主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

气象与环境学报 ›› 2024, Vol. 40 ›› Issue (4): 37-45.doi: 10.3969/j.issn.1673-503X.2024.04.005

• 论文 • 上一篇    下一篇

2022年5月江西省降水量气候趋势预测评估分析

刘雅楠1(),吴琼2,*(),李勇2   

  1. 1. 江西省气象科学研究所, 江西南昌 330046
    2. 江西省气候中心, 江西南昌 330046
  • 收稿日期:2023-02-20 出版日期:2024-08-28 发布日期:2024-10-11
  • 通讯作者: 吴琼 E-mail:changelyn2022@163.com;wuqioong@foxmail.com
  • 作者简介:刘雅楠, 女, 1994年生, 工程师, 主要从事气候变化研究, E-mail: changelyn2022@163.com
  • 基金资助:
    江西省气象局省所改革专项(JX2023Z11);江西省气象局面上项目(JX2023M20)

Assessment and analysis of climate trend predictions for precipitation in May of 2022 in Jiangxi province

Ya’nan LIU1(),Qiong WU2,*(),Yong LI2   

  1. 1. Jiangxi Institute of Meteorological Science, Nanchang 330046, China
    2. Jiangxi Climate Center, Nanchang 330046, China
  • Received:2023-02-20 Online:2024-08-28 Published:2024-10-11
  • Contact: Qiong WU E-mail:changelyn2022@163.com;wuqioong@foxmail.com

摘要:

选用地面观测、NCEP再分析等资料, 应用青藏高原积雪面积距平指数和大气环流指数, 对比实况与气候动力模式结果, 对2022年5月江西省降水量气候预测进行评估, 并分析预测信号及其应用情况。结果表明: 2022年5月气候动力模式“江西省南部降水偏多”的总体降水气候特征预测较为准确, 且“江西省存在降水集中期, 部分地区有洪涝发生”的预测与实况相一致, 5月降水过程的预报基本准确, 但江西省北部以及中部地区的旱情预报等级偏小。前期预测综合了拉尼娜事件、前一年冬季冬青藏高原积雪异常偏多和印度洋海温变化等多个预测信号对2022年5月江西省降水量气候趋势的影响, 但低估了拉尼娜事件对该月江西省降水的影响, 高估了高原积雪异常偏多对江西北部降水的影响, 导致出现预测偏差。

关键词: 拉尼娜, 青藏高原积雪, 印度洋暖海温

Abstract:

Based on datasets from ground observations and NCEP reanalysis, the climate prediction derived from the dynamic model was evaluated towards the precipitation in Jiangxi province in May of 2022, using the Tibetan Plateau snow cover anomaly index and atmospheric circulation index. Additionally, the predictive signals and their applications were also analyzed. The results showed that the model prediction of "above-normal precipitation in southern Jiangxi province" is generally accurate, and the prediction of "a concentration period of precipitation in Jiangxi province, with some areas experiencing floods" matches the reality. The precipitation processes in May are predicted well, though the drought severity in northern and central areas is underestimated to some extent. Prediction at the early stage combines the impacts of several predictive signals, including the La Niña event, the excessive snow cover anomaly over Tibetan Plateau in the preceding winter, and the sea surface temperature changes in Indian Ocean, on the precipitation trend in May of 2022 for Jiangxi province. However, it underestimates the influence of La Niña on the whole area and overestimates the impact of the excessive snow cover anomaly over Tibetan Plateau on the northern area, resulting in certain prediction deviations.

Key words: La Niña, Snow cover over Tibetan Plateau, Warm sea surface temperature in Indian Ocean

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