Development and Assessment of an ALLSSA‐Based Atmospheric Weighted Mean Temperature Model With High Time Resolution for GNSS Precipitable Water Retrieval. Issue 2 (10th February 2022)

• Record Type: Journal Article
• Authors: Ma, Yongchao; Chen, Peng; Liu, Tong; Xu, Guochang; Lu, Zhiping
• Is Part Of: Earth and space science. Volume 9:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-10
• Subjects: Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2021EA002089
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: The atmosphere weighted mean temperature, Tm, is an essential parameter for retrieving precipitable water from the ground‐based Global Navigation Satellite Systems (GNSS). The accuracy of high temporal resolution GNSS precipitable water vapor (PWV) estimation requires wideband Tm information and its magnitude. However, existing Tm empirical models use trigonometric functions with only fixed amplitude and low‐frequency for time fitting, which limits real‐time or near real‐time PWV retrieval from GNSS observation. Thus, an improved Tm model for China, LTCm, containing more frequency information of Tm, based on the antileakage least‐squares spectrum analysis by utilizing the ERA5 pressure‐level products during the years 2015–2019, is developed. Both Tm data from ERA5 pressure‐level products and radiosonde stations distributed in China over 2020 are selected as reference values to verify the performance of the LCTm model. The results show that the LCTm model yields significant performance against other models in Tm estimation over China, especially in marine regions and high‐altitude areas. Furthermore, the LCTm model can generally achieve a mean Bias/root mean square (RMS) of −0.33 K/2.06 K in contrast to ERA5 pressure‐level products and 0.03 K/3.47 K in comparison with radiosonde, which corresponds to a 7.2%–13.8% improvement against GPT2w, GTm‐III, and Bevis. Moreover, LCTm has σ pwv and σ pwv / PWV values of 0.27 mm and 1.25% when used to retrieve GNSS‐PWV, respectively. Consequently, the LCTm model that considers high‐frequency information of Tm can obtain more reliable Tm values. Therefore, the LCTm model can be applied to real‐time or near real‐time GNSS PWV retrieval, which is of great significance for GNSS meteorological research. Key Points: An advanced grid model based on antileakage least‐squares spectral analysis for estimating weighted mean temperature over China is built The performances of the new model, GPT2w, GTm‐III, and Bevis models are assessed under different data sources, and the impact of each model on GNSS PWV is evaluated The new model can reflect the complex changes of weighted mean temperature in a short time and has a prospective application in real‐time or nowcasting extreme weather forecasting