Observations of precipitable water vapor (PWV) in the atmosphere play a crucial role in weather forecasting and global climate change research. Spaceborne Interferometric Synthetic Aperture Radar (InSAR), as a widely used modern geodetic technique, offers several advantages to the mapping of PWV, including all-weather capability, high accuracy, high resolution, and spatial continuity. In the process of PWV retrieval by using InSAR, accurately extracting the tropospheric wet delay phase and obtaining a high-precision tropospheric water vapor conversion factor are critical steps. Furthermore, the observations of InSAR are spatio-temporal differential results and the conversion of differential PWV (InSAR ΔPWV) into non-difference PWV (InSAR PWV) is a difficulty. In this study, the city of Jinan, Shandong Province, China is selected as the experimental area, and Sentinel-1A data in 2020 is used for mapping InSAR ΔPWV. The method of small baseline subset of interferometry (SBAS) is adopted in the data processing for improving the coherence of the interferograms. We extract the atmosphere phase delay from the interferograms by using SRTM-DEM and POD data. In order to evaluate the calculation of hydrostatic delay by using the ERA5 data, we compared it with the hydrostatic delay calculated by the Saastamoinen model. To obtain a more accurate water vapor conversion factor, the value of the weighted average temperature T_m was calculated by the path integral of the ERA5. In addition, GNSS PWV is used to calibrate InSAR PWV. This study demonstrates a robust consistency between InSAR PWV and GNSS PWV, with a correlation coefficient of 0.96 and a root-mean-square error (RMSE) of 1.62 mm. In conclusion, our method ensures the reliability of mapping PWV by using Sentinel-1A interferograms and GNSS observations.

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.