Search Results (107)

Tropical cyclones typically weaken rapidly during poleward propagation due to decreasing sea surface temperatures and increasing vertical wind shear. Super Typhoon Oscar (1995) deviated from this pattern by maintaining Category-5 intensity at an anomalously high latitude. This study investigates the oceanic mechanisms driving this resilience by integrating satellite SST data with atmospheric (ERA5) and oceanic (HYCOM) reanalysis products. Our analysis shows that the storm track intersected a persistent marine heatwave (MHW) characterized by a deep thermal anomaly extending to approximately 150 m. This elevated heat content formed a strong stratification barrier at the base of the mixed layer (~32 m) that prevented the typical entrainment of cold thermocline water. Instead, storm-induced turbulence mixed warm subsurface water upward to effectively mitigate the negative cold-wake feedback. This process sustained extreme upward enthalpy fluxes exceeding 210 W m⁻² and generated a regime of thermodynamic compensation that enabled the storm to maintain its structure despite an unfavorable atmospheric environment with moderate-to-strong vertical wind shear (15–20 m s⁻¹). These results indicate that the three-dimensional ocean structure acts as a more reliable predictor of typhoon intensity than SST alone in regions affected by MHWs. As MHWs deepen under climate warming, this cold-wake mitigation mechanism is likely to become a significant factor influencing future high-latitude cyclone hazards. Full article

About 16% of typhoons making landfall in China strike Hainan Island, where near-surface extreme winds in dense urban areas exhibit a strong spatiotemporal heterogeneity that is difficult to capture with current observations and mesoscale models. Focusing on Haikou during Super Typhoon Yagi (2024)—the strongest autumn typhoon to hit China since 1949—we developed a multiscale ERA5–WRF–PALM framework to conduct 30 m resolution large-eddy simulations. PALM results are in reasonable agreement with most of the five automatic weather stations, while performance is weaker at the most sheltered park site. Mean near-surface wind speeds increased by 20–50% relative to normal conditions, showing a coastal–urban gradient: maps of weighted cumulative exposure to strong winds (≥Beaufort force 8) show much longer and more intense events along open coasts than within built-up urban cores. Urban morphology exerted nonlinear effects: wind speeds followed a U-shaped relation with both the open-space ratio and mean building height, with suppression zones at ~0.5–0.7 openness and ~20–40 m height, while clusters of super-tall buildings induced Venturi-like acceleration of 2–3 m s⁻¹. Spatiotemporal analysis revealed banded swaths of high winds, with open areas and islands sustaining longer, broader extremes, and dense street grids experiencing shorter, localized events. Methodologically, this study provides a rare, systematically evaluated application of a multiscale ERA5–WRF–PALM framework to a real typhoon case at 30 m resolution in a tropical coastal city. These findings clarify typhoon–city interactions, quantify morphological regulation of extreme winds, and support risk assessment, urban planning, and wind-resilient design in coastal megacities. Full article

Urban floods are becoming increasingly frequent and severe, highlighting the need for real-time information that supports safe evacuation decision-making. This study proposes and validates an unmanned aerial vehicle (UAV)-based methodology for real-time urban flood monitoring using an actual flood event caused by Typhoon Hinnamnor at the Seondeok Intersection in Gyeongju, Republic of Korea. The method comprises three simple steps: (1) collecting UAV images and data; (2) generating spatial and terrain information through photogrammetry; and (3) estimating flood extent, depth, and volume using GIS-based analysis. A total of 796 UAV images were processed, yielding a flooded area of 3847.36 m², a flood volume of 13,895.13 m³, and a maximum depth of 0.75 m. To assess performance, UAV-derived results were compared with XP-SWMM simulation outputs. Significant discrepancies were observed in flood extent, inundation volume, and flood persistence, indicating that hydrological models may not fully capture localized drainage failures or site-specific conditions in urban environments. These findings demonstrate that UAV-based monitoring provides a more accurate representation of actual flood and can supply high-resolution, rapidly obtainable information essential for real-time evacuation. This study provides empirical evidence of UAV applicability during the flood event itself and highlights its potential to enhance disaster-response capability, improve decision-making, and strengthen the resilience and sustainability of flood-prone urban areas. Full article

