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杭州大雪的成因和预报指标分析
引用本文:李进,周娟,毛则剑. 杭州大雪的成因和预报指标分析[J]. 科学技术与工程, 2020, 20(31): 12724-12733
作者姓名:李进  周娟  毛则剑
作者单位:杭州市气象局,杭州310051;杭州市气象局,杭州310051;杭州市气象局,杭州310051
基金项目:浙江省气象局2019年度科技计划项目(2019QN08)和杭州市气象局科技计划项目(QX201913)
摘    要:为了提高大雪天气的预报准确率,利用2008—2018年冬季美国国家环境预报中心( National Center of Environmental Prediction,NCEP) 1° × 1°逐6 h再分析资料、NCEP/NCAR再分析资料以及常规气象观测和降雪加密观测资料。挑选出杭州地区9次典型的大雪天气过程,从大尺度环流背景和水汽、动力以及热力因子等物理量场结构方面展开研究,同时与多年冬季平均的相关特征进行了比较分析,最终给出了杭州典型大雪天气发生时的概念模型和预报指标,大致概括如下:首先需要具备能够产生降雪的大尺度环流背景,其次,需满足大雪产生的水汽和动力等具体物理量条件,最后,必须达到特定的温度和厚度指标条件。该大雪预报模型可为杭州开展的精细化业务预报提供参考依据。

关 键 词:大雪  物理量指标  厚度  温度层结  预报指标
收稿时间:2020-03-04
修稿时间:2020-07-28

Analysis on the Cause and Forecast Indexes of Heavy Snow in Hangzhou
Li Jin,Zhou Juan,Mao Ze-jian. Analysis on the Cause and Forecast Indexes of Heavy Snow in Hangzhou[J]. Science Technology and Engineering, 2020, 20(31): 12724-12733
Authors:Li Jin  Zhou Juan  Mao Ze-jian
Affiliation:Hangzhou Meteorological Service
Abstract:In order to improve the forecast accuracy of heavy snow, based on the NCEP (National Center of Environmental Prediction) reanalysis data with resolutions of 1°×1°, NCEP/NCAR reanalysis data, conventional meteorological data, as well as intensive snowfall observations from 2008 to 2018, 9 typical heavy snow processes in Hangzhou region were selected to study on the aspects of large-scale circulation background and physical quantities such as dynamic, water vapor and thermal factors, which were compared with the relative average characteristics in winter, furthermore. Ultimately, the conceptual model and forecast indexes of typical heavy snow in Hangzhou are roughly as follows: First of all, the large-scale circulation background must satisfy some conditions for the formation of snowfall. Secondly, the physical quantities such as water vapor and dynamic factors should satisfy specific conditions for heavy snow. Finally, certain conditions for temperature and thickness indexes must be achieved. This forecast model of heavy snow can provide a reference for the daily delicate operational forecasting of Hangzhou.
Keywords:heavy snow   physical quantity index   thickness   temperature stratification   forecast index
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