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    首頁 > 期刊 > 自然科學(xué)與工程技術(shù) > 基礎(chǔ)科學(xué) > 海洋學(xué) > 中國海洋大學(xué)學(xué)報·自然科學(xué)版 > Improvements in Long-Lead Prediction of Early-Summer Subtropical Frontal Rainfall Based on Arctic Sea Ice 【正文】

    Improvements in Long-Lead Prediction of Early-Summer Subtropical Frontal Rainfall Based on Arctic Sea Ice

    XING; Wen; HUANG; Fei Key; Laboratory; of; Physical; Oceanography; Ocean; University; of; China; Qingdao; 266100; China; Laboratory; for; Ocean; and; Climate; Dynamics; Pilot; National; Laboratory; for; Marine; Science; and; Technology; (Qingdao); Qingdao; 266100; China; Ningbo; Collaborative; Innovation; Center; of; Nonlinear; Harzard; System; of; Ocean; and; Atmosphere; Ningbo; University; Ningbo; 315211; China
    • east
    • asia
    • subtropical
    • frontal
    • rainfall

    摘要:Seasonal prediction of East Asia(EA) summer rainfall, especially with a longer-lead time, is in great demand, but still very challenging. The present study aims to make long-lead prediction of EA subtropical frontal rainfall(SFR) during early summer(May-June mean, MJ) by considering Arctic sea ice(ASI) variability as a new potential predictor. A MJ SFR index(SFRI), the leading principle component of the empirical orthogonal function(EOF) analysis applied to the MJ precipitation anomaly over EA, is defined as the predictand. Analysis of 38-year observations(1979-2016) revealed three physically consequential predictors. A stronger SFRI is preceded by dipolar ASI anomaly in the previous autumn, a sea level pressure(SLP) dipole in the Eurasian continent, and a sea surface temperature anomaly tripole pattern in the tropical Pacific in the previous winter. These precursors foreshadow an enhanced Okhotsk High, lower local SLP over EA, and a strengthened western Pacific subtropical high. These factors are controlling circulation features for a positive SFRI. A physical-empirical model was established to predict SFRI by combining the three predictors. Hindcasting was performed for the 1979-2016 period, which showed a hindcast prediction skill that was, unexpectedly, substantially higher than that of a four-dynamical models’ ensemble prediction for the 1979-2010 period(0.72 versus 0.47). Note that ASI variation is a new predictor compared with signals originating from the tropics to mid-latitudes. The long-lead hindcast skill was notably lower without the ASI signals included, implying the high practical value of ASI variation in terms of long-lead seasonal prediction of MJ EA rainfall.

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