Dual-satellite observations of FY-4A and FY-4B exhibit continuity and complementarity, but differences in the satellites’ positions and observation paths may make their actual detection results inconsistent. This study, which is based on the AGRI full-disk Level 1 data and cloud top height products from dual-satellite imagers during June–August 2022, conducted parallax correction on the dual-satellite data and analyzed differences in thermal infrared channel brightness temperatures (BTs) under various cloud height scenarios and underlying surface conditions. The results showed that within the common observation area, the BT differences between FY-4A and FY-4B gradually turned positive to negative from west to east. In the equatorial region, the BT differences reached 8 K. As cloud height increases, the root mean square error of the BT differences increases from 1.63 K to 3.06 K. The differences were larger over land than over the ocean. Additionally, this study investigated the theoretical effects of satellite zenith angle on dual-satellite BT differences using the RTTOV fast radiative transfer model. Simulated BT difference trends between the satellites show broad consistency with observed empirical trends. Therefore, future research can perform physical correction on the dual-satellite observations according to these patterns, enabling joint applications of the dual-satellite data.

To investigate the mobility of the Southwest China Vortex (SWV) and its associated rainstorm regions, this study examined 25 SWV-related rainstorm events that affected Chongqing during 2019–2023. A dynamic compositing method that tracks the movement of the vortex center was employed to analyze the dynamic characteristics and genesis of the SWV and the distribution of heavy rainfall relative to the vortex center. The conclusions are as follows: SWV rainstorms can be categorized into three types: southeastern, eastern, and multi-quadrant types. The distribution of heavy rainfall for each SWV type is closely related to the position of the upper-level jet, the intensity and meridional extent of the trough, the exit region of low-level jets, and the distribution of warm-air and cold-air advection, while the thermodynamic and dynamic characteristics exhibit distinct similarities and differences. The southeastern type is influenced by the short-lived SWV with weaker upward motion, shallow vertical development, and a pronounced northwestward tilt. The eastern type involves the long-lived, intense SWV with deeper vertical development and a low-level northwestward tilt. The multi-quadrant type is influenced by the SWV with sustained cold-air intrusion from the rear and strong uplift movement. The configuration features symmetric winds in the front and rear, pronounced cold- and warm-air convergence, the deepest vertical development among the three types, and a low-level northward tilt.

Aircraft turbulence is primarily caused by atmospheric turbulence, which is closely related to changes in wind speed, temperature, and topography. This phenomenon is especially pronounced in the southwestern region, where the complex terrain and the significant uplifting effect of the plateau on air currents make aircraft highly susceptible to turbulence. The turbulence event experienced by flight MU5954, operating from Tengchong to Kunming on 4 April 2024, was analyzed using reanalysis data, topography data, satellite data, and aircraft in-flight reports. The results showed that the turbulence occurred near the boundary between the windward and leeward slopes of the mountains, where the air currents were unstable. The alternating positive and negative distributions of vertical velocity, divergence, and vorticity in the upper-level jet stream, combined with the convergence of cold and warm airflows, jointly triggered atmospheric turbulence, making the aircraft susceptible to turbulence during flight.

The China Meteorological Administration Mesoscale Model (CMA-MESO) serves as a critical operational system for precipitation forecasting. However, its eight-times-daily rolling updates present new challenges for forecast evaluation. A comprehensive understanding of mean bias characteristics, variations across different forecast lead times, and error sources is key to model improvement. This study systematically evaluated the precipitation forecast performance of the CMA-MESO over East China during the summer of 2023. The key findings are as follows: (1) While the averaged multiple forecasts generally reproduced the spatial distribution patterns of observed precipitation, systematic biases existed in precipitation intensity and frequency. (2) The model significantly overestimated the precipitation amount for moderate-and-above rainfall events, with 3.7% underestimation of the frequency of no-rainfall events but 2.6% overestimation of the frequency of light rain events, along with elevated false alarm rates for heavy-and-above rainfall events. (3) The forecast performance showed a distinct lead-time dependence, with precipitation biases largest in 3～6 h nowcasting, gradually decreasing to a minimum in 21～24 h forecasts, and then increasing again in the 24～36 h range. (4) Physical analysis revealed that the nowcasting overestimation stemmed from excessive hydrometeor introduction during cloud analysis, and the overestimation in the forecast after 24 h resulted from excessive low-level wind speeds that promoted moisture transport to the target region.

