干旱气象 ›› 2024, Vol. 42 ›› Issue (2): 209-216.DOI: 10.11755/j.issn.1006-7639(2024)-02-0209

• 论文 • 上一篇    下一篇

中国降水对热带太平洋海温的滞后响应特征探讨

高志伟1,2(), 刘佳2,3, 陈艳2,4(), 钟爱华5   

  1. 1.大理国家气候观象台,云南 大理 671000
    2.中国气象局横断山区(低纬高原)灾害性天气研究中心,云南 昆明 650034
    3.云南省红河州气象局,云南 蒙自 661199
    4.云南省气象科学研究所,云南 昆明 650034
    5.云南省大理白族自治州气象局,云南 大理 671000
  • 收稿日期:2023-10-30 修回日期:2024-04-15 出版日期:2024-04-30 发布日期:2024-05-12
  • 通讯作者: 陈艳(1976—),女,云南通海人,正高级工程师,主要从事季风天气气候研究。E-mail: chenyan@cma.gov.cn
  • 作者简介:高志伟(1973—),男,云南大理人,正高级工程师,主要从事气象服务和应用气象工作。E-mail: dlzqxjgzw@126.com
  • 基金资助:
    云南省科技厅重点研发专项(202203AC100006);国家自然科学基金项目(41965005);云南省气象局高原湖泊生态气象服务创新团队项目(2022CX08);及中国气象科学研究院基本科研业务费专项基金项目(2023Z010)

Exploration of the hysteresis response characteristics of precipitation in China to tropical Pacific sea surface temperature

GAO Zhiwei1,2(), LIU Jia2,3, CHEN Yan2,4(), Zhong Aihua5   

  1. 1. Dali National Climate Observatory, Dali 671000, Yunnan, China
    2. Research Center for Disastrous Weathers over Hengduan Mountains & Low-Latitude Plateau, CMA, Kunming 650034, China
    3. Meteorological Bureau of Honghe Prefecture, Mengzi 661199, Yunnan, China
    4. Yunnan Institute of Meteorological Sciences, Kunming 650034, China
    5. Meteorological Bureau of Dali Bai Autonomous Prefecture, Dali 671000, Yunnan, China
  • Received:2023-10-30 Revised:2024-04-15 Online:2024-04-30 Published:2024-05-12

摘要:

研究热带太平洋海温与中国降水之间的关系对提升我国气候预测水平具有重要科学意义。基于长时间序列的中国160站逐月降水资料和美国气候预测中心(Climate Prediction Center,CPC)的逐月海温指数,采用一种新的滞后累积相关分析方法,研究中国降水对热带太平洋海温的滞后响应特征。结果表明:(1)该分析方法能够有效揭示前期海温异常累积效应对降水的影响,进而为筛选最优预测因子提供依据;(2)在Ni?o1+2、Ni?o3、Ni?o4和Ni?o3.4等海温指数中,前期Ni?o1+2指数与中国降水的相关性最显著,尤其是Ni?o1+2海温序列与滞后4个月的中国降水呈现最显著正相关,而Ni?o1+2累积2个月海温序列与滞后9个月的中国降水呈最显著负相关;(3)Ni?o1+2海温序列对中国季风区降水影响明显,其正反馈区主要集中在青藏高原东部和云南地区;(4)Ni?o1+2海温序列与滞后4个月的中国平均降水量的线性拟合分析显示,拟合得到的降水量变化趋势与实测降水量一致,冬春季拟合误差较小,夏秋季拟合误差较大。

关键词: 中国降水, 热带太平洋海温, 滞后累积相关系数

Abstract:

Examine the relationship between tropical Pacific sea surface temperature (SST) and precipitation in China has scientific significance for improving China's climate prediction level. Based on the long-term monthly rain gauge data of 160 stations in China and the monthly SST index from Climate Prediction Center (CPC), USA, this paper explores the response characteristics of precipitation in China to tropical Pacific SST changes through a new method of lag cumulative correlation. The results are as follows: (1) This method is able to reveal the cumulative effect of previous abnormal SST on the precipitation effectively, so as to provide a basis for selecting the optimal predictive factors. (2) Among Ni?o1+2, Ni?o3, Ni?o4, and Ni?o3.4 SST indices, previous Nino1+2 index has the most significant relationship with China’s precipitation. More precisely, the positive correlation between Ni?o1+2 timeseries and the 4-month lagged precipitation, and the negative link between 2-month cumulative Ni?o1+2 time series and the the 9-month lagged precipitation in China are most significant. (3) The Ni?o1+2 SST can distinctly influence the precipitation in China's monsoon regions, with the strongest positive feedback are as primarily locate in the eastern part of the Qinghai-Tibet Plateau and Yunnan Province. (4) The linear fitting between the Ni?o1+2 time series and the average precipitation of China with a lag of 4 months shows that the fluctuation trend of fitted precipitation is consistent with that of the rain gauge data, with relative small fitting errors in winter and spring and larger errors in summer and autumn.

Key words: precipitation in China, tropical Pacific SST, lag cumulative correlation coefficient

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