A severe torrential rain attacked Henan province from July 19 to 21, 2021, resulting in extensive social and economic damages. The models’ sub-seasonal prediction skill for this extreme event remains to be evaluated. Based on the real-time data of 5 models (CMA, ECMWF, NCEP, KMA, and UKMO) from the sub-seasonal to seasonal (S2S) prediction project, our study compared the models’ predictability and explored the possible reasons. Results indicate that most models can predict the spatial distribution of accumulated precipitation for this event 1 week in advance. Two models (NCEP and CMA) still have specific reference values in predicting precipitation intensity 2–3 weeks ahead. However, the predicted maximum rainfall is only about 20% of the observation, and all models cannot catch the extremes of this event. While large-scale atmospheric circulation can be predicted with some accuracy, there are still significant deviations in predicting the location and intensity of the western North Pacific subtropical high (WNPSH) and Typhoon In-Fa. The models predict weaker intensity of the southeast airflow transporting water vapor into the rainstorm area, resulting in significantly weaker precipitation. This is mainly attributed to unsatisfactory predicted typhoon circulation in most models. The model ECMWF and KMA predict a better moisture flux at 925hPa, about 60% of the observations. The characteristics of local high SST centers in the Sea of Japan cannot be caught, resulting in the position of the predicted WNPSH eastward and weak. Therefore, to improve the prediction skill for extreme precipitation events, it is imperative to enhance the interaction mechanisms among atmospheric circulation systems within the model.

Two severe dust storm (DS) events (15–17 March and 28–29 March) hit northern China in 2021 consecutively. The lower atmospheric vertical dynamic and thermal structures during the two cases were compared using the ground-based sensor data from the microwave radiometer and radar wind profiler, combined with the environmental and meteorological observations data in Jinan, China. It was found that both cases occurred under the background of cold vortexes over northeastern China. The dust was transported through the cold air on the northwest route. During the dust period, 2–3 km was the west or northwest airflow, and below 2 km was the northeast wind. The variation in the dynamic structure determined the duration of the DS. During the DS maintenance phase, the vertical wind shear (VWS) below 3 km measured approximately 10 m∙(s∙km)⁻¹. The increased VWS during the dust intrusion period facilitated the transportation of dust. In contrast, the more significant VWS was not conducive to the maintenance of DS, and the shift to south wind control in the upper middle layer indicated the weakening of DS. In both cases, we observed a cliff-like decrease in relative humidity as a prominent indicator of dust outbreaks, occurring approximately 2–5 h beforehand. The diurnal difference between the vertical temperature and relative humidity during the dust maintenance period was found to be insignificant.

The Taklimakan Desert (TD), located in the Tarim Basin, and the Gobi Desert (GD), spanning northern China and southern Mongolia, are the two major dust source regions in East Asia, with substantial influence on China’s atmospheric environment and ecosystem. Using dust storm day (DSD) observations from national meteorological stations between 2000 and 2024, along with meteorological variables and the Normalized Difference Vegetation Index (NDVI), this study examines the spatiotemporal trends of dust storms and their key driving factors in both source regions. The TD and GD regions exhibit high levels of dust storm activity in China, with a distinct decreasing gradient from the source areas to downstream regions observed across all seasons. Trend analysis of DSD reveals distinct temporal patterns: the TD region experienced a moderate decline (−0.11 d/a) followed by a fluctuating increase (0.04 d/a), while the GD region exhibited a sharp drop (−0.32 d/a) and a subsequent marked resurgence (0.09 d/a). Seasonally, dust storm events in the TD region were frequent in both spring and summer, whereas in the GD region they were concentrated almost entirely in spring. In both source regions, spring dust storm events were closely linked to wind speed and the frequency of strong wind days. However, in summer, precipitation played a more suppressive role in the GD region, while wind remained the primary driver in the TD region. Between 2001 and 2013, both regions experienced a reduction in barren land area, aligning with a decline in dust storm events. In contrast, barren land in the GD region expanded from 2013 to 2023, accompanied by a significant increase in dust storm events. Notably, in the GD region, spring and summer NDVI values were negatively correlated with DSD, indicating stronger vegetation control over dust emission. In contrast, this relationship was weaker in the TD region, underscoring distinct ecological–meteorological interactions between the two desert systems.

Accurate identification of dust emission sources is crucial for simulating dust aerosols in atmospheric chemical models. Therefore, a dynamically updated dust source function (DSF) was developed within the dust emission scheme of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an East Asian dust storm event from 13 to 16 March 2021. Utilizing satellite-derived input of vegetation cover, snow cover, soil texture, and land use, the DSF was updated to better identify dust source areas over bare soils and sparsely vegetated regions in western China and central-western Mongolia. With the updated DSF, simulated dust emissions increase significantly over western China and Mongolia. The dust aerosol simulations demonstrate substantial improvements in near-surface PM₁₀ concentrations, a better agreement with remotely sensed dust aerosol optical depth (DOD), and a more accurate representation of the vertical distribution of dust extinction coefficients compared to observations. This study highlights the importance of integrating real-time data to accurately characterize dust emission sources, thereby improving atmospheric environment simulations.

The anomalous zonal wind moves southward during the ENSO mature phase in boreal winter. Previous studies suggest that it may be caused by the nonlinear interaction of annual cycles or the influence of background mean state changes. In this research, the ECHAM4.6 atmospheric model is used to confirm the mechanism of the anomalous zonal wind southward shifting. The annual cycle of solar radiation and SST are removed in the sensitivity experiments to avoid the interaction between the ENSO and annual cycle. The results show that the north–south asymmetry mode of the ENSO anomalous wind field is not the result of a nonlinear interaction between ENSO and the annual cycle. The mean v-winds in winter motivate the southward shifting of the ENSO anomalous wind field through advection.