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Wet Refractivity Tomography with an Improved Kalman-Filter Method
作者姓名:曹云昌  陈永奇  李炳华
作者单位:[1]The Hong Kong Polytechnic University, Hong Kong [2]National Satellite Meteorological Center, Beijing 100081 [3]The Hong Kong Observatory, Hong Kong
基金项目:The research was supported by the Hong Kong RGC Grant (PolyU code: B.34.37.Q609). We would like to express our appreciation to the Hong Kong 0bservatory for providing the facilities and data to support our research.
摘    要:An improved retrieval method, which uses the solution with a Gaussian constraint as the initial state variables for the Kalman Filtering (KF) method, was developed to retrieve the wet refractivity profiles from slant wet delays (SWD) extracted by the double-differenced (DD) GPS method. The accuracy of the GPS-derived SWDs is also tested in this study against the measurements of a water vapor radiometer (WVR) and a weather model. It is concluded that the GPS-derived SWDs have similar accuracy to those measured with WVR and are much higher in quality than those derived from the weather model used. The developed method is used to retrieve the 3D wet refractivity distribution in the Hong Kong region. The retrieved profiles agree well with the radiosonde observations, with a difference of about 4 mm km^- 1 in the low levels. The accurate profiles obtained with this method are applicable in a number of meteorological applications.

关 键 词:湿度  折射率  层析术  GPS  全球定位系统  卡尔曼滤波器
收稿时间:2005-11-23
修稿时间:2006-03-22

Wet refractivity tomography with an improved Kalman-Filter method
Yunchang Cao,Yongqi Chen,Pingwha Li.Wet Refractivity Tomography with an Improved Kalman-Filter Method[J].Advances in Atmospheric Sciences,2006,23(5):693-699.
Authors:Yunchang Cao  Yongqi Chen  Pingwha Li
Institution:The Hong Kong Polytechnic University, Hong Kong, National Satellite Meteorological Center, Beijing 100081,The Hong Kong Polytechnic University, Hong Kong,The Hong Kong Observatory, Hong Kong
Abstract:An improved retrieval method, which uses the solution with a Gaussian constraint as the initial state variables for the Kalman Filtering (KF) method, was developed to retrieve the wet refractivity profiles from slant wet delays (SWD) extracted by the double-differenced (DD) GPS method. The accuracy of the GPS-derived SWDs is also tested in this study against the measurements of a water vapor radiometer (WVR) and a weather model. It is concluded that the GPS-derived SWDs have similar accuracy to those measured with WVR and are much higher in quality than those derived from the weather model used. The developed method is used to retrieve the 3D wet refractivity distribution in the Hong Kong region. The retrieved profiles agree well with the radiosonde observations, with a difference of about 4 mm km?1 in the low levels. The accurate profiles obtained with this method are applicable in a number of meteorological applications.
Keywords:wet refractivity  tomography  GPS  kalman filter
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