Xiaoning Song

University of Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Dr. Xiaoning Song is a leading researcher in satellite remote sensing, with a primary focus on atmospheric water vapor retrieval and land surface parameter estimation. His most cited work, "An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data" (2016, 24 citations), introduced a novel passive microwave-based algorithm that estimates precipitable water vapor (PWV) over land without requiring land surface temperature (LST) data. This breakthrough simplifies the retrieval process by relying on two key assumptions, enabling more robust and widely applicable PWV measurements—a critical variable for understanding weather patterns, climate dynamics, and hydrological cycles. Dr. Song’s contributions advance the accuracy and accessibility of satellite-derived atmospheric data, supporting applications in meteorology, climate modeling, and water resource management. His work demonstrates a commitment to solving complex remote sensing challenges, making him a valuable resource for students and researchers exploring innovative methods for environmental monitoring from space.