Estimation and Evaluation of the Precipitable Water Vapor from GNSS PPP in Asia Region
Water vapor is one of the main atmospheric parameters, which has important reference value for climate research, weather forecast, weather monitoring and so on. BDS and GALILEO not only can realize high precision orbit determination and user positioning,
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Abstract Water vapor is one of the main atmospheric parameters, which has important reference value for climate research, weather forecast, weather monitoring and so on. BDS and GALILEO not only can realize high precision orbit determination and user positioning, but also can be an effectively sensor for satellite meteorology. The rapid development and improvement of BDS and GALILEO, which provide an opportunity to estimate a more high-resolution, precise solution of zenith wet delay (ZWD) and precipitable water vapor (PWV). In this paper, the observation from MGEX stations over Asia regional are processed respectively by GPS-only and GPS/BDS/GALILEO combining precise point positioning (PPP), and ZWD and PWV are retrieved by PPP method. The performance of the estimated ZWD and PWV was tested and verified by GGOS (Global Geodetic Observing System) and radiosonde data. The result shows that the ZWD solutions estimated from PPP agree with GGOS solution very well. Compared with the MAE and RMS of GPS, the results of GPS/BDS/GALILEO decrease by 0.6, 0.5 cm, respectively. The correlation coefficient increases 0.027–0.031. The correlation coefficient between PPP and radiosonde is above 0.9, which shows that they have reached a high level of convergence. The MEAN, RMS value of GPS/BDS/GALILEO is about 1 mm less than GPS. The correlation coefficient increases 0.023–0.034, which further proves that BDS and GALILEO can improve the estimation accuracy of PWV. Then we are sure that BDS and GALILEO will bring great benefits of ZWD and PWV. Keywords Precipitable water vapor delays Weighted mean temperature
Precise point positioning
Zenith wet
Z. Liu Y. Li (&) F. Li J. Guo College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2017 J. Sun et al. (eds.), China Satellite Navigation Conference (CSNC) 2017 Proceedings: Volume I, Lecture Notes in Electrical Engineering 437, DOI 10.1007/978-981-10-4588-2_8
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1 Introduction Water vapor is a highly instability component of atmospheric. It plays important roles in the transfer of energy and global climate change, which is one of crucial characterized meteorological parameters in weather forecast and atmospheric research applications [1]. A good knowledge of the spatiotemporal characteristics of water vapor will be needed for the improvement of weather forecast. Radiosonde is one of the traditional technique to obtain precipitable water vapor (PWV) observation, which has a long observation history. The algorithm using radiosonde data to retrieve PWV is relatively straightforward. However, the operational radiosonde stations commonly only measure water vapor twice a day because of high operational costs and heavy workload. It produces at most two measurements every day. Subject to the low spatio-temporal resolution and the low geographic density of radiosonde stations, PWV obtained from radiosonde becomes more and more unable to satisfy with the request of s
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