热带气象学报2017，Vol.33Issue(4)：500-509,10.DOI:10.16032/j.issn.1004-4965.2017.04.007
同化IASI资料对台风“红霞”和“莫兰蒂”预报的影响研究
IMPACT OF DATA ASSIMILATION FOR THE IASI OBSERVATIONS ON THE FORECAST OF TYOHOON HONGXIA AND MOLANDI
摘要
Abstract
The Infrared Atmospheric Sounder Interferometer (IASI) provides the temperature and humidity information with high precision about the atmosphere in the vertical direction.The IASI instrument can detect the characteristics of typhoon structure and make up for the shortage of the observation data distributed sparsely in typhoon-affected areas.In this study,a three-dimensional variational data assimilation for Weather Research and Forecasts (WRFDA) system was chosen as the basic assimilation system,and the MW cloud detection put forward by McNally was implemented in the WRFDA system for IASI cloud contamination detection and the cloud parameters were tuned for the research.All the IASI observations are assimilated after quality control and variational bias correction and the impact of the data assimilation on the forecasts of the super typhoon Hongxia (1506) and Molandi (1614) are assessed.The results from both the typhoon experiments are similar and indicate that the cloud detection influences the assimilation of the IASI observations very much.For the super typhoon Hongxia,the MW cloud detection scheme retained just 16.2％ the number of observations by the large-threshold LMW cloud detection scheme and 9.2％ of that by the MMR cloud detection scheme for the upper-level channel 299,and 3.3％ and 2.6％ respectively for the lower-level channel 921,but the analysis affected by the MW cloud detection scheme reduces the track error of typhoon Hongxia for the first 72 hours most remarkably and improves the path forecast most accurately.Generally the assimilation of IASI observations improves the skills of typhoon forecast.关键词
红外高光谱/IASI/台风/资料同化/云检测Key words
infrared hyper-spectral/IASI/Typhoon/data assimilation/cloud detection分类
天文与地球科学引用本文复制引用
余意,张卫民,曹小群,赵延来,段博恒..同化IASI资料对台风“红霞”和“莫兰蒂”预报的影响研究[J].热带气象学报,2017,33(4):500-509,10.基金项目
国家自然科学基金项目(41305101) （41305101）
国防科技大学优秀研究生创新资助项目(4345133214)共同资助 （4345133214）
