Search Results (1,042)

Climate change amplifies both chronic and episodic environmental risks, intensifying long-term exposure patterns that are unevenly distributed across space. This paper examines how differentiated regional climate and environmental risks in Thailand shape long-term well-being, and how the Sufficiency Economy Philosophy (SEP)—a Thai-origin framework grounded in three core principles of moderation, reasonableness/prudence, and self-immunity—may function as a diagnostic and adaptive sustainability framework within environmental and hazard geography. Using a comparative empirical environmental-risk analysis of secondary longitudinal datasets, the study examines four purposively selected regions—Chiang Mai, Bangkok, Rayong, and the southern Andaman and Gulf coasts (Phuket, Phang Nga, Songkhla)—chosen to maximise variation in exposure type and hazard. We also apply SEP’s three principles analytically within each regional case. Th findings show that chronic, low-intensity exposure—such as Chiang Mai’s seasonal PM2.5 haze and Bangkok’s combined air pollution and flooding—generates cumulative well-being costs that differ qualitatively from those associated with episodic, catastrophic hazards such as the 2004 Indian Ocean tsunami and Tropical Cyclone Pabuk. Deaths attributable to air pollution in Thailand rose from 47,709 in 2016 to 55,877 in 2022, underscoring that chronic exposure imposes a health and economic burden comparable in scale to discrete disaster events. Adaptive capacity, not exposure alone, differentiates regional outcomes: Rayong’s industrially concentrated coastal corridor exhibits a spatial monitoring scale mismatch, with city-level averages substantially underrepresenting industrial-core peak exposure in Maptaphut district. The paper concludes that durable adaptation requires shifting from reactive normality toward anticipatory, spatially differentiated resilience, and that this paper is best understood as methodological groundwork for a larger research programme requiring primary household-level well-being surveys and finer-resolution geospatial exposure mapping. Full article

Accurate forecasting of significant wave height (SWH) during tropical cyclones (TCs) is important for coastal risk management. This study develops a multi-horizon TC-aware sequence-to-sequence (MH-TCSeq2Seq) framework for 12 and 24 h lead time forecasting at eight Guangdong–Hong Kong stations, utilizing marine and historical TC data as baseline inputs. An enhanced variant integrated with 6–24 h future TC trajectory information (MH-TCSeq2Seq-FutureTC) is further established using retrospective best track data as an idealized upper bound benchmark. Evaluation against the ERA5 reanalysis data shows that MH-TCSeq2Seq-FutureTC achieves the lowest overall root mean square error (RMSE), reaching 0.207 m at 12 h and 0.307 m at 24 h. It reduces the TC-associated RMSE by 9.6% and 7.3% relative to the MH-TCSeq2Seq baseline. Statistical validation confirms the overall robustness of this forecasting improvement across TC events. Adding identical future TC predictors to Quantile Bidirectional Gated Recurrent Unit and TC-gated Bidirectional Gated Recurrent Unit degrades performance, indicating that such benefits are architecture dependent. Replacing these track inputs with operational forecast descriptors from the Automated Tropical Cyclone Forecasting System still reduces the TC-associated RMSE by 6.1% and 4.7% relative to MH-TCSeq2Seq. Interpretability analyses confirm the model’s reliance on future TC information for improving SWH forecasting. Full article

Reliable in situ observations of sea surface wind (SSW) in tropical cyclones (TCs) remain extremely limited because of the difficulty of operating conventional observing platforms under severe weather conditions. Autonomous, uncrewed surface vehicles (USVs), such as Wave Gliders (WGs), offer a promising solution, but their observational reliability under TC conditions has not been systematically assessed. This study presents a comprehensive evaluation of WG-derived SSW measurements in TCs using (1) internal quality assessment, (2) inter-sensor consistency analysis, and (3) comparisons with satellite observations (AMSR2, SMAP, ASCAT, and SAR) and a numerical weather prediction (NWP) model (JMA LFM). Before evaluating inter-sensor consistency, the influence of platform motion on the 10 m height conversion was assessed. The effect of platform motion correction was negligible, with a maximum RMSE of 0.11 m/s for wind speed and only minor changes in wind direction. Comparisons between sensors mounted on different USVs using 10 m-height-normalized winds showed good agreement over the wind-speed ranges sampled during the TC cases, with the most stable agreement observed under moderate-to-high wind conditions. Comparisons with external datasets also showed good consistency, although the statistical robustness varied among products because of differences in the number of available collocations. For samples within 500 km of the TC center, wind speed RMSE ranged from approximately 0.9 to 4.4 m/s among individual satellite products, while the integrated satellite comparison yielded an RMSE value of 2.36 m/s and the LFM comparison yielded an RMSE of 2.35 m/s. An integrated comparison using all available satellite products also showed strong agreement for wind speed, while the LFM exhibited variability comparable to that of the WG observations under TC-approach conditions. However, the number of independent collocations above 25 m/s was limited, precluding a robust assessment under extreme TC wind conditions. These results demonstrate that mid-size USVs can provide consistent and valuable in situ SSW observations over the range of TC conditions evaluated in this study and highlight their potential for evaluating satellite wind products, supporting NWP model improvement, and advancing air–sea interaction studies in extreme weather environments. Full article

