The Huanjinglianzai-2 (HJ-2) series of satellites are the latest members of the Chinese Environmental Protection and Disaster Monitoring Satellite Constellation developed by China, and the first two (HJ-2A and HJ-2B) HJ-2 series satellites were launched on 27 September 2020. Each satellite is equipped with four imaging sensors, including the wide view charge-coupled device (CCD) camera, the hyper-spectral imager (HSI), the infrared multispectral scanner (IRMSS), and the polarized scanning atmospheric corrector (PSAC) [8]. The first three sensors are mainly used for surface observations, and PSAC is mainly used to monitor atmospheric components such as water vapor and aerosols. In order to remove the atmospheric interference to the data of the first three main sensors to extend their application, it is necessary to perform atmospheric correction on these data according to the atmospheric parameters including CWV [9; 10]. Because of the large temporal differences in distribution of water vapor, it is essential to use CWV data synchronous with HJ-2 satellites rather than CWV data from other satellites for high-precision atmospheric correction. In addition, since the observation time of different satellites is different, the CWV data derived from HJ-2 satellites is useful for the studies on weather forecasting and climate change. Therefore, it is of great significance to develop CWV data using PSAC data. The current remote sensing retrieval algorithms for water vapor can be classified into four categories based on the wavelength of the data used, namely, visible algorithm, near-infrared (NIR) algorithm, thermal infrared (TIR) algorithm, and microwave (MW) algorithm [11; 12; 13; 14]. Each of these algorithms has its own scope of application. Among them, the visible algorithm, TIR algorithm, and MW algorithm can be used not only for CWV retrieval over the land, but also for CWV retrieval over the ocean, while the NIR algorithm is only applicable to areas with large surface albedo, such as land and the sun-glint region of the ocean. Due to the use of data in the visible-NIR spectral range, the visible algorithm and NIR algorithm are only suitable for water vapor retrieval in the daytime, while the TIR algorithm and MW algorithm can be used for water vapor retrieval at any time. In addition, the MW algorithm can be used for water vapor detection both over cloud-free areas and over areas covered by clouds because of the strong penetration ability of microwaves, while the other three algorithms are only applicable to areas not affected by clouds. In addition to the above methods based on remote sensing image data, there are still many other methods for monitoring water vapor content. For example, radio occultation methods [15; 16] and methods for retrieving CWV by using data observed by ground stations including global positioning system (GPS) receiver, sun photometer, and radiosonde [17; 18]. In general, the accuracy of CWV data derived from ground-based observations is higher than that of CWV data derived from satellite data, but ground-based observations have difficulty monitoring water vapor on a large scale due to the limitation of the number of ground-based stations. All the above-mentioned remote sensing retrieval algorithms for water vapor have been used in the development of water vapor products for multiple sensors.