Water vapor constitutes a vital component of atmospheric precipitation, serving as the fundamental material basis for weather phenomena such as rainfall, and is a significant factor contributing to extreme weather events. The Weighted Mean Temperature (Tm) is a crucial factor in the calculation of Precipitable Water Vapor (PWV) in the atmosphere, directly impacting the quality of GNSS-PWV inversion. The Tm_N, Tm_L1, and Tm_L2 models were constructed through regression analysis and LSTM based on data from the Zhangqiu Radiosonde Station in the Jinan region from 2020 to 2022, as well as ERA5 data. The six Tm models (Tm_N, Tm_L1, Tm_L2, Bevis, GTm, and GPT3) were analyzed by comparing them with the Tm value from the Radiosonde station in 2023. Compared with the Bevis, GTm, and GPT3 models, the accuracy of Tm_N was improved by 24%, 19%, and 45%, Tm_L1 was improved by 20%, 16%, and 42%, and Tm_L2 was increased by 34%, 29%, and 52%. The influence of the above six Tm models on GNSS-PWV accuracy was analyzed using both theoretical and experimental methods. It was demonstrated that the impact of Tm_L1 and Tm_L2 on the accuracy of the PWV solution is significantly enhanced in comparison with the other Tm models. The Tm_L1 and Tm_L2 models developed in this study offer enhanced accuracy for Tm data utilized in GNSS PWV inversion within the Jinan region.

Precipitable water vapor (PWV) is a pivotal parameter in the measurement of atmospheric water vapor content. Interferometric Synthetic Aperture Radar (InSAR) is capable of retrieving PWV with high accuracy and spatial resolution. However, the limitations imposed by factors such as low coherence and phase distortion prevent the monitoring of PWV over the sea surface by InSAR. For this problem, a joint InSAR/Fengyun sea–land cooperative PWV construction method is proposed using constraints from the Global Navigation Satellite System (GNSS) and ERA5 reanalysis data. The Jiaodong Peninsula of China was selected as the research area. The PWV over the land of the Jiaodong Peninsula was obtained by GNSS/ERA5/InSAR. The PWV over the nearby sea was obtained by Fengyun-4A (FY-4A). The PWV reconstruction over the sea and land region is realized by means of unified reference correction and transition processing. The results indicate that InSAR PWV and FY-4A PWV show good agreement with GNSS PWV, with R², MAE and RMSE values of 0.955, 1.86 mm and 2.32 mm for InSAR PWV, and 0.961, 1.90 mm and 2.28 mm for FY-4A PWV, respectively. The fused PWV significantly improves spatial completeness while preserving fine spatial structures, with an annual PWV range of 0.35–59.74 mm and a clear seasonal cycle from 4.16 mm in winter to 33.24 mm in summer. The results effectively capture the coastal moisture transition, with the strongest PWV gradient reaching 0.823 mm/km in the 0–10 km coastal zone during the warm season. PWV also shows the strongest correlation with dew point, with a Spearman correlation coefficient of 0.94. This study overcomes the limitation that PWV is restricted to land areas and provides reliable data support for the analysis of water vapor structures in coastal regions.