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      Predictability of Chinese Summer Extreme Rainfall Based on Arctic Sea Ice and Tropical Sea Surface Temperature

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          Abstract

          Chinese summer extreme rainfall often brings huge economic losses, so the prediction of summer extreme rainfall is necessary. This study focuses on the predictability of the leading mode of Chinese summer extreme rainfall from empirical orthogonal function (EOF) analysis. The predictors used in this study are Arctic sea ice concentration (ASIC) and regional sea surface temperature (SST) in selected optimal time periods. The most important role that Arctic sea ice (ASI) plays in the appearance of EOF1 may be strengthening the high pressure over North China, thereby preventing water vapor from going north. The contribution of SST is mainly at low latitudes and characterized by a significant cyclone anomaly over South China. The forecast models using predictor ASIC (PA), SST (PS), and the two together (PAS) are established by using data from 1980 to 2004. An independent forecast is made for the last 11 years (2005–2015). The correlation coefficient (COR) skills between the observed and cross-validation reforecast principal components (PC) of the PA, PS, and PAS models are 0.47, 0.66, and 0.76, respectively. These values indicate that SST is a major cause of Chinese summer extreme rainfall during 1980–2004. The COR skill of the PA model during the independent forecast period of 2004–2015 is 0.7, which is significantly higher than those of the PS and PAS models. Thus, the main factor influencing Chinese summer extreme rainfall in recent years has changed from low latitudes to high latitudes. The impact of ASI on Chinese summer extreme rainfall is becoming increasingly significant.

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          Author and article information

          Journal
          JOUC
          Journal of Ocean University of China
          Science Press and Springer (China )
          1672-5182
          14 May 2019
          01 June 2019
          : 18
          : 3
          : 626-632
          Affiliations
          1 Shanghai Marine Meteorological Center, Shanghai 201306, China
          2 Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China
          3 Ningbo Collaborative Innovation Center of Nonlinear Harzard System of Ocean and Atmosphere, Ningbo University, Ningbo 315211, China
          Author notes
          *Corresponding author: HUANG Fei
          Article
          s11802-019-3886-6
          10.1007/s11802-019-3886-6
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

          Product
          Self URI (journal-page): https://www.springer.com/journal/11802

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