Fengyun-3E, which is equipped with MicroWave Humidity Sounder 2 (MWHS-2) for detecting both temperature and humidity, is China’s latest polar orbiting meteorological satellite and China’s first satellite in early-morning orbit. The observation bias and observation error characteristics of MWHS-2 are evaluated by using ERA-5 as the background field. The results show that the biases range from −4 to 2 K, and the observation errors are within 1.5 K except for the window channels. A further analysis of the dependence on the scanning angles indicates that observation errors for the window channels and the 118-GHz channels increase with decreasing scanning angles. Observation errors of the window channels and water vapor channels are also latitudinally dependent, and the maximum errors in the high latitudes reach 2.0 K, while those in the tropical regions are approximately 0.8 K. In addition, the observed brightness temperature of FY-3E MWHS-2 is accompanied by striping noises along the track and high-frequency oscillation noises along the scanlines. The noise mitigation results show that both noises are approximately 0.2 K.

On 5 July 2021, China launched the world’s first early morning orbit meteorological satellite, which was equipped with China’s newest-generation microwave instrument, the Microwave Temperature Sounder-3 (MWTS-3). MWTS-3 has 17 detection channels, which can detect temperature profiles from near the ground to approximately 2 hPa. However, similar to the newest-generation microwave temperature instruments in other countries, MWTS-3 may also suffer from striping noise. In this paper, a principal component analysis (PCA) is combined with ensemble empirical mode decomposition (EEMD) to extract the striping noise from the brightness temperatures observed by MWTS-3, and a comparative analysis is performed with its predecessor (MWTS-2). This paper analyzes the characteristics of the striping noise of both instruments and its possible impact on their observations. The results show that the striping noise of MWTS-3 has been significantly reduced in most of the 17 channels. In particular, the striping noise of MWTS-3’s channel 3 is reduced by nearly half compared to the channel of MWTS-2 with the same frequency. Furthermore, the interchannel correlations for MWTS-3 are significantly lower than those for MWTS-2. After noise mitigation, the interchannel correlations of both MWTS-2 and MWTS-3 are obviously reduced. In addition, striping noise mitigation can reduce observation errors to some extent, especially for channels above the middle troposphere.

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 improve the assimilation accuracy of satellite microwave observations, it is necessary to conduct precipitation detection before assimilation and exclude the data contaminated by the scattering of hydromorphic particles. The induction of microwave scattering is closely related to the effective radius of hydromorphic particles, and the motion state of hydromorphic particles at different scales can directly affect the internal dynamic structure of clouds, which will lead to precipitation. To further analyze and validate the impact of microwave scattering in a precipitation environment on the assimilation of satellite microwave soundings within the temperature-sensitive band, this paper utilized the on-orbit observations of Microwave Temperature Sounder -III (MWTS-III) and Medium Resolution Spectral Imager (MERSI) onboard the Fengyun-3E (FY-3E) satellite to achieve multispectral fusion observation and precipitation detection over oceans, combined with the vertical dynamic characteristics of global numerical forecast in the cloud environment of China Meteorological Administration (CMA) Global Forecast System (CMA-GFS). By conducting the dynamic analysis of the hydrometeors in the cloud, the maximum possible effective particle radius of hydromorphic particles under the no-phase-transition condition and internal vertical motion is obtained. The consistency of the cloud liquid water path (CLWP) retrieved by MWTS-III and multispectral fusion precipitation detection is evaluated subsequently. The results show that the distribution of hydrometeors in the CMA-GFS forecast is broadly in line with the CLWP distribution obtained from the MWTS-III retrieval, regardless of Mie scattering or Rayleigh scattering. However, compared with Mie scattering, the weak convection of CMA-GFS shows better adaptability in the Rayleigh environment.

Fine spectrum refines conventional spectral sounding channels by increasing the spectral resolution to improve further the vertical resolution for accurate detection of atmospheric parameters. The 50-60 GHz absorption band is mainly used to sound the vertical distribution of atmospheric temperature in the troposphere and stratosphere, and 53 GHz is located in the weak oxygen absorption line. FY-3E MWTS-III has two sounding channels added to this absorption band, and initially realized the refinement of the sampling channels. In this paper, by establishing the assimilation operator for the radiance data of MWTS-III in CMA-GFS 4D-Var, and using the in-orbit observations from FY-3E MWTS-III, we investigate the impact of refining sounding channels at 53 GHz on numerical weather prediction. Results show that the temperature increment has the largest value and the widest influencing area near the peak weighting functions of channels, and the intensity and range of the temperature increment also change as the number of assimilated channels increases. An increment index can help quantify the impact of channel refinement on the forecast field. After single-cycle assimilation, the RMSE of atmospheric parameters in the analysis field shows a decreasing trend. After continuous assimilation, the RMSE of geopotential height has a positive effect on short-term forecasts as the number of assimilated channels increases. It can be seen that channel refinement at 53 GHz positively impacts the performance of numerical weather prediction.