New Models for Vertical Distribution and Variation of Tropospheric Water Vapor—A Case Study for China

Abstract

For better modeling the vertical distribution and variations of water vapor, a 10-year time-series of a newly derived water vapor parameter (termed IRPWV), defined as the ratio of water vapor density (WVD) to the total precipitable water vapor (TPWV), was statistically analyzed. This research showed that the vertical distribution of IRPWV presents a periodic pattern and is highly correlated with the relative magnitude of its corresponding TPWV when compared with the other TPWVs in the same time range. Six TPWV ranges were first chosen to determine the relative magnitude and then used to classify the IRPWV vertical distributions of TPWV. For the periodic variations in each of the six classified IRPWV vertical distribution time-series, a temporal IRPWV model was developed accordingly with six sets of coefficients. The new models were validated by comparing their predictions against the reference values from sounding data at 12 radiosonde stations in China, and their performance was also evaluated against that of the commonly used exponential model. Results showed that, first, the proportions of the height range that had reduced annual root mean square error (RMSE) of WVD in all height ranges within all TPWV ranges were over 75% at the 12 stations. Then, the annual RMSEs of the WVD for all the stations were reduced by at least 11%, 20%, 43%, 48%, 40%, 38%, 32%, 35%, 32%, and 28% in each of the 10 selected height ranges, respectively.