主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2019, Vol. 35 ›› Issue (2): 97-101.doi: 10.3969/j.issn.1673-503X.2019.02.014

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黄山冬半年云海预报研究

丁国香1, 刘安平2, 杨彬1   

  1. 1. 安徽省公共气象服务中心, 安徽 合肥 230031;
    2. 黄山气象管理处, 安徽 黄山 242709
  • 收稿日期:2017-12-03 修回日期:2018-01-30 出版日期:2019-04-30 发布日期:2019-04-30
  • 作者简介:丁国香,女,1982年生,工程师,主要从事专业气象服务方面研究,E-mail:kellyding_100@163.com
  • 基金资助:

    安徽省气象局科技发展基金项目“山岳型景区气象景观预报技术研究”（KM201603）资助。

Study on the forecast of cloud landscape in Huangshan Mountain in winter half-year

DING Guo-xiang1, LIU An-ping2, YANG Bin1   

  1. 1. Anhui Public Meteorological Service Center, Hefei 230031, China;
    2. Huangshan Meteorological Agency, Huangshan 242709, China
  • Received:2017-12-03 Revised:2018-01-30 Online:2019-04-30 Published:2019-04-30

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摘要：

利用2004—2014年黄山气象站地面气象观测资料和NCEP/NCAR再分析资料，分析了云海发生时气温、气压、湿度、风速等要素的垂直分布、时间演变特征，选取能够反映云海天气特征的指标作为预报因子，分析预报因子分布特征，确定其阈值及消空指标，采用指标叠套法建立了黄山冬半年各月08时云海预报模型，总体正确率为88%，TS评分为31%。利用2015—2016年资料进行检验，总体正确率为88%，TS评分为36%，其中3月、10月TS评分为44%，1月TS评分为38%，模拟结果对黄山冬半年的云海预报具有一定的参考价值。

关键词: 云海, 预报因子, 指标叠套法

Abstract:

In order to improve the forecast accuracy of cloud landscape in mountainous scenic spot,the temporal change and the vertical distribution characteristics of some meteorological elements such as temperature,humidity and so on were first analyzed based on the observed cloud data from the Huangshan weather station and the NCEP/NCAR reanalysis data during 2004-2014.Then,the forecast factors reflecting the cloud landscape weather features were selected,and their thresholds and negative indexes were determined by analyzing the distribution characteristics of the forecast factors.Finally,the forecast model of cloud landscape at 08:00 during winter half-year was developed with index accumulation method and its total forecasting accuracy and TS grade was 88% and 31%,respectively.In addition,the model was further verified using the data from 2015 to 2016.As a result,the forecast accuracy of cloud landscape is 88% and the total TS grade is 36%.Specifically,TS grades in March and October are 44% and that in January is 38%.In conclusion,the model simulation results can provide available reference to the forecast of cloud landscape in Huangshan Mountain in winter half-year.

Key words: Cloud landscape, Forecast factor, Index accumulation method

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