Study of M-estimator Variational Retrieval Using Simulated Feng Yun-3A Data  

作　　者：Wang Gen Wen Huayang Qiu Kangjun Xie Wei 

机构地区：[1]Anhui Meteorological Information Centre [2]School of Atmospheric Sciences,Nanjing University

出　　处：《Meteorological and Environmental Research》2016年第3期1-6,共6页气象与环境研究（英文版）

基　　金：Supported by Special Scientific Research Fund of Meteorological Public Welfare Profession of China(GYHY201406028);Meteorological Open Research Fund for Huaihe River Basin(HRM201407);Anhui Meteorological Bureau Science and Technology Development Fund(RC201506)

摘　　要：This paper adopts satellite channel brightness temperature simulation to study M-estimator variational retrieval. This approach combines both the advantages of classical variational inversion and robust M-estimators. Classical variational inversion depends on prior quality control to elim- inate outliers, and its errors follow a Gaussian distribution. We coupled the M-estimators to the framework of classical variational inversion to obtain a M-estimator variational inversion. The cost function contains the M-estimator to guarantee the robustness to outliers and improve the retrieval re- sults. The experimental evaluation adopts Feng Yun-3A （FY-3A） simulated data to add to the Gaussian and Non-Gaussian error. The variational in- version is used to obtain the inversion brightness temperature, and temperature and humidity data are used for validation. The preliminary results demonstrate the potential of M-estimator variational retrieval.This paper adopts satellite channel brightness temperature simulation to study M-estimator variational retrieval. This approach combines both the advantages of classical variational inversion and robust M-estimators. Classical variational inversion depends on prior quality control to elim- inate outliers, and its errors follow a Gaussian distribution. We coupled the M-estimators to the framework of classical variational inversion to obtain a M-estimator variational inversion. The cost function contains the M-estimator to guarantee the robustness to outliers and improve the retrieval re- sults. The experimental evaluation adopts Feng Yun-3A （FY-3A） simulated data to add to the Gaussian and Non-Gaussian error. The variational in- version is used to obtain the inversion brightness temperature, and temperature and humidity data are used for validation. The preliminary results demonstrate the potential of M-estimator variational retrieval.

关 键 词：Non-Gaussian M-ESTIMATOR Variational retrieval Re-estimated contribution rate FY-3A simulated data 

分 类 号：P412.27[天文地球—大气科学及气象学]