Typhoon-induced hazards in South Korea exhibit strong spatial heterogeneity, requiring localized assessments to support impact-based early warning. This study develops a district-level typhoon hazard framework by integrating high-resolution meteorological fields with structural and hydrological vulnerability indicators. Two impact-oriented indices were formulated: the Strong Wind Risk Index (SWI), based on 3 s gust wind intensity and building-age fragility, and the Heavy Rainfall Risk Index (HRI), combining probable maximum precipitation with permeability and river-network density. Hazard levels were classified into four categories, Attention, Caution, Warning, and Danger, using district-specific percentile thresholds consistent with the THIRA methodology. Nationwide analysis across 250 districts revealed a pronounced coastal–inland gradient: mean SWI and HRI values in Busan were approximately 1.9 and 6.3 times higher than those in Seoul, respectively. Sub-district mapping further identified localized hotspots driven by topographic exposure and structural vulnerability. By establishing statistically derived, region-specific thresholds, this framework provides an operational foundation for integrating localized hazard interpretation into Korea’s Typhoon Ready System (TRS). The results strengthen the scientific basis for adaptive, evidence-based early warning and climate-resilient disaster-risk governance. Full article

Floating structures are increasingly recognized as crucial infrastructure for deep-sea energy exploitation, offshore communities, and maritime hub facilities in recent years. Understanding their energy consumption characteristics under varying meteorological conditions is essential for ensuring operational efficiency and resilience. This study investigates the influencing factors and variation patterns of energy use in floating structures under normal and typhoon environments. Three representative scenarios with different scales and functions were developed based on a bionic hexagon-shaped floating unit, and their respective energy demands were defined. A systematic sensitivity analysis was conducted using DeST with Typical Meteorological Year data and field observations from Super Typhoon Yagi (No. 2411) at Qionghai Station. Results indicate that, according to sensitivity analysis using the dynamic “intraday fluctuation + daily quantile” threshold, dry-bulb temperature and specific humidity are the dominant factors influencing floating-structure energy consumption, contributing 31.1% and 7.8% increases, respectively—significantly higher than other parameters. Under typhoon conditions, total energy consumption rose slightly relative to the TMY baseline, by 0.12%, 0.49%, and 0.95% across the three scenarios, with diurnal variations within ±5%. This study provides a quantitative basis for optimizing energy storage design and enhancing the resilience of floating structures to extreme meteorological events. Full article

Uncertainty and variability in soil properties strongly impact slope stability under extreme rainfall. This study applies a probabilistic hydro-mechanical slope stability assessment to unsaturated volcanic hillslopes in southern Guam, covering a range of slope angles and subjected to four major 2023 typhoons. The slope scenarios analyzed include bare slopes, vegetated slopes with root water uptake, and vetiver with both uptake and root reinforcement. Laboratory-derived variability in effective cohesion, friction angle, and unit weight was incorporated via Latin hypercube sampling. Gentler slopes (≤40°) remained stable with a probability of failure (PoF) = 0%. For steep slopes (45–60°), vetiver root reinforcement improved the mean factor of safety by up to 12–15% and reduced variability in outcomes to less than 2%. Probabilistic predictions advanced failure timing compared to deterministic estimates, with differences more pronounced on steeper slopes. By integrating soil variability and vegetation effects within probabilistic frameworks, this approach provides a more accurate and comprehensive assessment of tropical slope failure risks, thereby informing more effective and resilient slope management strategies. Full article

Sandy beach resilience faces growing threats from extreme events and intensified human activity. Deep Learning (DL) has emerged as a powerful tool in coastal research, offering strengths in spatial feature extraction, nonlinear sequence modeling, acceleration of physical processes, and integration of multi-source data. This review frames resilience in three technical dimensions—resistance, recovery, and adaptation—and examines DL applications across three domains: first, monitoring and forecasting external forcing, including typhoon tracks and storm surge peak values; second, modeling and simulating beach processes, from rapid hydrodynamic forecasting to medium- and long-term shoreline evolution, and high-resolution sediment transport forecasting; and third, management and decision support, where DL methods and multi-scenario generation expand governance options, and interpretable features with uncertainty quantification enhance risk communication and policy adoption. DL complements traditional models by shortening the “observation–model–decision” cycle, expanding scenario analysis, and improving governance transparency. Challenges remain in cross-domain generalization, robustness in extreme scenarios, and data governance. This review confirms DL’s potential as a technology stack for enhancing sandy beach resilience and provides a methodological foundation for future research. Full article

