Effects and Atmospheric Processes of Disaster Weather in the Context of Global Climate Change

In recent years, the rapid intensification of global warming has led to significant deterioration and disruption of the natural environment. Against this backdrop, disaster weather—defined as severe meteorological events that threaten human lives and property and cause substantial damage to industry, agriculture, transportation, and other critical sectors—is occurring with increasing frequency and intensity [1,2,3]. These events pose a grave threat to societal safety and sustainable development [4,5]. To achieve global sustainable development goals, there is a pressing need for nations to address the following key priorities: (i) evaluate the multifaceted impacts of disaster weather on the environment, industry, agriculture, and society under climate change; (ii) advance understanding of the formation and maintenance mechanisms of such events, as well as making necessary projections for the future; and (iii) develop innovative methods to enhance forecasting accuracy and mitigation strategies. The primary purpose of this Special Issue is to partly address these urgent issues. This Special Issue includes a total of six published papers aiming to address the following key research objectives outlined earlier at https://www.mdpi.com/journal/sustainability/special_issues/MYLTZY28D0 (accessed on 16 January 2025). Disaster weather encompasses a range of phenomena, such as torrential rainfall, high winds, tornadoes, hail, and cold waves [6,7,8,9,10]. The published articles in this Special Issue feature research that primarily examines heavy rainfall events and tornadoes, analyzing their large-scale backgrounds, dominant weather systems, triggering mechanisms, long-term trends, and future projections. Additionally, it also explores the response of vegetation water-use efficiency to climate change. Collectively, these studies enhance our understanding of disaster weather by elucidating their underlying mechanisms, societal and environmental impacts, projected changes under climate scenarios, and potential mitigation strategies.

In terms of large-scale backgrounds for heavy rainfall events, Liao Rongwei et al. used observational 24 h accumulated rainfall data from China in conjunction with ERA-I reanalysis data to elucidate the relationship between Asian–Pacific Oscillation (APO) and daily rainfall patterns in Southwest China. Their results demonstrated that daily APO variability significantly impacts July rainfall in the Sichuan–Shaanxi region, where extreme rainfall events during high APO phases contribute disproportionately to total rainfall increases. Enhanced sea–land thermal contrasts during high APO days intensify water vapor transportation, leading to a ~122.6% surge in the frequency of extreme rainfall events and a ~23.3% rise in intensity compared to low APO phases. These findings demonstrate the APO’s predictive utility for extreme rainfall events, highlighting the critical need to incorporate APO dynamics into regional climate modeling frameworks. This integration could enhance forecasting accuracy and disaster resilience in ecologically sensitive and agriculturally critical regions such as Sichuan–Shaanxi.

In terms of dominant weather systems and triggering mechanisms for heavy rainfall, Yang Kangquan et al. investigated the interplay between topographic forcing and mesoscale convective systems that generate heavy rainfall by conducting a series of sensitivity simulations on an exceptionally persistent 66 h southwest vortex (SWV). After synoptic analyses, they found that the SWV’s persistence was tied to upper-level divergence associated with the South Asia High, which is a mid-tropospheric warm advection from a shortwave trough, and low-level jets steering its northeastward movement. Through quantitative vorticity budget analysis and backward trajectory modeling, they demonstrated that the vertical stretching term—driven by the lower-tropospheric convergence—plays a dominant role in the SWV’s genesis and intensification. Their results further revealed that the majority of air parcels contributing to the SWV originate from lower tropospheric sources. In particular, the Yunnan–Guizhou Plateau plays a pivotal role, with around half of the SWV’s air particles originating from this region, gaining cyclonic vorticity as they descend the plateau’s slopes. Similarly, Wang Xiuming et al. identified many smaller-scale mesoscale vortices (e.g., meso-β-scale, meso-γ-scale) within the west Henan low vortex (belonged to a type of meso-α-scale vortex) as the key drivers for the catastrophic 2021 Zhengzhou rainstorm. During this event, interactions between inflows from surrounding regions (including the low-level jet) and the terrain adjacent to Zhengzhou amplified lower-tropospheric convergence and vertical ascent, acting as the primary dynamical driver for the rapid intensification of rainfall-producing mesoscale convective systems. These studies illustrate how interactions between regional topography and mesoscale weather systems can effectively concentrate moisture and energy, transforming ordinary rainstorms into extreme events.

