An empirical atmospheric weighted mean temperature model considering the lapse rate function for China

doi:10.11947/j.AGCS.2020.20190168

Abstract

Abstract: The atmospheric weighted mean temperature, T_m, plays an important role in the process of retrieving precipitable water vapor from Global Navigation Satellite System (GNSS) signals. Aiming at the characteristics of complex terrain in China,we develop a T_m lapse rate function that considering sophisticated seasonal variations, and then a new grid T_m model for China, named as CT_m, is established using gridded T_m data over an 8-year period from 2007 to 2014 provided by the global geodetic observing system (GGOS) atmosphere.Both gridded T_m data and radiosonde profiles from 2015 are treated as reference values to assess the performance of CT_m. The results are compared with the Bevis formula and the GPT2w model. The results show that the CT_m with the annual bias and RMS error of -0.52 K and 3.28 K when compared with gridded T_m data, respectively. In terms of RMS,the CT_m has improved by approximately 27% and 13% against GPT2w-5 and GPT2w-1, respectively. While the CT_m has the annual bias and RMS error of 0.26 K and 3.75 K against radiosonde data, and which has improved by approximately 21% and 16% against GPT2w-5 and GPT2w-1, respectively,especially in Western China, where the significant performance was observed for CT_m. Besides, the CT_m has RMS_PWV and RMS_PWV/PWV values of 0.29 mm and 1.36% when used to estimate GNSS-PWV. The CT_m model does not require any in situ meteorological parameters, thus, which has potential application for high-precision real-time GNSS-PWV retrieving in China.

Key words: CT_m model, lapse rate function, GNSS precipitable water vapor, China area

CLC Number:

P227

HUANG Liangke, PENG Hua, LIU Lilong, LI Chen, KANG Chuanli, XIE Shaofeng. An empirical atmospheric weighted mean temperature model considering the lapse rate function for China[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(4): 432-442.

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