This study investigates the sensitivity of hurricane track and intensity forecasts to various cumulus parameterization schemes with scale-awareness, including the Simplified Arakawa-Schubert (SAS), Relaxed Arakawa-Schubert (RAS), and Chikira-Sugiyama Arakawa-Wu (CSAW), within the NOAA Global Forecast System (GFS) version 17 framework. Using a set of nine initial conditions for Hurricane Ian (2022), we demonstrate that schemes utilizing a spectrum of cloud types (RAS and CSAW) produce westward-shifted trajectories compared to the single-cloud SAS scheme, which exhibits an eastward track bias. When testing the sensitivity of the CSAW convective parameterization with Wb (cloud-base vertical velocity) spectrum and entrainment rates, a critical inverse relationship was revealed between parameterized convective strength and resolved storm intensity. Specifically, reducing the W_b range or increasing entrainment attenuates the sub-grid scale convective response, facilitating a compensatory intensification of the resolved-scale vortex and kinetic energy. Spectral analysis indicates that cloud-spectrum schemes exhibit reduced energy variance in low-frequency modes, which directly impacts large-scale steering. Furthermore, the results suggest that differences in the spatial orientation of PV anomalies may contribute to the simulated track divergence, with the storm propagating toward regions of maximum PV gradient. These findings underscore that the representation of the cloud spectrum and the subsequent energy partitioning between parameterized and resolved scales are important on tropical cyclone evolution in high-resolution numerical weather prediction models. Full article

Offshore wind development in the Colombian Caribbean requires characterization of tropical cyclone exposure to support climate-resilient planning, yet objective regime classifications for this basin remain limited. This study develops an unsupervised Self-Organizing Map (SOM) framework using the NOAA HURDAT2 best-track database for 1970–2023, comprising 668 six-hourly observations from 103 storms and nine physically interpretable features describing position, intensity, kinematics, and seasonality. A 4 × 4 SOM combined with hierarchical Ward clustering identified four cyclone exposure regimes: R0, late-season slow north-eastward disturbances near San Andrés (11.5%); R1, fast westward mature tropical storms across the central Caribbean (62.0%); R2, slow north-westward disturbances off Central America (21.9%); and R3, rare major hurricanes crossing the central Caribbean (4.6%, seven storms; historical mean recurrence interval 7.7 years). R3 exhibited mean maximum sustained winds of 67.8 m/s and a minimum central pressure of 938.5 hPa, with peak winds reaching 79.7 m/s. The results provide a complementary historical hazard characterization layer for offshore wind planning, supporting risk-informed spatial and operational assessment. However, the identified regimes do not represent wind-resource conditions or probabilistic design return periods and should therefore be integrated with site-specific wind, wave, and structural assessments. Full article

Island terrain poses a significant challenge in tropical cyclone (TC) track prediction, particularly during the early development of TCs. Using the Weather Research and Forecasting (WRF) model, China Meteorological Administration (CMA) best-track data, and ERA5 reanalysis, we conducted control (CTRL), terrain-removal (Te0P), terrain-enhancement (Te2P), and no-land-sensible-heat (HFX0) experiments for Typhoon Yagi (2024) near Luzon during 1–3 September. CTRL showed a pronounced northward track bias. Te0P shifted westward and closer to observations, whereas Te2P further amplified the northward bias; HFX0 remained close to CTRL. Terrain-height changes substantially modified the surrounding mid-tropospheric environmental flow and asymmetric horizontal-advection potential-vorticity tendency (PVT_h). Although Te0P produced the closest track, its PVT_h orientation deviated most from ERA5, suggesting that the track improvement partly reflects a compensating reduction in the excessive northward response in CTRL rather than a uniformly more realistic dynamical structure. Land sensible heating mainly affected the boundary layer and nearby circulation, with weaker effects on the broader mid-tropospheric flow and track. These results show that terrain dynamics dominate the simulated track response, while land sensible heat provides secondary modulation, and highlights the need to evaluate track, environmental flow, and PVT_h jointly near complex islands. Full article

