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气象:2024,50(10):1243-1255
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白鹤滩水电站干季偏北大风环流形势分析和客观判识
孟思彤,尹晔,白爱娟,刘皓,郑自君
(成都信息工程大学大气科学学院,成都 610225; 吉林省气象科学研究所/长白山气象与气候变化吉林省重点实验室,长春 130062;中国长江电力股份有限公司智慧长江与水电科学湖北省重点实验室,宜昌 443000;四川省凉山州气象局,西昌 615000)
Analysis and Objective Identification of Northerly Strong Wind Circulation Pattern for Baihetan Hydroelectric Power Station in Dry Season
MENG Sitong,YIN Ye,BAI Aijuan,LIU Hao,ZHENG Zijun
(School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225; Institute of Meteorological Sciences of Jilin Province/Jilin Provincial Key Laboratory of Changbai Mountain Meteorological & Climate Change, Changchun 130062;Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co. Ltd., Yichang 443000;Liangshan Meteorological Office of Sichuan Province, Xichang 615000)
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投稿时间:2023-06-26    修订日期:2024-07-03
中文摘要: 基于2018—2020年11月至次年4月金沙江下游峡谷区139次干季偏北大风天气个例开展大风天气环流形势的分析,并参考Lamb Jenkinson方法建立客观判识条件,并对判识条件进行检验和修正。获得以下结论:选择水电站15次典型偏北大风天气,通过对环流形势特征分析,将影响大风的高空环流概括为:南支槽型、高原槽型和横槽型。15次个例中南支槽型和高原槽型均出现了6次,横槽型出现了3次。基于Lamb Jenkinson方法的环流特征参数分析,确定了干季大风环流客观判识的关键区和初步判识条件。南支槽型和高原槽型判识条件为关键区地转风纬向分量u>10 dagpm/10°(经度),且与经向分量v的差(u-v)>10 dagpm/10°(经度),同时地转涡度ξ>0 dagpm/10°;横槽型判识条件为关键区u<20 dagpm/10°(经度),且要求ξ>u。另选取2021年干季14次大风个例检验以上环流判识条件,发现有11次准确识别出环流类型。根据未识别出环流类型的原因,对u和u-v的阈值进行修正,结果表明修正后的判识条件准确可行。最终建立的环流形势客观判识方法可为白鹤滩水电站大风预警提供参考。
Abstract:Baihetan Hydroelectric Power Station is located in the canyon area of the lower reaches of the Jinsha River, with frequent northerly strong wind weather in the dry season. Objectively identifying the circulation system that affects the strong winds of the hydroelectric power station is beneficial for revealing the formation mechanism of strong winds in special areas. Based on 139 cases of northerly strong wind weather in the dry season in the canyon area from November to April of 2018-2020, this paper analyzes the circulation situation of strong wind weather, and establishes objective identification conditions with reference to the Lamb-Jenkinson (L-J) method. Moreover, the identification conditions are tested and corrected. The results show that 15 cases of typical northerly strong winds at the hydropower station are selected. According to the analysis of the characteristics of circulation situation, the upper-air circulation affecting strong winds is summarized as southern branch trough, plateau trough and transverse trough. In the 15 cases, the first two types appeared 6 times each and the transverse trough type appeared 3 times. Based on the analysis of circulation characteristic parameters by L-J method, the key areas and preliminary identification conditions of strong wind circulation in dry season are determined. The identification conditions of the southern branch trough and plateau trough types are that the zonal component u of the geostrophic wind in the key area is greater than 10 dagpm/10°longitude-1, and its difference from the meridional component v is greater than 10 dagpm/10°longitude-1. At the same time, the vorticity of the geostrophic wind is greater than 0 dagpm/10°longitude-1. The identification condition of transverse trough type is that the critical area u is less than 20 dagpm/10°longitude-1, and it is required to be greater than u. In addition, 14 cases of strong winds in the dry season of 2021 are selected to test the above circulation identification conditions. It is found that from 11 of the 14 cases, the circulation types are identified accurately. According to the reason that the circulation type is not recognized, the thresholds of u and the difference between u and v are corrected. The results show that the corrected discrimination conditions are accurate and feasible. The objective identification method of circulation situation could provide a reference for strong wind warning at the Baihetan Hydroelectric Power Station.
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基金项目:国家自然科学基金项目(U2242202、U2040212)、成都信息工程大学教师科技创新能力提升计划重大项目(KYTD202201)、中国气象局创新发展专项(CXFZ2022J012)和高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金项目(SCQXKJYJXMS2022210)共同资助
引用文本:
孟思彤,尹晔,白爱娟,刘皓,郑自君,2024.白鹤滩水电站干季偏北大风环流形势分析和客观判识[J].气象,50(10):1243-1255.
MENG Sitong,YIN Ye,BAI Aijuan,LIU Hao,ZHENG Zijun,2024.Analysis and Objective Identification of Northerly Strong Wind Circulation Pattern for Baihetan Hydroelectric Power Station in Dry Season[J].Meteor Mon,50(10):1243-1255.