2023年8月四川地区两次强降水天气的云图释用
Application of Satellite Cloud Image of Two Heavy Precipitation Weather in Sichuan in August 2023
DOI: 10.12677/ccrl.2024.135126, PDF,   
作者: 王晨旭:成都信息工程大学大气科学学院,四川 成都;犍为县气象局,四川 乐山;袁 振, 刘晓达:民航西南空管局气象中心,四川 成都;张永莉*:成都信息工程大学大气科学学院,四川 成都
关键词: 强降水葵花9号卫星四川地区亮温Heavy Precipitation Himawari-9 Sichuan TBB
摘要: 文章使用葵花9号卫星资料与常规观测资料,利用环流形势分析、物理量场分析与云图分析对2023年8月上中旬四川地区两次降水过程进行分析。结果表明:1) 两次过程按主要影响系统可分为西南涡与东海台风型、南亚高压型。2) 高时空分辨率的葵花卫星云图可清晰分别对流云边界与轮廓,更容易判断对流发展的阶段、强度变化与移动方向。3) 对流云从初生到产生强降水的发展特征主要可分为单独对流云过程与有对流云融合过程两类,两类最主要的区别就是对流云融合过程比单独对流云过程多了加速发展过程,在亮温不变或波动上升阶段后有一明显的再加速下降过程。4) 最低红外亮温低于210 K且观测到红外亮温快速下降、红外与水汽亮温同步降低至212 K以下、红外与水汽亮温差降低至2 K以下,使用这三个特征来预测强降水产生时间,可提高预测的准确性。
Abstract: The Himawari-9 satellite data and conventional observation data were used to analyze the two heavy precipitation processes in Sichuan in August 2023, using circulation situation analysis, physical quantity field analysis and cloud image analysis. The results show that 1) the two processes can be categorized into the Southwest China vortex and East China Sea typhoon type, the South Asian high type, the South China Sea typhoon type, and the Western Pacific Subtropical High type according to the main influencing systems. 2) The high temporal and spatial resolution of the Himawari satellite cloud image can clearly separate the boundary and outline of the convective cloud, which makes it easier to judge the stage of convective development, intensity change and moving direction. 3) The development characteristics of convective clouds from the initial generation to the production of heavy precipitation can be divided into two categories: the process of convective clouds alone and the process of convective cloud fusion. The main difference between the two categories is that the process of convective cloud fusion is more accelerated than the process of convective clouds alone, which is reflected as a clear re-accelerating process of decreasing in the bright temperature evolution diagram after the bright temperature remains unchanged or fluctuates in the rising stage. 4) The three features of the minimum TBB13 below 210 K and the observed rapid decrease of TBB13, the simultaneous decrease of TBB13 and TBB8 below 212 K, and the decrease of the difference between TBB13 and TBB8 below 2 K, which can be utilized to improving the accuracy of predicting the generation of heavy precipitation.
文章引用:王晨旭, 袁振, 刘晓达, 张永莉. 2023年8月四川地区两次强降水天气的云图释用[J]. 气候变化研究快报, 2024, 13(5): 1098-1110. https://doi.org/10.12677/ccrl.2024.135126

参考文献

[1] 孙继松. 强对流天气预报的基本原理与技术方法中国强对流天气预报手册[M]. 北京: 气象出版社, 2014.
[2] 桂海林, 诸葛小勇, 韦晓澄, 等. 基于Himawari-8卫星的云参数和降水关系研究[J]. 气象, 2019, 45(11): 1579-1588.
[3] Larissa, P.-V., et al. (2022) A Machine Learning Algorithm for Himawari-8 Total Suspended Solids Retrievals in the Great Barrier Reef. Remote Sensing, 14, 3503-3503. [Google Scholar] [CrossRef
[4] Zhuge, X.Y. and Zou, X.L. (2018) Summertime Convective Initiation Nowcasting over Southeastern China Based on Advanced Himawari Imager Observations. Journal of the Meteorological Society of Japan. Ser. II, 96, 337-353. [Google Scholar] [CrossRef
[5] 郭巍, 崔林丽, 顾问, 等. 基于葵花8卫星的上海市夏季对流初生预报研究[J]. 气象, 2018, 44(9): 1229-1236.
[6] 张博, 段炼, 肖晓, 等. 基于葵花8号卫星的成都地区初生对流研究[J]. 航空计算技术, 2023, 53(3): 55-59.
[7] 杨磊, 才奎志, 孙丽, 等. 基于葵花8号卫星资料的沈阳两次暴雨过程中对流云特征对比分析[J]. 暴雨灾害, 2020, 39(2): 125-135.
[8] 王小龙, 王彤, 李映春, 等. 基于“葵花8号”气象卫星的陇东南地区强对流识别跟踪技术研究[J]. 沙漠与绿洲气象, 2022, 16(5): 56-61.