STCFCM: A Spatial and Temporal Cloud Fraction-Based Calibration Method for Satellite-Derived Near-Infrared Water Vapor Product

Precipitable water vapor (PWV) data from satellite-sensed near-infrared (NIR) measurements offer a unique source for monitoring atmospheric water vapor distribution locally and globally. However, the observational quality of satellite-based operational NIR PWV products is considerably affected by the presence of clouds. We develop a spatial and temporal cloud fraction-based calibration method (STCFCM) to calibrate satellite-sensed NIR PWV products and improve PWV accuracy. The STCFCM is built based on a light gradient boosting machine (LightGBM) using cloud fraction, together with spatial–temporal fields—latitude, longitude, height, and month. The newly calibrated PWV estimates from the MODIS sensor onboard the Terra satellite show that the STCFCM-estimated PWV data exhibit a better agreement with reference PWV estimates from global navigation satellite system (GNSS) and radiosonde observations. The root-mean-square error (RMSE) of MODIS/Terra operational PWV products is reduced by 55.53% from 11.40 to 5.07 mm compared to GNSS PWV and 60.74% from 14.67 to 5.76 mm compared to radiosonde PWV. The calibrated all-weather PWV estimates outperform operational clear-sky PWV products, highlighting the effectiveness of the STCFCM in calibrating satellite-sensed NIR PWV retrievals, particularly for cloudy sky conditions. The newly developed STCFCM approach is the first one in the research community to calibrate global PWV data from satellite NIR measurements. It is a promising technique to calibrate remote-sensing PWV products from other satellite observations under all weather conditions.