All‐sky <scp>FY4B</scp> ‐ <scp>GIIRS</scp> infrared hyperspectral satellite data assimilation in the <scp>CMA</scp> ‐ <scp>GFS 4DVar</scp> system. Part <scp>II</scp> : Evaluation

Abstract This study, the second in a two‐part investigation, assesses the impact of assimilating all‐sky hyperspectral infrared observations from the FY4B Geostationary Interferometric Infrared Sounder (GIIRS) within the China Meteorological Administration‐Global Forecast System (CMA‐GFS) four‐Dimensional Variational (4DVar) framework. Building on Part I, which addresses non‐Gaussian Observation‐minus‐Background (O − B) distributions, interchannel correlations, and model hydrometeor biases, this work (Part II) focuses on evaluating forecast impacts using single‐point observation experiments, typhoon case studies, and cycling assimilation experiments. Results show that cloud effects significantly alter the Jacobians of water vapor channels under all‐sky conditions, reducing vertical sensitivity and increasing interchannel similarity. Nevertheless, all‐sky assimilation improves humidity analysis, especially in the upper troposphere, with regional improvements over East Asia (˜2%) exceeding the global average (˜0.6%). Positive impacts are also observed in typhoon track forecasts, though changes in wind speed, center pressure and precipitation are limited. While short‐term global forecasts (within 72–120 hours) show nearly neutral effects, benefits emerge in the medium range (120–240 hours). All‐sky assimilation extends the skillful forecast (defined by anomaly correlation coefficient &gt;0.6 for 500‐hPa geopotential height) by approximately 0.18 days, substantially more than the 0.03 days gain from clear‐sky assimilation. These findings represent a crucial first step toward transitioning from clear‐sky to all‐sky assimilation of hyperspectral infrared data in CMA‐GFS.