In terms of the future projection of heavy rainfall, Liu Lu et al. (2024) projected a paradox under the RCP4.5 scenario: while total summer rainfall in the Yangtze River Basin may remain stable through 2030, extreme precipitation is expected to decline overall but with sharp regional contrasts—decreases in Hunan and Hubei versus increases in Jiangxi and Fujian. The high-resolution WRF model downscaling simulation revealed that these patterns correspond with high-pressure-induced subsidence in the lower basin, which suppresses convection and reduces rainfall. Enhanced (or diminished) moisture flux convergence and upward (or downward) vertical motion are key drivers of increased (or decreased) extreme precipitation. Mechanistically, anomalous easterly (or westerly) winds on the southern (or northern) flank of an anticyclonic anomaly induce descent (or ascent) via isentropic gliding, further explaining regional disparities. This indicates that policymakers must tailor region-specific adaptation strategies to address rapidly evolving climate change informed by localized projections of future precipitation variability and its distinct spatiotemporal characteristics.

In terms of the response to rapid climate change, Wang et al. (2024) analyzed the spatiotemporal characteristics of water use efficiency (WUE) of the Northwestern Sichuan Plateau from 2001 to 2021. They proposed that the WUE, which is a critical indicator of ecosystem resilience, varies seasonally and altitudinally, peaking from May to September. While most vegetation types showed rising annual WUE trends from 2001 to 2021, wetlands exhibited declines, and grasslands demonstrated remarkable adaptability. Mean climatic variables, particularly temperature, exerted stronger influences on the WUE than extremes, though synergistic effects—such as cold spells coupled with mean precipitation changes—could disrupt these patterns. This means croplands and forests displayed heightened sensitivity to climate extremes, suggesting that agricultural and forestry practices must evolve to account for both gradual climatic shifts and abrupt extremes.

In terms of tornadoes, which are one of the most intense forms of disaster weather, Li Danyu et al. conducted a 10 yr statistical analysis on the tornadoes that have occurred in Jiangsu (JST: 159 events, ranked first nationally) and Zhejiang (ZJT: 59 events, ranked fifth). The two provinces share analogous geographies. The authors pointed out that both JST and ZJT exhibit pronounced annual, monthly, and diurnal variability but diverge markedly in their spatiotemporal patterns. Composite analyses of pre-tornado environments highlighted key differences between the two types. For the JST environments, they favored convection through (a) the upper-tropospheric divergence and positive geopotential height anomalies, (b) the mid-level shortwave troughs with warm advection and temperature anomalies, and (c) the robust lower-tropospheric southwesterly convergence and cyclonic vorticity. However, the ZJT environments displayed less synoptic support overall, with conditions comparatively less conducive to tornadogenesis. Trend analyses showed a significant decline in JST frequency (annual and summer), whereas ZJT trends remained statistically insignificant. Such regional disparities underscore the need for localized climate adaptation strategies, as uniform policies may fail to address divergent trends even within geographically proximate areas. This study offers critical insights into advancing skillful forecast techniques targeting tornadoes in Jiangsu and Zhejiang while also shedding light on potential shifts in tornado climatology under global warming.

In summary, disaster weather events pose significant threats to society, as highlighted in recent climate assessments [1]. After detailed analysis, the studies of this Special Issue collectively reveal a dual challenge: improving predictive models while translating scientific insights into actionable strategies. Advances in high-resolution modeling, as seen in the WRF downscaling study, enhance localized projections, yet gaps remain in understanding mesoscale processes such as the interactions between mesoscale vortices and larger-scale systems. Moreover, the APO’s influence on rainfall extremes and the topographic amplification of rainstorms highlight the need for multiscale modeling frameworks that bridge large-scale oscillations and regional disaster weather. For policymakers, the prioritization of adaptive measures must align with these scientific advancements. As climate extremes increasingly test the limits of existing infrastructure and ecological resilience, integrating mechanism insights into policy design will be crucial for sustainable development in China’s climatically diverse regions [1].