Tropical cyclone (TC) intensity estimation over the western North Pacific remains affected by uncertainties in satellite observations, best-track records, and rapidly evolving inner-core structures. To further exploit information on cloud-system vertical structure and its temporal evolution, this study introduces FY-4A/B cloud-top height (CTH) products and develops CTH-TCNet, a three-branch gated-fusion model that integrates infrared brightness temperature, CMORPH precipitation, and multidimensional CTH information for TC intensity estimation. The model consists of a CNN-based spatial branch, an LSTM-based temporal branch representing CTH evolution over the preceding 12 h, and a shortcut branch preserving current-time CTH statistics. Systematic ablation experiments show that the contribution of CTH is closely related to its representation and fusion strategy. Directly adding a single-time-step two-dimensional CTH field as an additional spatial channel provides no further performance gain, whereas historical CTH evolution and current-time CTH statistics provide complementary information. Jointly representing these two types of information through the temporal and shortcut branches yields the best performance. The final model achieves an MAE of 6.26 kt and an RMSE of 7.41 kt on the test sets. Intensity-stratified results further show that CTH generally provides larger improvements for TY, STY, and Super TY than for TS. Interpretability analyses indicate that, as TC intensity increases, the model exhibits greater reliance on CTH temporal evolution and structural information from the inner-core and eyewall-adjacent regions, with these dependence patterns being broadly consistent with known characteristics of TC inner-core convective organization and eyewall-related structures. These results indicate that FY-4A/B CTH provides valuable complementary structural and temporal information for satellite-based TC intensity estimation. Full article

Convection-permitting simulations resolve the deep convective cells that organise Mediterranean tropical-like cyclones. They also generate localised pressure minima that can capture a conventional cyclone tracker and pull it away from the synoptic-scale centre. We introduce High-Resolution Multilevel Python-Based Algorithm for Cyclones’ Centroid Tracking (HIMPACT), an open-source Python algorithm developed by the corresponding author within the CETEMPS framework, that stabilises cyclone-centre identification by combining three elements: a multi-level geopotential analysis restricted to the 800–950 $\mathrm{hPa}$ layer, a percentile-based threshold that isolates the vortex core from convective perturbations, and a convex-hull centroid that depends on the geometry of a percentile-defined core rather than on a single extreme grid point, so that an isolated convective pressure deficit cannot displace the estimate by more than a fraction of the core radius. HIMPACT was evaluated in four tracking experiments across three Mediterranean cyclones at grid spacings from 2 to 28 $\mathrm{k}\mathrm{m}$ using WRF, ICON-DREAM and ERA5, while MPAS was additionally used to test portability and computational scaling on an unstructured Voronoi mesh. Across the three experiments in which the driving data resolve a coherent lower-tropospheric cyclone structure, the best five-level configurations reduce root-mean-square displacement errors by approximately 16–48% relative to the corresponding single-level configurations. Activating the absolute minimum alongside the centroid more than doubles the error variance when the pressure field is multi-modal. The 800–950 $\mathrm{hPa}$ window avoids both surface extrapolation artefacts below 950 $\mathrm{hPa}$ and mid-tropospheric steering signatures above 800 $\mathrm{hPa}$. A counterexample with an extratropical storm exposes a data-quality threshold: when the driving dataset does not resolve a vertically coherent cyclone structure, the multi-level weighted mean diverges, and single-level tracking becomes the safer choice. HIMPACT is model-agnostic, requires no format conversion, and runs on a single CPU core at approximately 9.8–41.3 s per time step for the recommended five-level configuration across the tested back-ends; substantially larger costs occur for high-level-count MPAS configurations. Full article

