摘要
分析了自动站资料同化中误差的主要来源,并对其进行分类。根据资料同化需求和不同的误差类型,在较为严格的质量控制策略下,设计与之对应的质量控制方法。针对新型自动气象站的风向风速、气温、相对湿度和气压5个要素,选取京津冀地区一周的数据进行数值试验,并进行定量分析。结果表明:本文的质量控制方法能够有效减小过失误差与代表性误差,保留随机误差的正态分布特性,观测与背景场的均方根误差得到一定程度的降低。使用海平面气压代替本站气压进行空间一致性检查能够取得更为合理的结果。
The analysis and classification are conducted on the error sources in data assimilation,and according to the categories and the demands of data assimilation,the matching quality control method is developed under the strict strategy.For one week data selected from the area of Beijing,Tianjin and Hebei Province of new type Automatic Weather Stations（AWS）,including pressure,temperature,humidity,and wind,numerical experiments are carried out.The results show that the method is applicable to reduce rough errors and representative errors effectively,keep the normal distribution characteristic of random errors,and lower the root mean square error between observation and background significantly.
作者
邵长亮
王娇
赵旭
Shao Changliang Wang Jiao Zhao Xu(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science ＆ Technology,CMA Meteorological Observation Centre CMA Huafeng Meteorological Media Group)
出处
《气象科技》
北大核心
2017年第4期583-589,共7页
Meteorological Science and Technology
基金
中国气象局气象探测中心青年科技基金(TCQN201621)
江苏省普通高校研究生科研创新计划项目(KYLX_0824)资助
