Title: A GNSS-based Novel Approach to Recover FY-3B Satellite Precipitable Water Vapor (PWV) Data and an Experiment to Assimilate Satellite-based Near-Infrared PWV into NWP
Lecturer: Zhizhao Liu, The Hong Kong Polytechnic University
Time: Tuesday December 5, 2023 at 4:00 PM
Venue: Lecture Hall D103, School of Atmospheric Sciences, Xianlin Campus
Abstract: The Medium Resolution Spectral Imager (MERSI) near-infrared (NIR) channels onboard the Chinese Fengyun-3B (FY-3B, 2010-2020) satellite are used to make precipitable water vapor (PWV) measurements. There is currently no valid PWV data available from the FY-3B satellite, which significantly affects the continuity of PWV data time series of the Chinese Fengyun mission. A novel Global Navigation Satellite System (GNSS)-based approach has been developed to successfully recover the PWV data from FY-3B. The retrieved water vapor data demonstrates an accuracy similar to that of the MODIS sensor onboard the NASA’s Aqua and Terra satellites. We will show the result of our experiment of assimilating satellite-based NIR PWV into Numerical Weather Prediction (NWP) models, i.e. the Weather Research and Forecasting (WRF) model. To the best of our knowledge, we are arguably the 2nd team in the world to assimilate NIR satellite PWV into NWP, after the U.K. Met Office which is the world’s first agency to operationally assimilate satellite NIR PWV into its global NWP since May 2022. Different from the U.K. Met Office, the NIR PWV dataset we assimilate has been calibrated using our Lab’s new approach thus it has a better accuracy. A comparison of assimilating calibrated and non-calibrated NIR PWV will be shown.