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): 54-63.doi: 10.3969/j.issn.1673-503X.2024.04.007

• 论文 • 上一篇    下一篇

2016—2021年5—10月辽宁省降水量时空分布精细化特征分析

李萍1,2(),陈传雷3,陈宇3,*(),牛丹4,刘硕2,聂安祺2,张绍勇5   

  1. 1. 中国气象局流域强降水重点开放实验室/暴雨监测预警湖北省重点实验室 中国气象局武汉暴雨研究所, 湖北武汉 4302051
    2. 辽宁省气象台, 辽宁沈阳 110166
    3. 辽宁省气象灾害监测预警中心, 辽宁沈阳 110166
    4. 辽宁省气象信息中心, 辽宁沈阳 110166
    5. 辽宁省气象装备保障中心, 辽宁沈阳 110166
  • 收稿日期:2023-02-13 出版日期:2024-08-28 发布日期:2024-10-11
  • 通讯作者: 陈宇 E-mail:ynulp@163.com;chenyu1018@163.com
  • 作者简介:李萍, 女, 1987年生, 高级工程师, 主要从事短期天气预报研究, E-maill: ynulp@163.com
  • 基金资助:
    中国气象局流域强降水重点开放实验室项目(2023BHR-Y21);辽宁省气象局气象科研项目(202403);辽宁省气象局气象科研项目(202301);中国气象局复盘总结专项(FPZJ2024-027)

Analysis of spatio-temporal characteristics of precipitation in Liaoning province from May to October during 2016-2021

Ping LI1,2(),Chuanlei CHEN3,Yu CHEN3,*(),Dan NIU4,Shuo LIU2,Anqi NIE2,Shaoyong ZHANG5   

  1. 1. China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
    2. Liaoning Provincial Meteorological Observatory, Shenyang 110166, China
    3. Liaoning Meteorological Disaster Monitoring and Early Warning Center, Shenyang 110166, China
    4. Liaoning province Meteorological Service Center, Shenyang 110166, China
    5. Liaoning Meteorological Equipment Support Center, Shenyang 110166, China
  • Received:2023-02-13 Online:2024-08-28 Published:2024-10-11
  • Contact: Yu CHEN E-mail:ynulp@163.com;chenyu1018@163.com

摘要:

选用2016—2021年5—10月辽宁省小时加密观测降水资料, 分析辽宁省降水过程、短时强降水过程、极端短时强降水过程降水量时空分布特征, 应用K均值聚类法对汛期短时强降水过程降水累积小时数的空间分布进行分类。结果表明: 辽宁省短时强降水过程(小时降水量大于或等于20 mm)和极端短时强降水过程(小时降水量大于或等于该站点历史降水量升序后的第99.9百分位)受地形影响较大。短时强降水高发区主要分布在辽宁东南部的沿海地区、辽宁西部的沿海平原和地势较高地区及辽宁东南部的迎风坡地区。辽宁省汛期降水受季风环流影响, 有明显的季节变化, 平均降水量和降水频次最大值发生在7月和8月, 降水时段主要集中在午后至夜间。辽宁省短时强降水过程降水频次的区域间差异较大, 极端短时强降水过程区域间差异较小。

关键词: 累积小时数, K均值聚类, 短时强降水, 加密自动站

Abstract:

Utilizing hourly high-density precipitation observation data from May to October during 2016-2021 in Liaoning province, this study analyzed the spatio-temporal distribution characteristics of precipitation processes, short-term heavy precipitation events, and extreme short-term heavy precipitation events. The K-means clustering method was applied to classify the spatial distribution of cumulative precipitation hours during short-term heavy precipitation events in the flood season. The results indicated that short-term heavy precipitation events (hourly precipitation ≥20 mm) and extreme short-term heavy precipitation events (hourly precipitation≥99.9th percentile of historical precipitation at the station) are significantly influenced by topography. High-frequency areas of short-term heavy precipitation are primarily in the southeastern coastal regions of Liaoning province, the coastal plains and areas with higher elevation in western Liaoning province, and the windward slopes in southeastern Liaoning province. Precipitation during the flood season in Liaoning province is affected by monsoon circulation, exhibiting distinct seasonal variations. The maximum average precipitation and precipitation frequency occur in July and August, and mainly concentrate from afternoon to night. Considerable regional differences are found in the frequency of short-term heavy precipitation events across Liaoning province, while the regional differences in extreme short-term heavy precipitation events are relatively minor.

Key words: The number of cumulative hours, K-means clustering, Short-term heavy precipitation, High-density automatic weather stations

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