Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States

As a part of the World Meteorological Organization (WMO) Global Observing System, HIRAS-1 and HIRAS-2’s observations’ impact on improving accuracy numerical weather prediction (NWP) can be summarized into two questions: (1) Will HIRAS observation help NWP system to improve its accuracy? (2) Which instrument has greater NWP? To answer questions, four experiments are designed here: (I) experiment, which assimilates principal component (PC) scores derived from radiance FY-3D satellite; (II) HIRAS-2 (onboard FY-3E satellite) radiance-observation-derived PC scores; (III) J-01 JPSS1 CrIS (IV) control experiment. Each experiment generated series forecasts with 24 h lead-time 16 March 2022 12 April using Unified Forecast System Short-Range Weather application. evaluation radiosonde aircraft reveals: (a) for upper-level variables (i.e., temperature specific humidity), assimilating NWP’s performance by decreasing standard deviation (Stdev) increasing anomaly correlation coefficient (ACC); (b) according multi-category Heidke skill score, assimilation experiments, especially have higher agreement hourly precipitation observations; (c) based tornado-outbreak case studies, occurred 30 5 2022, increase predicted intensity 0–1 km storm relative helicity decrease height lifted condensation level at tornado outbreak locations; (d) compared CrIS, still room improvement.