The FY-3E satellite was successfully launched on 5 July 2021 and carries on board the Microwave Temperature Sounder-III (MWTS-III). In this study, the biases of MWTS-III data with respect to simulations are analyzed according to the instrument field of view and location latitude over the Pacific region. The cloud liquid water path (CLWP) over oceans is retrieved from two new window channels at 23.8 and 31.4 GHz and is used for detecting the clouds-affected microwave sounding data. The absolute bias between the observed and simulated brightness temperature (O–B) under the clear sky point is, in general, less than 2.0 K, depending on the MWTS-III channel. The standard deviations of O-B in most channels are less 1.0 K, but they are 1–1.5 K in channels 1–4 and 17. The average and the standard deviation of O−B from the channels 1–10 shows an obvious symmetrical variation with FOV. The evaluation results all indicate good prospects for the assimilation application of FY-3E microwave sounding data.

FengYun-3E (FY-3E), the fifth satellite in China’s second-generation polar-orbiting satellite FY-3 series, was launched on 5 July 2021. FY-3E carries a third-generation microwave temperature sounder (MWTS-3). For the first time, this study demonstrates that MWTS-3 radiances data assimilation can improve the China Meteorological Administration Global Forecast System (CMA-GFS). By establishing a cloud detection module based on the retrieval results of the new channels of MWTS-3, a quality control module according to the error characteristics of MWTS-3 data, and a bias correction module considering the scanning position of satellite and weather systems, the effective assimilation of MWTS-3 data in the CMA-GFS has been realized. Through one-month cycling experiments of assimilation and forecasts, the error characteristics and assimilation effects of MWTS-3 data are carefully evaluated. The results show that the observation errors in MWTS-3 data are similar to those in advanced technology microwave sounder (ATMS) data within the same frequency channel, are slightly larger than those in the advanced microwave-sounding unit-A (AMSU-A) data, and are much better than those in the MWTS-2 data. The validation of the assimilation and prediction results demonstrate the positive contribution of MWTS-3 data assimilation, which can remarkably reduce the analysis errors in the Northern and Southern Hemispheres. Specifically, the error growth on the upper layer of the model is obviously suppressed. When all other operational satellite observations are included, the assimilation of MWTS-3 data has a neutral or slightly positive contribution to the analysis and forecast results, and the improvement is mainly found in the Southern Hemisphere. The relevant evaluation results indicate that the MWTS-3 data assimilation has good application prospects for operation.

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.

The assimilation of two surface-sensitive channels of the AMSU-A instruments on board the NOAA-15/NOAA-18/NOAA-19 and MetOp-A/MetOp-B satellites over land was achieved in the China Meteorological Administration Global Forecast System (CMA_GFS). The land surface emissivity was calculated by 1) the window channel retrieval method and 2) the Tool to Estimate Land Surface Emissivities at Microwave frequencies (TELSEM2). Quality controls for these satellite microwave observations over land were conducted. The predictors and regression coefficients used for oceanic satellite data were retained during the bias correction over land and found to perform well. Three batch experiments were implemented in CMA_GFS with 4D-Var: 1) assimilating only the default data, and adding the above data over land with land surface emissivity obtained from 2) TELSEM2 and 3) the window channel retrieval method. The results indicated that the window channel retrieval method can better reduce the departure between the observed and simulated brightness temperature. Over most land types, the positive impacts of this method exceed those of TELSEM2. Both TELSEM2 and the window channel retrieval method improve the humidity analysis near the ground, as well as the forecast capability globally, particularly in those regions where the land coverage is greater, such as in the Northern Hemisphere. The data utilization of the two surface-sensitive channels increase by 6% and 12%, respectively, and the additional data every 6 h can cover most land, where there was no surface-sensitive data assimilated before. This study marks the beginning of near-surface channel assimilation over land in CMA_GFS and represents a breakthrough in the assimilation of other surface-sensitive channels in other satellite instruments. Significance Statement: Surface-sensitive microwave channels are difficult to assimilate in NWP due to the lack of both direct measurement and appropriate modeling for instantaneous land surface emissivity. This paper discusses a method that improves the surface emissivity estimates, which has allowed the utilization of surface-sensitive microwave channels in CMA_GFS. Those capabilities have resulted in better data utilization, improved forecasts of temperature, geopotential height, and winds in the Northern Hemisphere at 3–7 days, and represent an incremental and important improvement to CMA_GFS.