A record-breaking extreme rainstorm occurred in Henan Province of China on 20 July 2021. To investigate the impacts of the Geostationary Interferometric Infrared Sounder (GIIRS) data assimilation on model analysis and forecasts of this rainfall event, the high temporal resolution GIIRS water vapor (WV) channel data were assimilated in the high-resolution CMA-MESO (Mesoscale Weather Numerical Forecast System of China Meteorological Administration) in this study. The results showed that the GIIRS WV radiance assimilation could improve the model WV analysis, which in turn adjusted the distributions of hydrometeors (radar composite reflectivities) and wind field, and finally improved the precipitation forecast. Additionally, although barely any GIIRS observations were assimilated over the cloudy area, the precipitation forecast errors of “21·7” extreme rainstorm events could be reduced by improving the structure of atmospheric circulations through the assimilation of neighboring data around Henan, especially over the upstream region. With the GIIRS WV data assimilation, the location error of maximum 24-h accumulated precipitation forecasts decreased from 128.48 km to 28.97 km (improved by 77.45%) for the cold start at 0000 UTC (Universal Time Coordinated) on 19 July 2021, and it was also reduced by about 60.52% for the warm start experiment at 0600 UTC on 19 July 2021. In addition, the GIIRS assimilation experiment showed an extraordinarily heavy rainfall area (above 250 mm/24 h) around Zhengzhou station, which did not appear in the control experiment, and was closer to the observed extreme precipitation. This study demonstrates the potential value of geostationary hyperspectral infrared sounders data assimilation in extreme weather early warning and forecasting.

The accurate forecasting of time, intensity, and spatial distribution is fundamental to weather prediction. However, the limitations of numerical weather prediction (NWP) models, as well as uncertainties in inital conditions, often lead to temporal biases in forecasts. This study addresses these biases by employing visible reflectance data from the Himawari-9/AHI satellite and RTTOV (TOVS radiation transfer) simulations derived from CMA-MESO model outputs. The time-shift method was applied to analyze two precipitation events—20 October 2023 and 30 April 2024—in order to assess its impact on precipitation forecasts. The results indicate the following: (1) the time-shift method improved cloud simulations, necessitating a 30 min advance for Case 1 and a 3.5 h delay for Case 2; (2) time-shifting reduced the standard deviation of observation-minus-background (OMB) bias in certain regions and enhanced spatial uniformity; (3) the threat score (TS) demonstrated an improvement in forecast accuracy, particularly in cases exhibiting significant movement patterns. The comparative analysis demonstrates that the time-shift method effectively corrects temporal biases in NWP models, providing forecasters with a valuable tool to optimize predictions through the integration of high-temporal- and spatial-resolution visible light data, thereby leading to more accurate and reliable weather forecasts.

Actual Spectral Response Function (SRF) of quadruple-sideband channel of microwave sounder is axisymmetrical, and its distortion degree affects the difference of observations between actual microwave sounder and ideal design situation. Effects of actual quadruple-sideband channel’s SRF on observations has been evaluated by applying actual SRF of quadruple-sideband channel of FengYun-3D (FY-3D) MicroWave Temperature Sounder -2 (MWTS-2) and rapid Radiative Transfer Model (RTM) of China Meteorological Administration-Global Forecast System (CMA-GFS). Compared with ideal SRF, actual SRF could improves microwave-radiance simulation, the observation-minus-background could be decreased about 0.7 K. The improvements in the mid-high latitudes of south hemisphere are more evident than other latitudes. Effects of distortion types of actual SRF on observations has been analyzed by comparing simulated radiance differences between reference SRF and originally proposed SRFs with eight typical distortion types. Inner sideband drifting type and outer sideband drifting type have the greatest influence of about 1K on microwave radiance. Inner-outer sideband symmetrical difference type has the least impact of approximately 0.02K. Effects of the axisymmetry of SRF on observations has also been evaluated. Compared microwave radiance simulation by reference SRF with axisymmetrically and non-axisymmetrically distorted SRFs respectively, simulation errors induced by axisymmetrically distorted SRFs are less than by non-axisymmetrically distorted SRFs of about 0.1K to 0.4 K.