Influencial experiments of AIRS data quality control method on hurricane track simulation
In order to examine the quality control (QC) method of Atmospheric Infrared Sounder (AIRS) data in Weather Research Forecast Data Assimilation system (WRFDA) model and numerical experiments on hurricane Earl in America,the effect of QC method on hurricane track simulation was studied.The results show that:11 quality control principles in WRFDA model had great effects on AIRS brightness temperature data assimlation.No matter whether the quality control principles were joined one by one,or the certain one was neglected,the simulation effects of hurricane tracks in assimilation experiments were not as great as those in control experiments.If all quality control principles were applied,the track errors as well as the maximal one in assimilation experiments were less than those in control experiments during most simulation periods.The capacity of different quality control principles for eliminating "bad" data were different.Four quality control principles like surface emissivity Jacobian component detection,limb detection,cloud detection and SST detection can all remove larger number of satellite data.The comparison experiments of different QC principles of AIRS brightness temperature in this paper can help develop infrared high spectrum satellite system in China.
国家科技期刊平台
NSTL
万方数据
维普
