Validating TIR-Derived Total Column Water Vapor Using Sun Photometers and GPS Measurements

Total column water vapor (TCWV) is essential for assessing Earth’s radiation budget and hydrological cycle and plays a crucial role in accurate Land Surface Temperature (LST) retrieval from thermal infrared (TIR) imagery. Although TCWV is commonly estimated using near-infrared or microwave observations, TIR-based methods offer an efficient alternative; however, their long-term validation remains limited. This study evaluates TCWV retrieval from Landsat 8/9 Thermal Infrared Sensor (TIRS) using an updated version of the Modified Split-Window Covariance-Variance Ratio (MSWCVR) method, implemented on the Google Earth Engine platform, across Europe. Validation is conducted using AERONET sun photometer measurements (2013–2024) and GPS-based TCWV estimates enhanced with meteorological inputs (2020). Retrieval accuracy is evaluated analyzed in relation to seasonal variations, surface characteristics (e.g., land cover, altitude) and background climate. Results demonstrate robust performance of the TIR-based method, with an average Mean Absolute Error (MAE) of 0.6 gr/cm2 across stations and datasets, supporting its applicability for LST retrieval and broader environmental monitoring applications.