Data Fusion of GEO FY4A GIIRS and LEO Hyperspectral Infrared Sounders with Surface Observations: A Hong Kong Case Study

Abstract

Abstract Hyperspectral infrared satellite observations from geostationary platforms allow for the retrieval of temperature and water vapor measurements with higher temporal and vertical resolution than was previously available. The Chinese satellite, FY-4A includes the Geostationary Interferometric Infrared Sounder (GIIRS) which has the ability to measure vertical profiles of temperature and water vapor from space at times when ground-based upper air soundings are not available and can fill an important need in short-range weather prediction. In this study, CAPE and LI, which are used for forecasting atmospheric instability, were computed using the SHARPpy algorithm used by the NWS Storm Prediction Center. However, remote infrared and microwave sensing is lacking detailed information in the boundary layer, so the addition of the NOAA MADIS surface data may be necessary in order to get accurate temperature and moisture measurement near the surface. This study uses May 10-16, 2019 in the coastal region near Hong Kong for evaluating the use of hourly surface observations combined with satellite soundings from FY4A GIIRS at two hour intervals. The GIIRS plus MADIS surface-based CAPE and LI estimates are compared to estimates derived from low earth orbiting (LEO) SNPP and NOAA20 from NOAA, METOP from EUMETSAT, NWP reanalysis, and local radiosondes. In the case study, the two-hour sampling interval of the GIIRS geostationary sounder was able to capture the rapid transition (16 hours) from stable to unstable atmosphere in both CAPE and LI. The use of surface observations with satellite soundings gave mixed results, possibly due to the complex terrain near Hong Kong.