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Rethinking Indian monsoon rainfall prediction in the context of recent global warming

机译:在全球变暖背景下对印度季风降雨的预测进行反思

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摘要

Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989-2012) have little skill. Here we show, with both dynamical and physical-empirical models, that this recent failure is largely due to the models' inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP-ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical-empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989-2012 and a 92-year retrospective forecast skill of 0.64 for 1921-2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP-ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.
机译:印度夏季风降雨量(ISMR)的预测是热带气候预测的核心。尽管自1886年以来在预测ISMR方面已取得了巨大进展,但最近几十年(1989-2012年)的运行预测几乎没有技巧。在这里,我们通过动力学和物理经验模型都表明,这种近期的失败很大程度上是由于这些模型无法捕获在最近的全球变暖(即中太平洋太平洋爱妮诺南部地区)的发展过程中出现的新的可预测性来源。震荡(CP-ENSO),亚洲低气压的快速加深以及北方春季南北太平洋高点的加强。捕获这些新预测变量的物理经验模型可以得出1989-2012年的独立预测技能为0.51,1921-2012年的92年回顾性预测技能为0.64。动力学模型的最新低技能归因于捕获发展中的CP-ENSO和异常亚洲低气压的缺陷。结果表明,ISMR预测技能和可预测性之间存在相当大的差距。

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