The Zhanjiang Bay ecosystem, frequently influenced by typhoons, represents a highly dynamic coastal environment where elucidating phytoplankton responses to extreme disturbances is essential for sustainable management. This study investigated the impacts of Typhoon Prapiroon on phytoplankton community composition and distribution by employing high-throughput sequencing of the 28S rDNA D1–D2 regions. A total of 137 species belonging to 46 genera was identified, with the ten dominant genera collectively contributing more than 85% of the total abundance, exhibiting substantial shifts in community structure following the typhoon. Salinity was identified as the predominant environmental driver shaping phytoplankton distribution, while temporal analyses revealed lagged community responses to post-typhoon conditions. Moreover, biotic interactions among taxa further influenced patterns of community restructuring. These findings enhance the understanding of phytoplankton resilience mechanisms under extreme climatic disturbances. The integration of phytoplankton monitoring into coastal early warning systems is recommended to inform adaptive management strategies and mitigate ecological risks associated with the increasing frequency and intensity of typhoons, thereby supporting the sustainable use and conservation of estuarine and coastal ecosystems. Full article

The deployment of floating offshore wind turbines (FOWTs) in deep, typhoon-prone waters like the South China Sea requires platforms with exceptional stability. However, the performance validation of novel Tension Leg Platform (TLP) concepts under such extreme metocean conditions remains a significant research gap. This study addresses this by numerically evaluating a novel TLP design, including a regular hexagonal topology, a unique bracing structure and heave plates, and an increased ballast-tank height. A coupled numerical framework, integrating potential-flow theory and blade element momentum (BEM) theory within ANSYS-AQWA (2023), was established to simulate the TLP’s dynamic response to combined irregular wave, current, and turbulent wind loads. The resulting time-series data were analyzed using the Continuous Wavelet Transform (CWT) to investigate non-stationary dynamics and capture transient peak loads critical for fatigue sizing, which demonstrated the platform’s superior stability. Under a significant wave height of 11.4 m, the platform’s maximum heave was limited to 0.86 m and its maximum pitch did not exceed 0.3 degrees. Crucially, the maximum tension in the tendons remained below 22% of their minimum breaking load. The primary contribution of this work is the quantitative validation of a novel TLP design’s resilience in an understudied, harsh deep-water environment, confirming the feasibility of the concept and presenting a viable pathway for FOWT deployment in challenging offshore regions. Full article

Amid long-term human consumption of surface resources and the intensifying climate crisis, underground space has increasingly attracted attention as a viable alternative for habitation, survival, and urban resilience. Historical and contemporary examples—from the Derinkuyu Underground City in Cappadocia, Turkey, to Iran’s “Shavadan” cooling system, as well as subterranean dwellings in hot arid regions such as the Berbers’ homes in Tunisia and miners’ settlements in Coober Pedy, Australia, and underground complexes in cold regions like Harbin, Sapporo, and Helsinki—demonstrate the significant advantages of underground spaces in thermal regulation, protection from extreme weather, and efficient resource utilization. With climate change driving increasingly frequent and severe extreme weather events, including tornadoes, typhoons, and prolonged droughts, surface buildings face growing vulnerability, further emphasizing the potential of underground space for sustainable urban development. In parallel, advances in science and technology, particularly in space exploration, have accumulated extensive practical knowledge, creating pathways to extend terrestrial construction experience into extraterrestrial environments. The Moon, despite its strategic significance and potential resource value, presents an extremely hostile surface environment characterized by microgravity, near-vacuum conditions, extreme diurnal temperature variations of several hundred degrees, and very low thermal conductivity, all of which render conventional surface habitation challenging and prohibitively costly. Consequently, contemporary research has gradually shifted focus from lunar surface facilities toward the development and utilization of lunar underground spaces, which could provide enhanced environmental stability and habitation potential. This paper reviews the historical development and current research on lunar underground space utilization, proposes five guiding principles for its progressive exploration and construction, and presents a phased “1.0–4.0 era” framework for systematic development. Additionally, based on an adaptive design theoretical framework, spatial, environmental, and climatic strategies are proposed to guide future lunar habitation and ensure sustainable extraterrestrial development, providing a comprehensive reference for long-term planning and construction of lunar underground habitats. Full article

