Prior to assimilating hyperspectral infrared data on the FengYun (FY) satellite in the numerical weather prediction (NWP) system, it is necessary to identify the quality and bias characteristics of these data, especially as China’s first early-morning-orbit satellite data. Using the numerical model CMA-GFS (China Meteorological Administration Global Forecast System) and the observation of FY-3E HIRAS-II (Hyperspectral Infrared Atmospheric Sounder-II), the differences between observed and simulated brightness temperatures (O-Bs) are comprehensively analyzed, with a focus on evaluating the long-wave (LW) temperature sounding channels of HIRAS-II observation in the clear sky. The results show that the O-Bs in the LW channels are between ±1.0 K, except for the ${\mathrm{C}\mathrm{O}}_2$ absorption line peak at 667 ${\mathrm{c}\mathrm{m}}^{-1}$. Only a tiny variation in O-Bs, with relative consistency, could be observed during the day, the line of dawn and dusk, and night. The difference in the standard deviations of O-Bs in the three cases is less than 0.1 K. The O-Bs of two typical channels (channels 14 and 47) in the stratosphere have disturbances at individual times, whereas the O-Bs are much more stable in time series in the tropospheric channels. The O-Bs in different channels show the characteristics of changing with the latitude, but the bias and standard deviations of O-Bs during the ascending and descending stages are not much different, except for the bias of channel 47 in low latitude. The optimal ranking of Fields of View (FOVs) in assimilation is derived from a priori analysis of O-Bs. The results demonstrate that FOV4 and FOV5 are the best in a Field of Regard (FOR) compared to all LW channels of HIRAS-II in constructions of their O-Bs and magnitude of O-B standard deviations, and they can be used as the preferred FOVs for assimilation. While the O-Bs in FOV1 and FOV2 are slightly larger, the O-Bs’ characteristics also meet the assimilation requirements and can be used as assimilation FOVs in HIRAS-II LW channels after FOV4 and FOV5 lose their efficacy.

Fine spectral detection can basically solve the problem of low vertical resolution at the 183 GHz water-vapor absorption line, and it is expected to become one of the main methods for next-generation geostationary and polar-orbiting satellites. Here, using data from Microwave Humidity Sounder II (MWHS-II) onboard the Chinese Fengyun 3D (FY-3D) satellite in the Global/Regional Assimilation and Prediction System (GRAPES) Four-Dimensional Variational (4D-Var) system of the China Meteorological Administration (CMA), we explore the assimilation application of the water-vapor absorption line at 183.31 ± 1 GHz, 183.31 ± 3 GHz and 183.31 ± 7 GHz, as well as 183.31 ± 1.8 GHz and 183.31 ± 4.5 GHz, two added channels, to assess the impact of adding the 183.31 ± 1.8 GHz and 183.31 ± 4.5 GHz sampling channels on data assimilation and numerical weather prediction. Our findings reveal a significant increase in the specific-humidity increment, which in the middle–upper troposphere is numerically much larger than in the lower troposphere. Specifically, the assimilation of 183.31 ± 1.8 GHz observations, positioned near the center of the water-vapor absorption line, results in a pronounced adjustment compared with the 183.31 ± 4.5 GHz observations. And under the strong constraint of the numerical model, the Root Mean Square Error (RMSE) of the wind field diminishes more significantly (by an average of 2–4%) after assimilating the water-vapor observations at greater heights.

To make better use of microwave radiance observations for data assimilation, removal of radiances contaminated by hydrometeor particles is one of the most important steps. Generally, all observations below the middle troposphere are eliminated before the analysis when precipitation is present. However, the altitude of the cloud top varies; when the weighting function peak height of a channel is higher than the altitude of the cloud top, observations are not affected by the absorption or scattering of cloud particles. Thus, the radiative transfer calculation can be performed under a clear sky scenario. In this paper, a dynamic channel selection (DCS) method was developed to determine the radiance observations unaffected by clouds under cloudy conditions in assimilation. First, the sensitivity of cloud liquid water (CLW) profiles to radiance from the microwave temperature sounding frequencies was analyzed. It was found that the impact of CLW on transmittance can be neglected where the cloud top height is below the weighting function peak height. Second, three lookup tables were devised through analysis of the impact of cloud fraction and cloud top height on radiance, which is the basis of the DCS method. The unified cloud top height of the Microwave Temperature Sounder (MWTS)-2 fields of view (FOVs) can be calculated by remapping the cloud mask and cloud top height data from the Medium Resolution Spectral Imager-2 (MERSI-2). Observations from various channels may be removed or retained based on real-time dynamic unified cloud top height data. Twelve-hour and long-term time-series brightness temperature simulation experiments both showed that an increase in the amount of observations used for data assimilation of more than 300% can be achieved by application of DCS, but this had no effect on the amount of error. Through DCS, areas of strong precipitation can be accurately identified and removed, and more observations above cloud top height can be included in the data assimilation. The application of DCS to data assimilation will greatly improve the data utilization rate, and therefore allow for more accurate characterization of upper atmospheric circulation.

Microwave hyperspectral instruments represent one of the main atmospheric sounders of China’s next-generation Fengyun meteorological satellites. In order to better apply microwave hyperspectral observations in the fields of atmospheric parameter retrieval and data assimilation, this paper analyzes the sensitivity of trace gases to five selected bandwidth channels using a radiative transfer model based on the simulated data of microwave hyperspectral radiances at 50–60 GHz. This method uses information entropy and a weighting function to select channels and analyze the impact of this on the retrieval accuracy of atmospheric profiles before and after channel selection. The experimental results show that channel selection can reduce the number of channels by approximately 74.05% while maintaining a large amount of information content, and this retrieval effect is significantly better than that of MWTS-III. After channel selection, the 10 MHz, 30 MHz, and 50 MHz bandwidths have the best retrieval results in the stratosphere, whole atmosphere, and troposphere, respectively. When considering the number of channels, computational scale, and retrieval results comprehensively, the channel selection method is effective.