Tropical cyclones can rapidly alter vegetation structure and resource availability in Caribbean island ecosystems, yet species-specific, island-wide assessments of avian resilience remain limited. We integrated remotely sensed vegetation greenness, topographic data, and citizen-science observations to evaluate post-hurricane resilience in the Puerto Rican Emerald (Riccordia maugaeus), an endemic hummingbird of Puerto Rico. We defined resilience through post-disturbance decline, recovery toward baseline reporting probability, and local persistence. We analyzed 89,682 filtered eBird checklists from 2013 to 2025 across three hurricane-related periods: Pre-Maria, Inter-Hurricanes, and Post-Fiona. Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Shuttle Radar Topography Mission elevation data were linked to checklist locations to quantify environmental gradients associated with reporting probability and occupancy dynamics. Binomial generalized linear models showed that reporting probability was strongly associated with elevation, NDVI, sampling effort, and a Period × Elevation interaction. Predicted reporting probabilities were lowest during the Inter-Hurricanes period and were closer to Pre-Maria levels in the Post-Fiona period, particularly at higher elevations. Dynamic multi-season occupancy models showed that initial occupancy increased with elevation and NDVI, whereas local extinction probability decreased with both elevation and NDVI. These findings indicate that post-hurricane reporting probability and local persistence in the Puerto Rican Emerald were associated with elevation and vegetation condition, with higher-elevation and greener sites representing candidate areas for monitoring and potential conservation action. Full article

Mutual interactions exist between tropical cyclones and the East Asian mid-latitude trough (EAMT). This study mainly used statistical analysis and numerical experiments to investigate the influence of TCs on the zonal movement of EAMT. Composite results indicate that TCs can induce an average of 11.82 degrees in the EAMT meridional displacement, and the anomalous remote geopotential height (HGT) triggered by TCs serves as an important factor driving the zonal movement of the EAMT. The EAMT tends to move towards the region of negative HGT difference and away from the region of positive HGT difference. The temperature anomalies induced by TCs are a critical factor leading to the HGT anomalies. For the TC Maria case, it induces a maximum meridional displacement of 0.76 degrees of the EAMT at 450 hPa. TC Maria first triggers anomalous cold advection in the mid-latitude regions of the East Asia–Northwest Pacific area, which then leads to an anomalous decrease in HGT within the EAMT trough region under the constraint of hydrostatic equilibrium. Consequently, the anomalous negative HGT caused by the TC results in the zonal movement of the EAMT line. The results of this study provide evidence that remote disturbances induced by TCs in the tropical WNP can affect weather circulation in the mid-latitudes of East Asia. Full article

Parametric insurance products for tropical cyclone risk transfer typically rely on maximum wind speed (MWS) as the only trigger parameter. While interpretable and widely used, it nevertheless leaves a substantial portion of loss variance unexplained. This paper proposes and evaluates two dual-parameter extensions of the cat-in-a-grid parametric framework, combining MWS with either the radius of maximum wind speed (RMW) or minimum central pressure (MCP). Two integration strategies are examined: a stratified approach, in which events are partitioned by the secondary parameter and separate MWS-based loss functions are fitted within each stratum, and a multivariable approach, in which both parameters enter a bivariate polynomial loss function directly without event partitioning. Four dual-parameter configurations are evaluated against a single-metric MWS baseline using 5-fold cross-validation (CV) on a large stochastic catalog for Jamaica, across four training data strategies. Results show that RMW improves predictive accuracy over the MWS baseline under most training strategies, although the multivariable extension underperforms the baseline under binned training. MCP, by contrast, offers only a marginal benefit that disappears under binned training, consistent with its strong correlation with MWS. In addition, results also show that multivariable models require IQR-filtered raw training to realize their potential, while stratified models perform best with binned training. Full article

As crucial weather-scale systems widely affecting the global marine-atmospheric boundary layer, cyclones exert a regulatory effect on aerosols in the marine boundary layer through interrelated physical and chemical processes, including dynamic uplift, strong wind forcing, precipitation scavenging, and cloud microphysical interactions. Following an overview of aerosol properties in the marine boundary layer and synoptic cyclone characteristics, this paper reviews the full-process regulation mechanisms and mutual feedback effects of tropical and extratropical cyclones on aerosol generation, long-range transport, and removal, integrating the latest advances in observational, numerical, and theoretical studies. Cyclone-driven aerosol generation has two key pathways: mechanical fragmentation of sea surfaces in cyclones’ strong wind cores, emitting sea salt aerosols of varying particle sizes, and cyclone-induced disturbances triggering photochemical and heterogeneous reactions that accelerate secondary aerosol formation. Cyclone movement, with strong advection and updrafts, enables cross-ocean long-distance transport and upper troposphere injection of aerosols in the marine boundary layer, altering their global distribution. Wet deposition (rainout and washout) is the dominant removal mechanism, eliminating aerosols and mediating the cyclone–aerosol–cloud feedback loop, where aerosols as cloud condensation nuclei or ice nuclei regulate cyclone intensity, precipitation, and cloud cover. Current challenges (e.g., emission quantification uncertainties, incomplete microphysical understanding, model limitations) and prospects (e.g., enhanced long-term observations, improved model parameterization) are discussed. This review provides a scientific basis for aerosol-climate effect studies under extreme weather and references for related fields. Full article

