new significant potential for improving predictability of floods and droughts. Previous studies have identified a significant teleconnection between the Nile flow and the eastern Pacific Ocean. El Nino-Southern Oscillation (ENSO) explains about 25% of the interannual variability in the Nile flow. Here, this study identifies a region in the southern Indian Ocean, with a similarly strong teleconnection to the Nile flow. Sea surface temperature (SST) in the region (50-80A degrees E and 25-35A degrees S) explains 28% of the interannual variability in the flow of the Nile River and, when combined with the ENSO index, the explained variability of the flow of the Nile River increases to 44%. In addition, during those years with anomalous SST conditions in both oceans, this study estimates that indices of the SSTs in the Pacific and Indian oceans can collectively explain up to 84% of the interannual variability in the flow of the Nile. Building on these findings, this study uses the classical Bayesian theorem to develop a new hybrid forecasting algorithm that predicts the Nile flow based on global model predictions of indices of the SST in the eastern Pacific and southern Indian oceans.
机译:这项研究分析了20世纪收集的大量数据集,并定义了尼罗河流量的四种自然变化模式,从而确定了提高洪水和干旱可预测性的新的重大潜力。先前的研究已经确定了尼罗河水流与东太平洋之间的显着遥相关。 El Nino-Southern Oscillation(ENSO)解释了尼罗河流量中约25%的年际变化。在这里,这项研究确定了印度洋南部的一个区域,与尼罗河流具有类似的强遥相关性。该地区(东经50-80A和南经25-35A)的海表温度(SST)解释了尼罗河流量年际变化的28%,当与ENSO指数结合使用时,其解释的变化尼罗河的流量增加到44%。此外,在这两个海洋中海温异常的年份,这项研究估计太平洋和印度洋海温的指数可以共同解释尼罗河流量年际变化的84%。基于这些发现,本研究使用经典贝叶斯定理开发了一种新的混合预测算法,该算法基于东太平洋和印度洋南部海表温度指数的全球模型预测来预测尼罗河流量。

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