An Improved Algorithm for Retrieving Atmospheric Water Vapor Using MODIS Near-Infrared Data

Atmospheric water vapor plays a vital role in studying global climate change. It´s very important to accurately determine water vapor amounts (WVA) for predicting rainfalls and weather disasters. Water vapor data are also used as an input parameter in applications of satellite remote sensing. In this paper, we improved an algorithm for water vapor derivation using the Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) data above cloud-free land surfaces. The Moderate Resolution Transmittance (MODTRAN) radiation model is used to simulate the relationship between column WVA and atmospheric transmittance (AT) under various conditions. Finally, a comparison of the retrieved WVA with on-the-spot measurements shows the improved algorithm has high accuracy.