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  • 副教授
  • 性别:女
  • 毕业院校:中国科学院大学
  • 学历:博士研究生毕业
  • 学位:理学博士学位
  • 在职信息:在岗
  • 所在单位:大气物理学院
  • 办公地点:气象楼805
  • 电子邮箱:003144@nuist.edu.cn
  • 2022-01-10曾获荣誉当选:南京信息工程大学年度优秀教职工
  • 2021-12-01曾获荣誉当选:南京信息工程大学-优秀班主任

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Geostationary satellite‐based 6.7 μm band best water vapor information layer analysis over the tibetan plateau

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影响因子:4.261

DOI码:10.1002/2016JD024867

发表刊物:Journal of Geophysical Research: Atmospheres

刊物所在地:美国

关键字:best water vapor information layer water vapor absorption band Jacobian function the Tibetan Plateau

摘要:With the successful launch of FengYun-4A (FY-4A), the first satellite in a new Chinese geostationary weather satellite series (FY-4 series), which carries a high spectral resolution infrared (IR) sounder called GIIRS (Geosynchronous Interferometric Infrared Sounder), and vertical atmospheric profiles can be obtained frequently at the regional scale. A fast radiative transfer model is a key component for quantitative applications of GIIRS radiance measurements, including deriving soundings in near real time for situation awareness and radiance assimilation in numerical weather prediction models. The weighted least squares method on enhancing the accuracy of RTTOV (Radiative Transfer for TOVS) for GIIRS is developed. Besides, currently, fast radiative transfer models for IR sensors are based on global training profiles, since GIIRS is targeted for regional observations; it is beneficial for local weather related applications using local training profiles, which better represent the characteristics of that weather regime. A local training profile data set has been developed for GIIRS using the RTTOV approach, comparisons with line-by-line radiative transfer model indicate that weighted least squares method provides better accuracy (smaller root-mean-square error) in the brightness temperature simulation for the middlewave band of GIIRS than the ordinary least squares method, and the local training profiles have further remarkable improvements on brightness temperature simulation over the global training profiles, especially for GIIRS longwave band. The methods can be applied to RTTOV development for other IR sensors onboard the geostationary satellites.

全部作者:Di D., Ai Y., Li J., Shi W., Lu N.,Xue Y., Li Z.,Li Z., Lu R., Gunshor M. M., Moeller S. L., Di D.,Timothy J. S.

第一作者:Di, Di,Yunheng Xue

通讯作者:Ai Yufei,李俊,Li Jun

论文编号:10.1002/2016JD024867

学科门类:气象与大气科学

一级学科:地学

卷号:121

期号:9

页面范围:1-19

ISSN号:2169-8996

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发表时间:2016-05-16