GWMT Global Atmospheric Weighted Mean Temperature Models: Development and Refinement
The atmospheric weighted mean temperature Tm plays a pivotal role in remote sensing water vapor with GNSS technique. However, real-time Tm cannot be obtained at given place due to limitation of modern technology. In order to remove this barrier, a global
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GWMT Global Atmospheric Weighted Mean Temperature Models: Development and Refinement Changyong He, Yibin Yao, Dong Zhao, Ke Li and Chuang Qian
Abstract The atmospheric weighted mean temperature Tm plays a pivotal role in remote sensing water vapor with GNSS technique. However, real-time Tm cannot be obtained at given place due to limitation of modern technology. In order to remove this barrier, a global and season-specific Tm model (GWMT-I) based on spherical harmonics analysis was built using land radiosonde data. Combining Global Pressure and Temperature (GPT) model with the Bevis formula to provide virtual Tm observation at sea, a modified Tm model (GWMT-II) was presented aimed to improve the accuracy of GWMT-I in the ocean areas. Thereafter, the third generation Tm (GWMT-III) model, derived from GGOS Atmosphere surface global grid Tm data, came into existence. But on the one hand, these three models fail to accurately describe vertical Tm variation. On the other hand, they are expanded into spherical harmonics up to degree and order nine which may impose restriction to their precision. This paper reconstructs the latest model (GWMT-IV) with 4D global NCEP/DOE 2 Reanalysis data from 2005 to 2009. Comparison of result between 2010 NCEP2 data and the GWMT-IV model shows that it achieves high accuracy all over the world and its modeling method better conforms to reality.
Keywords GNSS meteorology Weighted mean temperature GWMT models GWMT-IV model
C. He (&) Y. Yao D. Zhao School of Geodesy and Geomatics, Wuhan University, Wuhan, China e-mail: [email protected]@qq.com K. Li College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China C. Qian GNSS Research Centre, Wuhan University, Wuhan, China
J. Sun et al. (eds.), China Satellite Navigation Conference (CSNC) 2013 Proceedings, Lecture Notes in Electrical Engineering 244, DOI: 10.1007/978-3-642-37404-3_40, Ó Springer-Verlag Berlin Heidelberg 2013
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40.1 Introduction Water vapor is a vital component of Earth atmosphere playing a crucial role in globally atmospheric radiation, hydrological cycle and energy equilibrium. Remotely measuring the Precipitable Water Vapor (PWV, the height of an equivalent column of liquid water) [1] is a staple part for forecasting short-term rainstorm and Meiyu season [2], for improving numerical weather prediction [3, 4], for studying tempo-spatial distribution and diurnal variations of PWV [5], for monitoring severe weather events including thunderstorms, hail stones, strong wind and hurricanes [6] and for studying global climate change [7]. The tropospheric zenith total delay (ZTD) is firstly estimated in remote sensing PWV with GPS technology. The zenith ‘wet’ delay (ZWD), which is mainly contributed to the water vapor in the atmosphere, can be separated from ZTD by Saastamoinen model with measured air pressure [8]. The relationship between ZWD and PWV is presented by Askne and Nornius in 1987 which led to the ideas of detecting atmosphere wit
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