Region-Specific and Weather-Dependent Characteristics of the Relation between GNSS-Weighted Mean Temperature and Surface Temperature over China

Abstract

Weighted mean temperature of the atmosphere, Tm, is a key parameter for retrieving the precipitable water vapor from Global Navigation Satellite System observations. It is commonly estimated by a linear model that relates to surface temperature Ts. However, the linear relationship between Tm and Ts is associated with geographic regions and affected by the weather. To better estimate the Tm over China, we analyzed the region-specific and weather-dependent characteristics of this linear relationship using 860,054 radiosonde profiles from 88 Chinese stations between 2005 and 2018. The slope coefficients of site-specific linear models are 0.35~0.95, which generally reduce from northeast to southwest. Over southwest China, the slope coefficient changes drastically, while over the northwest, it shows little variation. We developed a Ts∼Tm linear model using the data from rainless days as well as a model using the data from rainy days for each station. At half the stations, mostly located in west and north China, the differences between the rainy-day and rainless-day Tm models are significant and larger than 0.5% (1%) in mean (maximal) relative bias. The regression precisions of the rainy-day models are higher than that of the rainless-day models averagely by 28% for the stations. Radiosonde data satisfying Tm−Ts>10 K and Ts−Tm>30 K most deviate from linear regression models. Results suggest that the former situation is related to low surface temperature (280 K) and a distinct humidity inversion above 600 hPa.

Keywords

• GNSS meteorology
• weighted mean temperature of atmosphere
• linear relation
• weather dependence
• site-specific model
• radiosonde data