The atmospheric temperature profiles (ATPs) retrieved through the geostationary Interferometric Infrared Sounder (GIIRS) onboard the FY-4A satellite (GIIRS/FY-4A) can effectively fill the gap of the scarce conventional sounding data in the Taklimakan Desert (TD), the second largest desert in the world, with an area of 330,000 square kilometers. In this study, we take the experimental radiosonde observations (RAOB) from one RAOB station in the hinterland of TD and seven conventional radiosondes in the oasis region around the desert as the true values and analyze the bias distribution characteristics of GIIRS/FY-4A ATPs with quality control (QC) flags 0 or 1 for this region. In addition, a bias comparison is made with GIIRS/FY-4A ATPs, and the fifth generation ECMWF atmospheric reanalysis of the global climate (ERA5) ATPs. The results show that (1) Missing measurements in GIIRS/FY-4A ATPs are the most frequent in the near-surface layer, accounting for more than 80% of all the retrieved grid points. The averaged total proportion of GIIRS/FY-4A ATPs with QC marks 0 or 1 is about 33.06%. (2) The root mean square error (RMSE) of GIIRS/FY-4A ATPs is less than 3 K, smaller than that of ERA5 ATPs. The RMSE of ERA5 ATPs can exceed 10 K in the desert hinterland. The absolute mean biases of GIIRS/FY-4A ATPs and ERA5 ATPs are, respectively, smaller than 3 K and 2 K, the former being slightly larger. The correlation coefficients of GIIRS/FY-4A ATPs with ERA5 ATPs and RAOB ATPs are higher than 0.98 and 0.99, respectively, and the correlation between GIIRS/FY-4A ATPs and RAOB ATPs is inferior to the latter. (3) The overall atmospheric temperature retrieved by GIIRS/FY-4A is 0.08 K higher than the temperature of RAOB, on average, while the overall temperature from ERA5 is 0.13 K lower than that of RAOB, indicating that the temperature profile obtained by integrating GIIRS/FY-4A ATPs and ERA5 ATPs may be much closer to RAOB ATPs. (4) The probability density of the GIIRS/FY-4A ATP biases in the TD region generally follows the Gaussian distribution so that it can be effectively assimilated in the 3-D variational assimilation modules. The probability density distribution characteristics of the GIIRS/FY-4A ATP biases in the desert hinterland and oasis are not much different. However, due to the fusion analysis of the relatively rich multi-source conventional observation data from the oasis stations, the probability density of ERA5 ATPs biases at the oasis stations is nearer to Gaussian distribution than that of the GIIRS/FY-4A ATPs. In the desert hinterland, where conventional observation is not enough, the probability density distributions of the ATPs biases from ERA5 and GIIRS/FY-4A are alike. Therefore, the GIIRS FY4A can contribute to a more accurate estimation of ERA5 ATPs in the TD region.

Global deterministic numerical weather predictions (DNWPs) initialized from the ensemble mean analysis of four‐dimensional ensemble‐variational (4DEnVar) data assimilation are usually worse than those initialized by four‐dimensional variational (4DVar) data assimilation. As the average of ensemble forecasts initialized from 4DEnVar analyses generally outperforms the 4DVar‐initialized DNWP in anomaly correlation and anomaly root mean square error, a new approach was proposed to improve the 4DEnVar‐initialized DNWP with only doubling forecasting computational resources. This method approximately supplements the diffusion term existing in the ensemble mean forecast, which is missed in the DNWP initialized from ensemble mean analysis. The diffusion filters noise from initial uncertainty. Experiments show higher skill in the new 4DEnVar‐initialized DNWP than in those initialized from 4DEnVar ensemble mean analysis using purely ensemble covariances and 4DVar analysis with a purely climatological covariance. This approach provides an effective way to expand applications of 4DEnVar and possibly other ensemble‐based methods to operational forecasting.

From 17 to 22 July 2021, the “21·7” extreme rainfall event (“21·7” ERE) hit Henan Province, breaking the record for mainland China with a maximum hourly rainfall of 201.9 mm at the Zhengzhou station. The long-lived (20 h) mesoscale Huang-Huai vortex (HHV) was an important system that directly affected the major rainfall stage, including the extreme hourly rainfall. This study investigates the formation and development mechanism of the HHV, as well as its association with the simulation of extreme hourly rainfall through numerical simulations. The simulated rainfall and radar composite reflectivity were in good agreement with the observations, thus effectively reproducing the generation and developmental process of the HHV. The analysis results showed that the HHV initially formed at 850 hPa on 19 July at 1800 UTC and eventually developed to 550 hPa. The positive feedback formed by the horizontal convergence and vertical vorticity transport was the main mechanism leading to the generation and deepening of the HHV. The stretching effect (STR) term played an absolutely dominant role in the increase in the vorticity tendency, and it primarily originated from the coupling effect of boundary layer jets (BLJs) and synoptic-weather-system-related low-level jets (SLLJs). The accurate simulation of the HHV allowed the early rainfall to reasonably reproduce the surface cold pool near the Zhengzhou station, and then the cooperation of the SLLJs, the BLJs, and the cold pool made the simulated extreme hourly rainfall exactly close to the Zhengzhou station, but with a weaker intensity, due to the fact that the HHV moved northeastward after its formation, resulting in a narrow range of southerly flow in southern Henan, which is not conducive to convective triggering in the southerly flow.

In this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of this method on water vapor analysis and rainstorm forecasting is examined through observing system simulation experiments and actual case experiments. The high proportion of inverted humidity profiles in the cirrus‐effected pixels is the main reason for the negative effect of assimilation in the mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into the cost function. The statistical results reveal that the addition of a CER assimilation improves the analysis increment of water vapor, with pattern correlation coefficients of 0.33, 0.35, and 0.20 at 200, 300, and 400 hPa, respectively, which are greater than those of a clear‐sky radiance assimilation (0.28, 0.33, and 0.17, respectively). Moreover, the inclusion of a CER assimilation greatly improves data utilization, and has a neutral to positive effect on precipitation forecasting.

Applying the four‐dimensional variational (4DVar) method in nonlinear systems faces conflicts between a lack of long‐term dynamical information using a short assimilation window and a trap of local minima using a long window. Here, an adjusted analysis approach that incorporates a thought of pseudo‐orbit analysis adjusting into 4DVar was proposed, resulting in the enhanced consistency between the initial condition (IC) and the long‐term dynamics of model, and the reduced risk of falling into local minima. This approach tries to find a truer orbit of weather state by minimizing the distance from the 4DVar‐based pseudo‐orbit to the long‐term model trajectory. Sensitivity experiments based on observing system simulation experiment reveal that the new approach with a proper iterative number can produce more reasonable analysis than 4DVar. Real observation experiments further exhibit that this approach can help 4DVar produce ICs that are more consistent with the long‐term dynamics and benefit the forecast skills.