摘要:为了科学设计黄渤海海洋气象边界层观测站网并研究观测网布局对数值天气预报模式的影响，本文采用模式误差、海洋气象要素特征区域资料统计分析和观测系统模拟试验（OSSE）方法，根据边界层雾、层云降水、小风与中等风速天气条件设计布局方案，并分析站点观测要素对数值预报模式的要素预报的影响。模拟试验数据使用了每6 h NCEP再分析资料FNL（NCEP Final Operational Global Analysis data）、NCEP每天平均的高分辨率海温资料RTG_SST（Real-Time Global Sea Surface Temperature）和石油平台、浮标站等每小时实况观测资料，评估了黄渤海海洋气象站网布局各个方案的优缺点。评估结果表明，湿度和风的要素预报受实况风向风速条件影响，偏东和偏北风个例湿度要素预报较好。然而，在偏南中等风速个例中，风场预报要素更接近实况。温度场的分析综合结果显示，在海气相互作用影响较大的天气过程中，特征区域布站能明显提高温度要素的预报准确率。最后，综合分析多项模拟试验的结果，给出了改进数值预报准确率的海洋布站建议。
关键词:观测系统模拟试验/
数值模拟/
海洋气象/
布局/
天气预报
Abstract:This work aimed to design an observational network of the air-sea boundary layer over the Bohai and the Yellow Sea, China, and further investigate the effects of these observations on a U.S. numerical prediction model (Weather Research and Forecasting model, WRF). Statistical analysis of the regional characteristics of the air-sea elements, model error, and observation system simulation experiments (OSSE) were conducted. Evaluations of the observation network were conducted under different wind and weather conditions and the advantages and disadvantages of each configuration scheme were weighed. The 6-h NCEP/NCAR FNL (NCEP Final Operational Global) reanalysis data, NCEP real-time global daily sea surface temperature (RTG_SST) analysis data, and buoy and oil-platform observational data were used. Results showed that the forecast humidity and wind were greatly affected by the actual direction and velocity of the wind, and humidity was better predicted under easterly and northerly wind conditions. Moreover, in the moderate southerly wind case, the forecast winds were closer to the observations. It was found that the forecast accuracy of temperature could be significantly improved by configuring the station network based on regional characteristics. Based on a comprehensive overview of the model simulations, suggestions for configuring the air-sea observation stations so as to improve numerical forecast accuracy are provided.
Key words:OSSE (Observation System Simulation Experiment)/
Numerical simulation/
Ocean meteorology/
Distribution/
Weather forecast
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http://www.iapjournals.ac.cn/qhhj/article/exportPdf?id=201906004
