Anomaly-based synoptic analysis and model product application for 2020 summer southern China rainfall events
Anomaly-based synoptic analysis and model product application for 2020 summer southern China rainfall events
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2020年华南夏季降水异常天气分析及模型产品应用
DOI：
10.1016/j.atmosres.2021.105631
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发表时间：
2021-08
影响因子：
5.5
通讯作者：
Ai Y Leung JCH Zhang BL
中科院分区：
文献类型：
--
作者：
Qian WH;Ai Y Leung JCH Zhang BL
采用一种基于异常的天气分析方法对2020年夏季影响中国南方的9次降水事件进行了研究，并与标准天气分析结果进行了比较。这些降水事件主要发生在珠江至长江、淮河一带的龙舟雨季和梅雨雨季，并不完全遵循夏季风的气候季节走向。第一次降水事件发生在龙船雨季，降水中心分布广泛，与925 hPa两个异常反气旋系统之间分布有湿涡异常（MVA）中心的异常流辐合区有关。其余8次降雨事件均出现在梅雨雨季，一般只与异常气流的窄辐合带和正MVA带有关，对流层下层有时伴有异常气旋东移。ECMWF模式成功预测了这些异常辐合区和MVA带，提前时间为2-7天。这种基于异常的分析方法的优点包括它能够直观地识别降雨事件的位置，查明可能的气象原因，并通过早期发现预测者来延长模型预测的长度。
Nine rainfall events affecting southern China in the 2020 summer were studied by a novel anomaly-based synoptic analysis approach, and the results were compared to those of standard synoptic analysis. These rainfall events occurred in the Dragon-boat rainy season and Meiyu rainy season from the Pearl River to the Yangtze and Huaihe rivers and did not entirely follow the climatic seasonal march of the summer monsoon. The first rainfall event occurred within the Dragon-boat rainy season and was associated with a broad rainfall area with scattered precipitation centers related to a broad convergence area of anomalous flows with scattered moist vorticity anomaly (MVA) centers located between two anomalous anticyclonic systems at 925 hPa. The other eight rainfall events appeared in the Meiyu rainy season and were generally associated with only a narrow convergence belt of anomalous flows and a positive MVA belt, sometimes with an anomalous cyclone moving eastward in the lower troposphere. The ECMWF model successfully predicted these anomalous convergence areas and MVA belts with lead times of 2–7 days. The advantages of this anomaly-based analysis approach include its ability to visually identify the location of a rainfall event, pinpoint possible meteorological causes and extend the model forecast length by the earlier detection of predictors.
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DOI：
--
发表时间：
2013
期刊：
Meteorological Monthly
影响因子：
--
作者：
H. Yami
通讯作者：
H. Yami
影响因子：
3.2
作者：
H. Savijärvi
通讯作者：
H. Savijärvi
影响因子：
3.2
作者：
T. Yabe;R. Tanaka;T. Nakamura;F. Xiao
通讯作者：
T. Yabe;R. Tanaka;T. Nakamura;F. Xiao
影响因子：
2.9
作者：
W. Qian;Jun Du;X. Shan;Ning Jiang
通讯作者：
W. Qian;Jun Du;X. Shan;Ning Jiang
影响因子：
5.2
作者：
Liu, Boqi;Yan, Yuhan;Li, Jianying
通讯作者：
Li, Jianying