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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. [ABSTRACT FROM AUTHOR]

With the Microwave Humidity Sounder-2 (MWHS-2)/Fengyun (FY)-3D in operation, this is the first study to evaluate the impact of a joint assimilation of MWHS-2 radiances under all-sky conditions from both the FY-3C and FY-3D satellites on typhoon forecasting within regional areas. In this study, Typhoon Hagupit in 2020 was chosen to investigate the impacts of assimilating MWHS-2 radiances; the forecasting performances of the joint assimilation method were slightly better than the experiments assimilating MWHS-2 observations from FY-3C or FY-3D only, and the results of the latter two experiments were comparable, especially in terms of the landfall location of Hagupit. With additional assimilated cloud- and precipitation-affected MWHS-2 observations, improved typhoon track and intensity forecasts as well as forecasts of the precipitation caused by Hagupit were achieved due to the improved analyses of relative humidity, temperature and wind fields around Hagupit compared to the clear-sky assimilation experiments. In addition, the channel-selection scheme evidently affected the forecasting performance; that is, the radiances from the MWHS-2 118 GHz and 183 GHz channels provided opposite results in terms of the Hagupit track, and this finding needs further investigation in the future. [ABSTRACT FROM AUTHOR]

All-sky (i.e., clear, cloudy, and precipitating conditions) assimilation of microwave observations shows potentially positive impacts on the improvement of the forecasts of cloud-associated weather processes. In this study, a typical mei-yu heavy precipitation event that occurred in 2017 was investigated, and the Weather Research and Forecasting data assimilation (WRFDA) as well as its 3D-Var assimilation scheme (excluding cloud and precipitation control variables) were applied to assimilate the Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) observations under clear-sky (excluding the observations that are strongly affected by ice clouds and precipitation) and all-sky conditions. Three experiments including a control experiment without assimilating any observations, clear-sky, and all-sky experiments with only FY-3C/MWHS-2 observations assimilated were carried out. The results show that the all-sky assimilation approach that provides more cloud and precipitation information and increased more than 10% of the satellite data usage than the clear-sky experiment. Meanwhile, as compared with the control experiment, the all-sky assimilation reduced nearly 0.5% of the root mean square errors in the humidity fields, leading to more accurate forecast performances regarding the distribution and intensity of heavy rainfall; but it exhibited a neutral to negative impacts on the wind and temperature. Although the system used to conduct all-sky assimilation is only able to adjust control variables for moisture-, wind-, and temperaturerelated variables in the presence of cloud and does not benefit directly from cloud or precipitation information, the positive effects on heavy rainfall forecasts achieved in this study indicate a potential future benefit regarding disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

The dynamic emissivity retrieved from window channels of the microwave humidity sounder II (MWHS-2) onboard the China Meteorological Administration's FengYun (FY)-3C polar orbiting satellite can provide more realistic emissivity over lands and potentially improve the numerical weather prediction (NWP) forecasts. However, whether the assimilation with the dynamic emissivity works for the precipitation forecasts over the complex geography is less investigated. In this paper, a typical precipitating case generated by the Southwest Vortex is selected and the Weather Research and Forecasting data assimilation (WRFDA) system is applied to examine the impacts of assimilating MWHS-2/FY-3C with the uses of the emissivity atlas and the dynamic emissivity on the forecasts. The results indicate that the use of the dynamic emissivity retrieved from the 89 GHz channel of MWHS-2/FY-3C apparently increases the used data number for assimilation and does improve the initial fields and the 24-hour forecasts (from 0000 UTC 24 June 2016 to 0000 UTC 25 June 2016) of precipitation distribution and intensity except for the rainfall over 100 mm. But these positive impacts are not evidently better than those with the emissivity atlas. In general, these results still suggest that the future use of the dynamic emissivity in the assimilation over the complex terrain is promising. [ABSTRACT FROM AUTHOR]