Tourism has emerged as a critical economic pillar for many island communities worldwide, transforming their socio-economic structure and land use strategies. However, intensifying typhoons and other extreme climate events pose escalating risks to these communities, demanding adaptive transformations in disaster knowledge systems and risk management strategies. Local disaster knowledge (LDK), as a place-based knowledge system, plays an essential role in shaping adaptive responses and enhancing resilience within these communities. This study investigates the structure and dynamic adaptation paths of local disaster knowledge amid the shift toward tourism-based communities. Using a qualitative approach, this study conducted an in-depth case study on Shengsi Island, China. The findings reveal that LDK exhibits a three-layered structure: deep-intermediate-surface layers. Beliefs constitute the deep core, while social cohesion, risk knowledge and perception form the middle mediating layer. The surface practical layer encompasses early warning systems, anticipatory measures, structural measures, and livelihood adaptation strategies. The interaction among the three layers constitutes the endogenous dynamics driving knowledge adaptation, while macro-level disaster governance and tourism development act as exogenous drivers. Together, these mechanisms facilitate two adaptive pathways: policy-guided structural transformation and tourism-led practical adaptation. This study advances theoretical understanding of LDK by exploring its dynamics in transforming communities, with a framework that can be extrapolated to other disaster risk contexts. It also provides policy-relevant insights for developing disaster resilience and sustainable land use policies in island communities experiencing tourism transformation. Full article

This study investigates landslide occurrence in Taiwan, a region highly susceptible to landslides due to steep mountains and frequent typhoons (TYPs). The primary objective is to understand how both geomorphological factors and TYP characteristics contribute to landslide occurrence, which is essential for improving hazard prediction and risk management. The research analyzed landslide events that occurred during the TYP seasons of 2019 and 2023. The methodology involved using satellite-derived landslide inventories from SPOT imagery for events larger than 0.1 hectares, tropical cyclone track and intensity data from IBTrACS v4 (classified by Saffir–Simpson Hurricane Scale), and detailed topographic variables (elevation, slope, aspect, Stream Power Index) extracted from a 30 m Shuttle Radar Topography Mission Digital Elevation Model (SRTM-DEM). Land use and land cover classifications were based on Landsat imagery. To establish a timeline, landslides were matched with TYPs within a ±3-day window, and proximity was analyzed using buffer zones ranging from 50 to 500 km around storm centers. Key findings revealed that landslide susceptibility results from a complex interplay of meteorological, topographic, and land cover factors. The critical controls identified include elevations above 2000 m, slope angles between 30 and 45 degrees, southeast- and south-facing aspects, and low Stream Power Index values typical of headwater and upper slope locations. Landslides were most frequent during Category 3 TYPs and were concentrated 300 to 350 km from storm centers, where optimal rainfall conditions for slope failures exist. Interestingly, despite the stronger storms in 2023, the number of landslides was higher in 2019. This emphasizes the importance of interannual variability and terrain preparedness. These findings support sustainable disaster risk reduction and climate-resilient development, aligning with Sustainable Development Goals 11 (Sustainable Cities and Communities) and 13 (Climate Action). Furthermore, they provide a foundation for improving hazard assessment and risk mitigation in Taiwan and similar mountainous, TYP-prone regions. Full article

