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 ›› 2013, Vol. 29 ›› Issue (1): 84-88.doi:

• 简报 • 上一篇    下一篇

基于自动站资料的海上风客观预报方法

吴曼丽1 王瀛2 袁子鹏1 曲荣强1 梁寒1   

  1. 1. 沈阳中心气象台，辽宁 沈阳 110016；2. 辽宁省气象灾害监测预警中心，辽宁 沈阳 110016
  • 出版日期:2013-02-28 发布日期:2013-02-28

An objective forecast method on sea wind based on data from automatic weather stations

WU Man-li1 WANG Ying2 YUAN Zi-peng1 QU Rong-qiang1 LIANG Han1   

  1. 1. Shenyang Central Meteorological Observatory, Shenyang 110016, China; 2. Liaoning Warning Center of Meteorological Disaster Monitoring, Shenyang 110016, China
  • Online:2013-02-28 Published:2013-02-28

PDF (PC)

573

被引次数

3

摘要： 根据辽宁省沿海自动站资料，采用卡尔曼滤波方法对沈阳区域气象中心MM5中尺度数值预报产品进行解释应用，制作环渤海及邻近海域海面最大风矢量预报的技术方法，对2009年8—12月预报结果进行检验。结果表明：海上最大风矢量预报结果中风速的预报要明显好于风向的预报，其中风向预报最好的海区为黄海北部，准确率为57.3 %；风速预报最好的海区为渤海中部，准确率为64.6 %；风速误差以正误差为主，说明风速的预报值与实况值相比偏大。该方法对于环渤海及邻近海域海上风的预报效果较好，能够比较真实地反映海上风演变过程，具有预报参考价值。

关键词: 自动站资料, 卡尔曼滤波, 环渤海区域, 海上风

Abstract: Utilizing wind speed and wind direction data from automatic weather stations along the coast in Liaoning province, mesoscale numerical prediction products from the MM5 model in Shenyang regional meteorological center were applied by a Kalman filtering method. A forecast method on the maximum wind vector along the Bohai Sea and the surrounding sea area was developed. The forecast results  from August to October of 2009 were tested. It is seen that the forecast accuracy of the maximum wind vector is higher for  wind speed than for  wind direction. The forecast accuracy of wind direction is highest in the north of the Huanghai Sea and reaches 57.3%, while that of wind speed is in the middle of the Bohai Sea and it is 64.6%. Most errors of wind speed are positive, and it means that the forecast value is higher than the observational value. This method is good for sea wind forecast in the Bohai Sea and the neighbor sea area. This forecast method could reflect truly the evolution process of sea wind, and it could provide references for the corresponding forecast.

Key words: Automatic weather station data, Kalman filter, The Bohai region, Sea wind