The vertical structure of water vapor in atmosphere is one of the initial information of numerical weather forecast model. Because of the strong variation of water vapor in atmosphere and limited spatio-temporal solutions of traditional observation technique, the initial water vapor field of numerical weather forecast model can not accurately be described. At present, using GPS slant observations to study water vapor profile is very popular in the world. Using slant water vapor(SWV) observations from Shanghai GPS network,we diagnose the three-dimensional(3D) water vapor structure over Shanghai area firstly in China. In water vapor tomography, Gauss weighted function is used as horizontal constraint, the output of numerical forecast is used as apriori information, and boundary condition is also considered. For the problem without exact apriori weights for observations, estimation of variance components is introduced firstly in water vapor tomography to determine posteriori weights. Robust estimation is chosen for reducing the effect of blunders on solutions. For the descending characteristic of water vapor with height increasing, non-equal weights are used along vertical direction. Comparisons between tomography results and the profile provided by numerical model (MM5) show that the forecasted moisture fields of MM5 can be improved obviously by GPS slant water vapor. Using GPS slant observations to study 3D structure of atmosphere in near real-time is very important for improving initial water vapor field of short-term weather forecast and enhancing the accuracy of numerical weather forecast.Keywords: Shanghai GPS network, GPS slant water vapor, tomography, 3D structure of water vapor, robust estimation of variance component.The vertical profile of water vapor is very important for revising and improving the initial moisture field of mid-scale numerical weather model. At present, the three-dimensional (3D) information of water vapor is provided mainly by radiosonde. However, the distances between any two radiosonde stations exceed 200-300km and the observing time interval is 12 h, which is not enough for observing storm system smaller than 100km and can not satisfy real time short-term weather forecast. The accuracy of water vapor retrieved from meteorology satellite is yet too low. While PWV (Precipitable Water Vapor) with high accuracy and resolutions can be retrieved from ground-based GPS network in real time [1] . However, PWV is the integrated amount of water vapor over each station which can not reflect the 3D structure of atmosphere. Commonly, it is considered difficult to retrieve vertical profile of water vapor from ground-based GPS which is the choke of ground-based GPS meteorology and limits the further application of GPS technique in meteorology. In fact, GPS slant observations include the vertical information of water vapor. Using GPS slant observations from a dense network, 3D structure of water vapor can be retrieved by appropriate tomography technique. In these years, Flores et al. [2] and Lubomir ...
GPS data from Shanghai GPS Comprehensive Application Network (SGCAN) in summer of 2002 are analyzed. The ultra‐rapid orbits of IGS (IGU) are used directly in real‐time processing. Reliable Precipitable Water Vapor (PWV) series can be obtained with the assistance of remote stations. Considering the effect of ocean tide, the accuracy of PWV can be improved. The difference between GPS/PWV and Radiosonde observations is about 2mm. Comparison between the output of MM5 and GPS/PWV shows that GPS can be regarded as one means to verify the forecast of MM5 in near real time. Continuous GPS/PWV series in the whole Meiyu season reflect the changing processes of PWV in detail before and after the onset of Meiyu Season in Yangtze River Delta in 2002 summer. The variation of GPS/PWV shows that the onset of Meiyu season was from southwest to northeast and completed in about 7–8 hours. Rainband moved back and forth between Yangtze River Delta and Huaihe area in Meiyu season. The statistics of PWV peaks and one‐hour rain explains some short‐term forecast ability of GPS/PWV for rainstorms. The humidity condition of numerical forecast model is optimized after GPS/PWV being interpolated to the gridpoints of background field using Cressman method. The accuracy of numerical forecast is improved. One example is provided in this paper which shows the potential of GPS/PWV for improving numerical forecast.
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