A Study of the Atmospheric Weighting Mean Temperature in Northwest Plateau of China

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Abstract:

The data from 11 meteorological radiosonde stations in 5 provinces including Shanxi, Shaanxi, Ningxia, Inner Mongolia and Hebei are divided into 9 different data collections which are used to deduce the linear regression models of atmospheric weighting mean temperature (Tm) for Ground-based GPS precipitable water vapor (PWV) retrieval. These 9 models, together with Bevis model, are used to retrieve the GPS PWV at station BGTY. In comparison with the correlations between the ground-based GPS PWV and radiosonde PWV at this station, the difference between these 10 different models of Tm is analyzed. The results show that the Bevis model of Tm can be used to retrieve the GPS PWV of the regions mentioned above. At the same time, the Tm model computed from the radiosonde measurements of specific regions and seasons can provide more accurate GPS PWV than the Bevis model.

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291-296

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October 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. Bevis, S. Businger, T.A. Herring, et a1, GPS meteorology : Remote sensing of atmospheric water vapor useing the global positioning system, J. Geophys Res .97(1992)15787-15801.

DOI: 10.1029/92jd01517

Google Scholar

[2] G.P. Li, et al, Ground_based GPS Meteorology, Science press, Beijing, 2010.

Google Scholar

[3] G.R. Xu, R. Wan, W.J. Li, et al, Improvement on the method for estimating precipitable water from ground-based GPS, J. Torrential Rain and Disasters .28(3)(2009)203-209.

Google Scholar

[4] H.M Yang, P. He, B.X. Xu, et al, Analysis of water vapor characteristics of torrential rainfall in south China with GPS data, J. Meteorological Monthly, 28 (5)(2002)17-21.

Google Scholar

[5] J. Guo, G.P. Li. Ground-based GPS in remote sensing of water vapor development and application, J.. Journal of geodesy and geodynamics, 27 (z1)(2007)35-42.

Google Scholar

[6] J.G. Li, J.T. Mao, C.C. Li. The approach to Rremote sensing of water vapor based on GPS and linear regression Tm in eastern region of China, J. Acta Meteorologica Sinica ,57(3)(1999)283-292.

Google Scholar

[7] M. Chen, S.Y. Fan, J.Q. Zhong, et al, An experimental study of assimilating the Global Position System-preeipitable water vapor observations into the rapid updated cycle system for theBeUing area, J.Acta Meteorologica Siniea, 68(4)(2010)450-463.

Google Scholar

[8] P.X. Sheng, J.T. Mao, J.G. Li. et al, Atmosphere physics. Peking university press,Beijing, 2003.

Google Scholar

[9] P. Xie, C.L. Zhang, Y.C. Wang, et al. Atmospheric water vapor experiment with the mixed single- and dual-frequency ground-based GPS-met network in Beijing ,J. Journal of applied meteorological science,17(z1)(2006)28-34.

Google Scholar

[10] J. Saastamoinen. Contributions to the theory of atmospheric refraction, J. Bull Geod, 107(1973)13-34.

Google Scholar

[11] X.W. Zhang. A relationship between precipitable water and surface vapor pressure, J. Meteorological Monthly, 30 (2)(2004)9-11.

Google Scholar

[12] Y.C Xiang, Z.H. Chen, G.R. Xu, et al, A Comparsion and analysis of the results of three methods for the calculation of water vapor resources, J. .Meteorological Monthly, 35 (11)(2009)48-54.

Google Scholar

[13] Y. Wang, B.Y. Yang, Y.P. Liu, et al, The study of the model about mean vapor pressure-weighted temperature of the atmosphere based on radiosonde , J. Science of surveying and mapping, 35(2)(2010)112-113.

Google Scholar