Mangrove ecosystems are vital to coastal carbon cycling, yet their response to extreme climatic events remains underexplored. This study assesses dissolved organic carbon (DOC) dynamics across four ecosystem types—primary mangrove, restored (5-year and 8-year), and bare land—during three typhoons (Maliksi, Yagi, and Trami) that occurred in 2024. DOC concentrations (mol m⁻² s⁻¹) were measured across pre-, during-, and post-event phases and analyzed using boxplots, heatmaps, and ANOVA. Results show that primary mangroves maintained stable DOC levels, indicating strong biogeochemical resilience. Restored plots exhibited phase-dependent DOC variability, with older restoration age linked to improved carbon retention. Bare land showed consistently high DOC release, especially post-event, reflecting vulnerability to hydrological stress. DOC peaks occurred after typhoons, suggesting delayed carbon mobilization via microbial turnover and detrital input. These findings highlight the role of restoration age and vegetation cover in stabilizing coastal carbon under intensifying climatic extremes. Full article

Taipei’s metropolitan region faces frequent typhoon impacts that test its urban resilience. This study examines the relationship between Transit-Oriented Development (TOD) urban spatial forms and Taipei’s resilience against typhoons, considering both physical urban morphology and planning factors. We apply a Dynamic Analytic Network Process (DANP), an integrated DEMATEL-ANP multi-criteria approach to evaluate and prioritize key resilience-related spatial and planning factors in TOD areas. Rather than using GIS flood modeling, we emphasize empirical indicators derived from local data, including urban density, transit accessibility, historical typhoon flood impacts, infrastructure vulnerability, and demographic exposure. An extensive literature review covers TOD principles, urban resilience theory, and DANP methodology, with a particular emphasis on the Taiwanese context and case studies. Empirical results reveal that specific TOD characteristics indeed enhance typhoon resilience. High-density, mixed-use development around transit can reduce overall exposure to hazards by curbing sprawl into floodplains and enabling efficient evacuations. Using DANP, we find that infrastructure robustness and emergency planning capacity emerge as the most influential factors for resilience in Taipei’s TOD neighborhoods, followed by land use and management and transit accessibility. Weighted rankings of Taipei’s districts suggest that centrally located TOD-intensive districts score higher in resilience metrics, while peripheral districts with flood-prone areas tend to lag. The Discussion explores these findings, considering planning policies—noting that TOD can bolster resilience if coupled with adaptive infrastructure and inclusive planning—and compares them with examples like Singapore’s integrated land use and transit strategy, which dramatically reduced flood risk. The study concludes with policy implications for integrating TOD and climate resilience in urban planning, and contributions of the DANP approach for complex urban resilience evaluations. Full article

This study employs an improved fractional-order grey multivariable convolution model (FGMC(1,N,2r)) to predict abalone aquaculture output in Fujian, Shandong, and Guangdong. By integrating fractional-order accumulation (r₁, r₂) with a particle-swarm-optimization (PSO) algorithm, the model addresses limitations of handling multivariable interactions and sequence heterogeneity within small-sample regional datasets. Grey relational analysis (GRA) first identified key factors exhibiting the strongest associations with production: abalone production in Fujian and Shandong is predominantly influenced by funding for aquatic-technology extension (GRA degrees of 0.9156 and 0.8357, respectively), while in Guangdong, production was most strongly associated with import volume (GRA degree of 0.9312). Validation confirms that FGMC(1,N,2r) achieves superior predictive accuracy, with mean absolute percentage errors (MAPE) of 0.51% in Fujian, 3.51% in Shandong, and 2.12% in Guangdong, significantly outperforming benchmark models. Prediction of abalone production for 2024–2028 project sustained growth across Fujian, Shandong, and Guangdong. However, risks associated with typhoon disasters (X₆ and import dependency (X₅) require attention. The study demonstrates that the FGMC(1,N,2r) model achieves high predictive accuracy for regional aquaculture output. It identifies the primary drivers of abalone production: technology-extension funding in Fujian and Shandong, and import volume in Guangdong. These findings support the formulation of region-specific strategies, such as enhancing technological investment in Fujian and Shandong, and strengthening seed supply chains while reducing import dependency in Guangdong. Furthermore, by identifying vulnerabilities such as typhoon disasters and import reliance, the study underscores the need for resilient infrastructure and diversified seed sources, thereby providing a robust scientific basis for production optimization and policy guidance towards sustainable and environmentally sound aquaculture development. Full article