As urbanization accelerates, hazards including flash floods, debris flows, and urban inundation are becoming more frequent and severe, with escalating social disruption and economic losses. A scientific and effective radar quantitative precipitation estimation (QPE) product is essential for enhancing the monitoring, forecasting, and early warning of extreme precipitation, which is of great value to current disaster prevention and mitigation efforts. This study used data from a single S-band dual-polarization radar and six X-band dual-polarization phased array radars in Jiaxing to develop S-band and X-band radar QPE products for the region. After preprocessing the radar observation data, including removing nonmeteorological echoes and performing quality control of the differential propagation phase, the effective minimum hybrid elevation for each radar was calculated. Then, the rain rate was estimated using single radar observations and raindrop size distribution parameters provided by the Dual-frequency Precipitation Radar onboard the Global Precipitation Measurement satellite (GPM-DPR). Finally, the rain rate was mosaicked for multiple radars, forming a gridded QPE product with a temporal resolution of 1 min and a spatial resolution of 50 m. To verify the accuracy of the proposed method, two heavy precipitation events that occurred on 10 and 16 September 2024, in the Jiaxing area were selected to evaluate the radar QPE products. The evaluated products included the original Jiaxing X-band QPE product and the X-band, S-band, and mosaic products developed in this study. The results show that the proposed QPE products outperform the original X-band product in terms of accuracy and stability, with the mosaic product yielding the best estimation result. For localized heavy rainfall with horizontally inhomogeneous distribution, the mosaicking product accurately reflects the precipitation distribution across various towns (subdistricts), contributing to the early issuance of accurate warnings.

Two large-hail supercells that occurred before spring in Zhejiang, on February 21, 2024 (“24·2·21”), and March 3, 2025 (“25·3·3”), were analyzed using the reanalysis data, automatic weather station observations, lightning location data, and S-band dual-polarization radar data. The results indicate that both convection events occurred after the passage of a cold wave front and were elevated convection systems. Above the inversion layer, conditionally unstable stratification and positive convective available potential energy were present. Deep convection was rapidly triggered under the influence of the 850 hPa shear line. Strong, deep-layer vertical wind shear favored the development of supercells. The dry layer in the “25·3·3” case was deeper than that in the “24·2·21” case. In both supercell hail processes, hailfall was accompanied by a decrease in storm centroid height and in the maximum shear height of the mesocyclone. The “24·2·21” supercell exhibited a long maintenance time, a mid-level double vortex structure, and differential reflectivity (Z_DR) and specific differential phase (K_DP) columns extending above 6 km. The Z_DR and K_DP values within the overhanging echo were small, and the cross-correlation coefficient (C_C) decreased with decreasing height, indicating the presence of melting small ice phase particles, which favored moist hail growth. In contrast, the “25·3·3” supercell had a shorter maintenance time, a deep single vortex (mesocyclone) structure, and a pronounced rear inflow. The Z_DR and K_DP columns were confined below 5 km. Small Z_DR and K_DP values accompanied by large C_C values at upper levels indicated a greater abundance of dry ice phase particles. This was manifested by an increased frequency of intracloud lightning flashes, which may be associated with accelerated freezing caused by rear-inflow dry cold air and was conducive to dry hail growth in the upper cold cloud region.

