Topic: Improvement of Land Surface Simulation based on Multi-source Observation Assimilation

Time: 14:00-15:30, May 24, 2024

Venue: S927, Mong Man Wai Technology Building, Tsinghua University

Speaker: Professor Zhao Long

Abstract: The land surface model (LSM) is a major tool for acquiring crucial regional land surface states, including soil moisture and snow cover, albeit with significant uncertainties in its estimation outcomes. Ground-based observations offer ground truth for evaluating model and satellite products, facilitating insights into land surface processes; however, their spatial coverage is limited. Conversely, multi-source satellite remote sensing enables multi-scale and multi-dimensional independent monitoring of the land surface, albeit with potential inversion errors. The integration of ground observations with multi-source satellite data represents a crucial step towards enhancing our understanding of land surface processes and improving the simulation capabilities of LSMs. This report outlines recent practices and applications of regional soil temperature and moisture observations on the Tibetan Plateau and southwestern mountainous regions over the ten-plus years, highlights the development of a multi-source land surface assimilation system aimed at enhancing land surface state estimation, and discusses advancements in optimizing LSM key parameters such as water and thermal conditions using multi-source satellite signals.

Profile of the Speaker:

Zhao Long is a Professor in the School of Geographical Sciences at Southwest University. He obtained his Bachelor's degree from the Department of Water Conservancy and Hydropower Engineering at Tsinghua University in 2008. Subsequently, in 2013, he completed his Ph.D. at the Tibetan Plateau Institute of the Chinese Academy of Sciences, where he was awarded the Dean's Award of the Chinese Academy of Sciences. From 2013 to 2017, Dr. Zhao pursued postdoctoral research at the University of Texas at Austin. His primary research interests encompass land surface process observation, simulation, and satellite data assimilation. He has an impressive publication record, with over 50 articles in prestigious journals such as National Science Review (NSR) and Remote Sensing of Environment (RSE). Dr. Zhao has led four national, provincial, and ministerial research projects and developed the "Multi-source Remote Sensing-based Land Model Parameter Optimization and Data Assimilation System (MDAS)." His contributions to the field have significantly advanced the understanding and modeling of land surface dynamics.