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Asymmetry of probabilistic prediction skills of the midsummer surface air temperature over the middle and lower reach of the Yangtze River valley
Climate Dynamics ( IF 3.8 ) Pub Date : 2021-07-04 , DOI: 10.1007/s00382-021-05866-x
Shankai Tang 1 , Taichen Feng 1 , Yu Wang 1 , Guolin Feng 1, 2, 3, 4 , Shaobo Qiao 3, 5 , Yang Yang 5 , Zhisen Zhang 6
Affiliation  

Using the prediction data from the Global Seasonal Forecast version 5 (GloSea5) during the 1993–2016 period, the probabilistic prediction skills of the midsummer (July and August) surface air temperature (SAT) over the middle and lower reach of the Yangtze River valley (MLYR) are evaluated by the ranked probabilistic skill score. We found that the GloSea5 better predicts below-normal (BN) events than above-normal (AN) events at a long lead time, as well as the associated western Pacific subtropical high (WPSH) and circumglobal teleconnection (CGT) anomaly. This result reveals the asymmetry of the probabilistic prediction skills of the midsummer MLYR SAT, which is related to the asymmetric effect of predictability sources: the warm midsummer ENSO favors BN events via promoting the eastward retreat of the WPSH, whereas the cold midsummer ENSO exhibits weak effect on AN events due to the induced southwestward expansion of the WPSH; the warm mid-latitude North Atlantic (MNA) promotes AN events via projecting its influence onto the atmospheric teleconnections such as the CGT, but not vice versa. The GloSea5 exhibits strong response to both two predictability sources, but fails to reproduce the asymmetric effect of predictability sources especially for ENSO, which limits the prediction skills of AN events. On the other hand, the worse (better) simulations of the warm MNA (warm midsummer ENSO) lead to the lower (higher) prediction skills of AN (BN) events. These results are useful for better understanding the predictability of the midsummer SAT over the MLYR.



中文翻译:

长江中下游地区盛夏地表气温概率预测技术的不对称性

利用1993-2016年全球季节预报第5版(GloSea5)的预测数据,对长江流域中下游地区盛夏(7-8月)地表气温(SAT)的概率预测技术(MLYR) 通过排名的概率技能分数进行评估。我们发现 GloSea5 在较长的提前期能更好地预测低于正常 (BN) 的事件,而不是高于正常 (AN) 的事件,以及相关的西太平洋副热带高压 (WPSH) 和环地球遥相关 (CGT) 异常。这一结果揭示了仲夏 MLYR SAT 概率预报技巧的不对称性,这与可预报源的不对称效应有关:温暖的仲夏 ENSO 通过促进副高东退有利于 BN 事件,而寒冷的仲夏ENSO由于诱导副高向西南扩张而对AN事件的影响较弱;温暖的中纬度北大西洋 (MNA) 通过将其影响投射到大气遥相关(如 CGT)来促进 AN 事件,但反之则不然。GloSea5 对两种可预报源均表现出强烈响应,但未能再现可预报源的非对称效应,尤其是对 ENSO 而言,这限制了 AN 事件的预测技能。另一方面,暖 MNA(暖仲夏 ENSO)的更差(更好)模拟导致 AN(BN)事件的预测技能较低(较高)。这些结果有助于更好地理解仲夏 SAT 对 MLYR 的可预测性。温暖的中纬度北大西洋 (MNA) 通过将其影响投射到大气遥相关(如 CGT)来促进 AN 事件,但反之则不然。GloSea5 对两种可预报源均表现出强烈响应,但未能再现可预报源的非对称效应,尤其是对 ENSO 而言,这限制了 AN 事件的预测技能。另一方面,暖 MNA(暖仲夏 ENSO)的更差(更好)模拟导致 AN(BN)事件的预测技能较低(较高)。这些结果有助于更好地理解仲夏 SAT 对 MLYR 的可预测性。温暖的中纬度北大西洋 (MNA) 通过将其影响投射到大气遥相关(如 CGT)来促进 AN 事件,但反之则不然。GloSea5 对两种可预报源均表现出强烈响应,但未能再现可预报源的非对称效应,尤其是对 ENSO 而言,这限制了 AN 事件的预测技能。另一方面,暖 MNA(暖仲夏 ENSO)的更差(更好)模拟导致 AN(BN)事件的预测技能较低(较高)。这些结果有助于更好地理解仲夏 SAT 对 MLYR 的可预测性。但未能重现可预测性来源的非对称效应,尤其是对 ENSO 而言,这限制了 AN 事件的预测技能。另一方面,暖 MNA(暖仲夏 ENSO)的更差(更好)模拟导致 AN(BN)事件的预测技能较低(较高)。这些结果有助于更好地理解仲夏 SAT 对 MLYR 的可预测性。但未能重现可预测性来源的非对称效应,尤其是对 ENSO 而言,这限制了 AN 事件的预测技能。另一方面,暖 MNA(暖仲夏 ENSO)的更差(更好)模拟导致 AN(BN)事件的预测技能较低(较高)。这些结果有助于更好地理解仲夏 SAT 对 MLYR 的可预测性。

更新日期:2021-07-04
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