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Studies of the seasonal prediction of heavy late spring rainfall over southeastern China

机译：中国东南部重型春季降雨季节性预测研究

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摘要

The late spring rainfall may account for 15% of the annual total rainfall, which is crucial to early planting in southeastern China. A better understanding of the precipitation variations in the late spring and its predictability not only greatly increase our knowledge of related mechanisms, but it also benefits society and the economy. Four models participating in the North American Multi-Model Ensemble (NMME) were selected to study their abilities to forecast the late spring rainfall over southeastern China and the major sources of heavy rainfall from the perspective of the sea surface temperature (SST) field. We found that the models have better abilities to forecast the heavy rainfall over the middle and lower reaches of the Yangtze River region (MLYZR) with only a 1-month lead time, but they failed for a 3-month lead time since the occurrence of the heavy rainfall was inconsistent with the observations. The observations indicate that the warm SST anomalies in the tropical eastern Indian Ocean are vital to the simultaneously heavy rainfall in the MLYZR in May, but an El Nino event is not a necessary condition for determining the heavy rainfall over the MLYZR. The heavy rainfall over the MLYZR in May is always accompanied by warming of the northeastern Indian Ocean and of the northeastern South China Sea (NSCS) from April to May in the models and observations, respectively. In the models, El Nino events may promote the warming processes over the northeastern Indian Ocean, which leads to heavy rainfall in the MLYZR. However, in the real world, El Nino events are not the main reason for the warming of the NSCS, and further research on the causes of this warming is still needed.
机译：春季降雨可能占每年降雨量的15％，这对中国东南部的早期种植至关重要。更好地了解春季晚期的降水变化及其可预测性，而不仅大大提高了对相关机制的知识，而且还享有社会和经济。参加北美多模型集合（NMME）的四种模型被选中以研究他们预测中国东南部春季降雨的能力，以及从海面温度（SST）领域的角度来看的大雨的主要来源。我们发现，只有1个月的交易时间，这些模型可以预测长江地区（Mlyzr）的中下游的大雨降雨量，但由于发生了3个月的提前时间，他们失败了大雨降雨与观察结果不一致。观察结果表明，热带东部印度洋中的温暖SST异常对5月份的Mlyzr中同时降雨至关重要，但El Nino事件不是确定含量大雨降雨的必要条件。 Mlyzr的暴雨可能总是伴随着西北印度洋和东北南海（NSCS）的变暖，分别于4月至5月在模型和观察中。在模型中，El Nino活动可能会促进东北印度洋的变暖过程，这导致了Mlyzr的大雨。然而，在现实世界中，El Nino事件不是NSCs热身的主要原因，仍然需要进一步研究这种变暖的原因。

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  • 来源
    《Climate dynamics》 |2021年第8期|1919-1931|共13页
  • 作者

    Zhang Shouwen; Wang Hui; Jiang Hua; Ma Wentao;

  • 作者单位

    Natl Marine Environm Forecasting Ctr Dahuisi Rd 8 Beijing 100081 Peoples R China;

    Natl Marine Environm Forecasting Ctr Key Lab Res Marine Hazards Forecasting Beijing Peoples R China|Shandong Univ Inst Marine Sci & Technol Qingdao Shandong Peoples R China;

    Natl Marine Environm Forecasting Ctr Dahuisi Rd 8 Beijing 100081 Peoples R China|Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai Peoples R China;

    Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Seasonal forecasting; Precipitation; Late spring; SST teleconnection;

    机译：季节性预测;降水;春天;SST Teleconnection;

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