气象2026，Vol.52Issue(5)：621-630,10.DOI:10.7519/j.issn.1000-0526.2026.011701
基于环流分型的拉萨机场降雪天气对比分析
Comparative Analysis of Snowfall Events at Lhasa Airport Based on Circulation Type Classification
摘要
Abstract
To improve snowfall forecast accuracy and aviation meteorological services at Lhasa Airport,by employing the improved Jenkinson-Collison(J-C)circulation type classification method,this paper classi-fies and diagnoses 56 snowfall events that occurred during 2013-2020 at Lhasa Airport.The results are that,with the improved method,a classification success rate of 92.9％is achieved,and three types,i.e.,the cyclonic type(12.5％),low-pressure trough type(42.9％)and westerly advection type(37.5％)of snowfall events are identified.There are only 7.1％of snowfall events remaining unclassified-significantly lower than that by the traditional method.The characteristics of the three identified circulation types are signifi-cantly different.The cyclonic type,corresponding to plateau vortices,features the strongest dynamics and water vapor conditions,with the most average snowfall(3.4 mm)and longest duration(358 min).The low-pressure trough type,influenced by the southern branch trough,shows the most unstable atmospheric stratification but relatively weak dynamics and water vapor,resulting in the lowest mean snowfall(1.2 mm)and shortest duration(170 min).The westerly advection type,dominated by warm ridges and upper-level jets,has the most stable atmospheric stratification,with a"low-level convergence and upper-level divergence"moisture structure.Its intermediate snowfall indicators lie between those of the other two types,that is,the average snowfall is 1.8 mm and the duration is 280 min.These findings could pro-vide a scientific basis for refined snowfall forecasting and help improve the aviation meteorological services at Lhasa Airport.关键词
拉萨机场/降雪天气/Jenkinson-Collison环流分型Key words
Lhasa Airport/snowfall weather/Jenkinson-Collison circulation type classification分类
天文与地球科学引用本文复制引用
袁敏,王迪,朱国辉,田续蔚..基于环流分型的拉萨机场降雪天气对比分析[J].气象,2026,52(5):621-630,10.基金项目
科技部科技基础资源调查专项(2025FY101500)、国家重点研发计划(2021YFB2601701-01)、西南区域人工影响天气能力建设(四川)研究试验项目[SCIT-ZG(Z)-2024100001]和中央高校基本科研业务费专项资金(24CAFUC01003)共同资助 （2025FY101500）
