大气科学2013，Vol.37Issue(1)：54-64,11.DOI:10.3878/j.issn.1006-9895.2012.11234
消除系统性观测误差的时空梯度信息同化方法研究
Assimilation of Temporal and Spatial Gradient Information to Eliminate the Systematic Observation Error
摘要
Abstract
With the advances of meteorological observation instruments, a variety of meteorological observations can be used in numerical prediction models. However, due to the observational error, especially systematic deviations in unconventional observations, the effect of observational data assimilation has not been fully examined. Thus, a variational assimilation method for temporal and spatial gradient information is proposed to eliminate such errors. The principle is that no a priori estimates of the systematic bias are needed, but a gradient information operator is used to transform the original variables so as to implicitly avoid this systematic error. A series of results of four-dimensional variational assimilation ideal experiments based on a shallow water model shows that this assimilation could completely eliminate the impact of smoothness systematic deviation on the assimilation results. The model could provide a good assimilation effect for the variables having a small value, and could estimate the scope of application for the ones having a large value. Due to the uncertainty of the optimal solution, the assimilation effect absorbs more of the overall temporal and spatial gradient trends of the observation field rather than the observation value itself, which is applicable to observational data with low credibility.关键词
数值预报/系统性观测偏差/时空梯度信息/同化Key words
Numerical weather prediction/ Systematic error/ Temporal and spatial gradient information/ Assimilation分类
天文与地球科学引用本文复制引用
王云峰,费建芳,袁炳,韩月琪..消除系统性观测误差的时空梯度信息同化方法研究[J].大气科学,2013,37(1):54-64,11.基金项目
国家高技术研究发展计划(863计划)2010AA012304,国际科技合作项目2010DFB33880,国家自然科学基金41005029、41105065、11271195,国家公益性行业(气象)科研专项GYHY201106004,江苏省自然科学基金BK2010128 （863计划）
