Accurate prediction of summer thermal convective systemsu2014including their initiation, intensity, and associated hazardsu2014remains a major challenge in operational meteorology across China. This study evaluates the utility of high-resolution temperature and humidity profiles retrieved from the Fengyun-4B (FY-4B) Geostationary Interferometric Infrared Sounder (GIIRS) for analyzing and forecasting a representative thermal convection event in Zhejiang, a coastal province in Southeast China. With significantly higher temporal and spatial resolutions than conventional radiosondes, the retrieved profilesu2014characterized by strong convective available potential energy (CAPE), weak convective inhibition (CIN), and elevated equivalent potential temperature (u03B8e)u2014exhibit marked diurnal variations in thermodynamic conditions and capture pronounced moisture accumulation and vertical expansion in pre-convection environments. On this basis, this study further investigates how the assimilation of GIIRS-retrieved humidity profiles affects simulations of summer thermal convection within the China Meteorological Administration Mesoscale Model (CMA-MESO). Numerical experiments demonstrate that assimilating GIIRS-retrieved humidity profiles effectively adjusts initial moisture and thermodynamic fields, leading to improved predictions of the location and intensity of convection initiation. Multi-case experiments reveal that the assimilation of GIIRS-retrieved humidity profiles yields a 44% higher average threat score (TS) for moderate rain and above relative to experiments without such assimilation, despite considerable variability among individual cases. The results highlight the potential of FY-4B GIIRS data to enhance convective-scale forecasting and early warning systems.
Meteorological satellite remote sensing offers a crucial solution to the issue of insufficient ground-based observation coverage in regions with complex terrains. However, being an indirect method for measuring meteorological elements, current satellite-based precipitation estimation still suffers from limited accuracy. This paper proposes a novel Dual-Stream Transformer-Augmented UNet (DSTA-UNet) framework for satellite quantitative precipitation estimation (QPE). It generates high-accuracy precipitation analysis fields in near real-time by using the satellite cloud imagery from China’s new-generation geostationary satellite, Fengyun-4A (FY-4A). Extensive comparisons against operational products [FY-4A QPE, Global Precipitation Measurement Integrated Multi-satellite Retrievals (GPM IMERG), and Climate Forecast System Reanalysis Version 2 (CFSv2)] and deep-learning-based (Attention-UNet and UCTransNet) precipitation estimation methods demonstrate that DSTA-UNet achieves competitive performance. When evaluated against ERA5 as the benchmark, DSTA-UNet reduces the root mean square error (RMSE) by 52.38
Polar-orbiting microwave humidity sounders, with 6-h revisit intervals, cannot resolve rapidly evolving moisture features in the lower troposphere. Cost-effective small-satellite constellations promise shorter revisit times, yet their impact on global numerical weather prediction (NWP) using actual observations has not been quantified. From 25 March to 25 April 2024, clear-sky radiances from the Compact Atmospheric Microwave Sounder (CAMS) aboard the 500-km small satellite Tianyan-16 (TY-16; launched December 2023) were, for the first time, assimilated into the China Meteorological Administration Global Forecast System (CMA-GFS) global four-dimensional variational (4D-Var) system. Four cycling experiments were carried out: a control experiment (CTRL) assimilating conventional and operational satellite observations [excluding radiances from the Microwave Humidity Sounder-2 (MWHS-2) aboard Fengyun-3E (FY-3E)]; CTRL plus CAMS radiances (EXP1); CTRL plus MWHS-2 radiances (EXP2) for benchmark comparison; and CTRL plus both CAMS and MWHS-2 radiances (EXP3). Offline bias correction was applied to 12 out of 18 channels (7 for temperature and 5 for humidity) against CMA-GFS model backgrounds. Compared to CTRL, EXP1 reduces the standard deviation of background departures for humidity-sensitive channels of independent sounders by 0.5
Short-duration heavy rainfall (SHR) is a major hazard, but conventional methods using fixed thresholds or percentile extremes struggle to identify locally impactful events and preclude objective cross-regional comparisons. This paper introduces a novel SHR intensity index that quantifies an SHR event’s local extremity relative to its climatic background. This is achieved by normalizing the exceedance beyond the historical 95th percentile precipitation using the standard deviation of values above that percentile. Applied to hourly data from 2422 stations (2010–2022), the index identifies three intensity tiers, with Tier 2 and above representing higher-impact SHR events. Key findings include: (1) The new index reveals SHR hotspots not only in humid southeastern China but also in arid/semi-arid northwestern and northern regions, which are largely missed by the conventional 20 mm h−1 threshold. (2) SHR exhibits distinct regionality: frequency peaks in South China, while extreme-intensity events (Tier 3) are most frequent over the mid–lower Yangtze River basin. Diurnal cycles vary from nocturnal peaks in the Sichuan basin to afternoon maxima in North China. (3) Long-duration SHR events (⩾ 4 h) also impact dry western and northern regions. (4) Underlying surfaces modulate SHR: within the same region, hills promote higher afternoon SHR frequency, while plains exhibit greater average intensity. For similar surface types, wetter southern regions show higher frequency and intensity than drier northern ones. This regionally adaptive index provides a transferable framework for identifying locally impactful SHR, offering enhanced utility for regional hazard assessment, forecasting, and climate adaptation planning.
Despite advances in understanding severe convective weather in South China, large-scale dynamical pathways that sustain organized mesoscale convection over multiple days remain poorly understood. This study investigates the multi-scale dynamical mechanisms for a rare severe convective outbreak (SCO) over western South China during 16–22 April 2024. We propose a “sustained charging-triggered discharging” conceptual model, in which the synergistic interplay between persistent oceanic forcing and synoptic-scale wave dynamics serves as the fundamental driver. During the El Niño decay year, record-breaking warm sea surface temperature anomalies in the tropical Indian Ocean and North Atlantic were identified as dominant forcing for an exceptionally strong western Pacific subtropical high (WPSH). The WPSH acted as a “sustained charger”, promoting pre-SCO energy accumulation. Subsequently, the dual Rossby wave trains that originated from the North Atlantic functioned as the “discharge switch”, modulating the spatiotemporal phasing of the Ural blocking high (UBH) and the southern branch trough (SBT). This “dual-core” dynamic structure of UBH and SBT drove extreme low-level frontogenesis anomalies, which directly triggered the convection and released/discharged the accumulated unstable energy in the SCO area. This study reveals a distinct pathway for sustained convective activity from the perspective of multi-scale remotely forced dynamics.