Using multi-level observation data of the near-surface layer on the Weizhou Island, Beihai, Guangxi, this study examined the periods influenced by typhoons Yagi, Sanba, and Talim during 2023–2024. First, quality control and correction were conducted on the observation data for each event. Subsequently, the structural characteristics of the typhoon boundary layer under the influence of the complex underlying surface of the Beibu Gulf islands were analyzed. The analysis included near-surface wind field evolution, wind profile characteristics, and variations in aerodynamic parameters, namely, friction velocity (u_*), roughness length (z₀), and drag coefficient (C_d), along with near-surface wind speed and direction. The results indicate that the typhoon boundary layer within 10–32 m exhibits near-neutral stability and the mean wind speed profile follows a logarithmic distribution. Under the influence of the complex underlying surface of the Beibu Gulf islands, the variations in u_*, z₀, and C_d with near-surface wind speed exhibit characteristics typical of a land underlying surface, showing obvious nonmonotonicity, and cannot be simply categorized as those typical of a homogeneous marine underlying surface. Specifically, u_* ranges between 0.5 and 1.5 m s⁻¹; when the 10 m wind speed exceeds approximately 15 m s⁻¹, the magnitudes of z₀ and C_d are on the order of 10⁻² m and 10⁻³, respectively. The u_*, z₀, and C_d values are generally higher under easterly winds than under westerly winds. The findings contribute to a deeper understanding of typhoon boundary layer structures over the complex underlying surface of an island and hold significance for optimizing numerical simulations and parameterization schemes of typhoons in the Beibu Gulf.

In the context of global warming, the spatiotemporal correlation between extreme drought and heatwave events has intensified over time. Their compounding effects not only amplified their individual impacts but also exacerbated the pressure on water resources, agriculture, and ecological environments. Based on the fifth-generation reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5), this study calculated the standardized precipitation evapotranspiration index (SPEI) and the standardized temperature index (STI) and employed the Frank Copula function to construct the standardized compound dry and hot index (SCDHI). This approach systematically revealed the spatiotemporal evolution characteristics of compound hot–dry events in the Mongolian Plateau between 1982 and 2023. Additionally, the study integrated a random forest regression model to identify and quantify the key climatic factors that influenced compound hot–dry events in the region. The results indicated that over the past four decades, the intensity, the time proportion, and the affected area proportion of compound hot–dry events in the Mongolian Plateau exhibited a significant decreasing trend. Among the climatic variables, STI was the most influential factor affecting the compound events, with a feature importance value of approximately 0.5. This was followed by SPEI, temperature, and potential evapotranspiration (PET), with feature importance values of 0.4, 0.1, and 0.1, respectively, while precipitation had a relatively weak impact. This study underscored the need to incorporate the long-term impacts of compound hot–dry events into the protection and management of the grassland ecosystem of the Mongolian Plateau. It emphasized the importance of developing adaptive management strategies based on scientific predictions and risk assessments to enhance the resilience and sustainability of the ecosystem.

