Estimation of precipitable water from the thermal infrared hyperspectral data

Total precipitable water (TPW) is an important atmospheric parameter in many applications. A method was proposed to estimate TPW from thermal infrared hyperspectral data. First, 21 channel groups were selected to retrieve TPW. Then, two indices, namely, the differenceand the ratio-depth in each channel group, were used as the measurement of the water vapor absorption. By multivariate regression, the relationship between the TPW and the indices was established. Finally, this relationship was applied to the simulated thermal infrared hyperspectral data. Results showed that the root mean square error (RMSE) of the model is 0.102 g·cm^-2, and the relative error is 8.1%. The proposed method needs to be further refined in the future work, including the complete elimination of the Earth´s emission in the retrieval.