Impact of Assimilating Geostationary Interferometric Infrared Sounder Observations from Long- and Middle-Wave Bands on Weather Forecasts with a Locally Cloud-Resolving Global Model

The Geostationary Interferometric InfraRed Sounder (GIIRS) provides a novel opportunity to acquire high-spatiotemporal-resolution atmospheric information. Previous studies have demonstrated the positive impacts of assimilating GIIRS radiances from either long-wave temperature or middle-wave water vapor bands on modeling high-impact weather processes. However, the impact of assimilating both bands on forecast skill has been less investigated, primarily due to the non-identical geolocations for both bands. In this study, a locally cloud-resolving global model is utilized to assess the impact of assimilating GIIRS observations from both long-wave and middle-wave bands. The findings indicate that the GIIRS observations exhibit distinct inter-channel error correlations. Proper inflation of these errors can compensate for inaccuracies arising from the treatment of the geolocation of the two bands, leading to a significant enhancement in the usage of GIIRS observations from both bands. The assimilation of GIIRS observations not only markedly reduces the normalized departure standard deviations for most channels of independent instruments, but also improves the atmospheric states, especially for temperature forecasting, with a maximum reduction of 42% in the root-mean-square error in the lower troposphere. These improvements contribute to better performance in predicting heavy rainfall.