Using surface dense automatic precipitation observations, ERA5 reanalysis data, and radar composite reflectivity data, this study analyzes the causes of a heavy rainstorm event over the western Sichuan Basin on July 11, 2023, focusing on the impacts of inertial oscillation on wind fields and terrain–airflow interactions on rainfall. A physical conceptual model of this rainstorm event is also developed. The results show that this precipitation event exhibited three prominent characteristics: a linear distribution of heavy rainfall along mountainous terrain, pronounced nocturnal development, and strong convective activity. Before the heavy rainstorm, the Sichuan region was under the control of the South Asian High, while the basin was influenced by southerly airflow on the periphery of the Western Pacific Subtropical High, with no considerable weather systems affecting the area. Quantitative analysis revealed that the Coriolis force and geostrophic deviation terms showed large variations. While atmospheric advection and vertical transport were weak, inertial oscillation dominated the wind speed increase in the central–eastern Sichuan Basin and eastern Yunnan–Guizhou Plateau. This process led to nocturnal boundary layer jets and clockwise rotation of the ageostrophic wind. The development of southeastward ageostrophic winds at night enhanced the southeasterly flow over the basin. The superposition of jet transport from the eastern Yunnan–Guizhou Plateau and wind speed growth in the central–eastern basin enhanced wind convergence in the basin. The combined effects of the divergence term and vertical transport term promoted the development of cyclonic wind fields. Under the combined influence of airflow in the northern sector of the cyclonic wind field and ageostrophic winds, southeasterly winds persisted over the northwestern basin, playing a crucial role in the formation of nocturnal rainfall. The southeasterly winds transported warm, moist air westward, leading to considerable wind and moisture convergence along the mountains of the western basin. The intrusion of dry air at mid-to-upper levels combined with low-level warm and moist airflow enhanced convective instability. The perpendicular intersection of southeasterly winds with the mountains of the western basin produced strong upslope flow. Orographic lifting on windward slopes and the formation of secondary vertical circulations triggered convection ahead of the mountains. As nocturnal southeasterlies intensified, convergence ahead of the mountains strengthened, and convection continued to develop. The persistent southeasterlies combined with topographic blocking and cyclonic wind field development, generated northerly winds along the western basin margin and easterly winds along the northern edge. Their convergence with easterly/southeasterly flows formed wind shear lines that promoted convective organization. The steep terrain transition from the basin to the mountains and the perpendicular intersection of the southeasterlies with the northeast–southwest-oriented mountains in the western basin favored strong upward motion on windward slopes. Sensitivity experiments conducted using a multisource observation data assimilation system and the WRF model demonstrated that halving terrain slopes reduced precipitation intensity by one order of magnitude. This decrease clearly indicates the enhancement effect of steep topography on rainfall. Under the combined forcing of low-level shear lines and steep terrain, a quasi-linear intense convective system developed along the mountains, forming a linear downpour zone along the western basin’s foothills. With the interaction of persistent southeasterly flow and the unique topography, efficient precipitation persisted, ultimately causing the extreme rainfall event.

An extratropical cyclone is an important weather system in mid-latitude regions and has a profound impact on global weather and climate. The frontal system is a key component of the cyclone, and its accurate identification is crucial for improving the accuracy of weather forecasts. In recent years, deep learning methods have been applied to automatic frontal recognition, but research on frontal identification over the Eurasian continent has been limited, with a focus on detecting single-type fronts. Achieving simultaneous recognition and classification of cold and warm fronts remains a major challenge. Therefore, this paper proposes a method for the synchronous recognition of cold and warm fronts based on the Detection Transformer (DETR) model called DETR-FRONT (DETR-FRO). This method constructs RGB feature images using meteorological variables, such as sea level pressure, temperature advection, temperature, and relative humidity at 850 hPa. The DETR model is trained using an artificially created cold and warm front label set, enabling automatic synchronous recognition and classification of both types of fronts. DETR-FRO improves the original DETR model by enhancing its transmission channel and incorporating multiple meteorological variables to construct RGB feature images. This modification strengthens the ability of the model to capture and express frontal features, leading to improved recognition performance for cold and warm fronts. Multidimensional validation results show that DETR-FRO can simultaneously identify cold and warm fronts in extratropical cyclones over the Eurasian continent with high accuracy and stability. In a typical snowstorm case study, the DETR-FRO model accurately reconstructs the cold and warm fronts and their evolution processes. The recognition results are consistent with dynamic and thermodynamic fields, further confirming the model’s generalization ability and meteorological interpretability. This improvement provides new technical support for weather forecasting and the study of extratropical cyclones. In addition, the long-term frontal dataset created using DETR-FRO, covering the period from 1995 to 2024, reveals the seasonal distribution characteristics of cold and warm front frequencies in extratropical cyclones over the Eurasian continent at the climate scale. This information contributes to a deeper understanding of the climatic characteristics of cold and warm fronts in extratropical cyclones.