Accurately forecasting waypoint-level tropical cyclone (TC) intensity, defined as the local wind speed at specific maritime route waypoints under TC influence, is crucial for navigation safety and voyage planning. Conventional studies mainly focus on the central intensity of TC systems and underutilize the complementary value of multimodal meteorological data with inconsistent sampling intervals. To address these challenges, this study proposes a multimodal-augmented conditional diffusion model (MADiff) for waypoint-level TC intensity prediction. To exploit the potential of multimodal inputs, we first design a temporal-adaptive dynamic convolution module (TDConv) to capture multi-timescale features, mitigating multimodal sampling discrepancies without rigid temporal alignment. Second, we develop a discriminative cross-fusion module (DisCF) to aggregate multi-timescale features across diverse modalities, quantifying multimodal heterogeneity and integrating valuable modality-specific features while suppressing noise interference. Fused features are fed into a diffusion model with physics-informed regularization to generate final intensity forecasts. Extensive experiments on four Western North Pacific datasets show that MADiff achieves average MAE and RMSE values of 2.08 kt and 2.37 kt, respectively, for 12 h intensity forecasting. Compared with the state-of-the-art baseline (TC-Clouds-DP), MADiff yields substantial performance improvements, reducing MAE by 16.3% and RMSE by 10.6% on average. This study provides an effective framework for fine-grained TC intensity forecasting, offering valuable insights for extreme marine weather early warning and intelligent navigation decision-making. Full article

East Asia is both the densest subsystem of the global liner shipping network and the home basin of its signature hazard, the typhoon. This study quantifies the relationship in both directions, as a stress test of the sustainability of maritime connectivity, across Alphaliner-based reconstructions of the 2017 and 2021 networks that cover every port with at least one scheduled liner service. A Typhoon Vulnerability Index built from validated IBTrACS exposure, betweenness sensitivity, and national adaptive capacity scores 330 and 272 affected ports. The risk geography anchors in East Asia in both years and more strongly in the second, as the regional share of affected ports is 29 percent in 2017 and 44 percent in 2021, the 2017 top five are all East Asian, and the 2021 top four are all Chinese, led by Shanghai. Removing every indexed typhoon port in descending risk order destroys 47.5 and 41.3 percent of baseline efficiency. Equal-sized random removals destroy a similar share at the end, so the information of the hazard ordering lies earlier and elsewhere, in early losses that run about forty percent above the random expectation, in seven of the ten earliest failures being invisible to degree screening, and in the identity of the removed ports, while equal-depth-degree targeting destroys far more at every stage. An East Asia-only attack reproduces a third of the full attack’s damage in 2017 and half in 2021. Under one fixed baseline, East Asia carries 23.8 and 24.6 percent of global efficiency before the attack and its survivors retain 7.1 and 3.6 percent after it. On the evidence of these two years, the typhoon corridor is a jointly held systemic asset, its protection is a problem shared by the three economies, and the bidirectional accounting gives sustainable maritime transport a measurable resilience baseline under a warming climate. Full article

Tropospheric evaporation ducts can trap radio waves within a refractive layer, which may guide signals above 1 GHz, enabling beyond-line-of-sight transmission. This makes duct-assisted propagation attractive for maritime communications. The marine environment is characterized by complex hydrometeorological variability and frequent extremes, particularly tropical cyclones, which can perturb duct properties and degrade link reliability. This study develops a multivariate cyclone-aware nonlinear regression framework (CNRF) to estimate contemporaneous evaporation duct strength (EDS) by integrating high-resolution dropsonde observations with tropical-cyclone descriptors from the International Best Track Archive for Climate Stewardship (IBTrACS). The framework uses CatBoost, natural-gradient boosting (NGBoost), and a multilayer perceptron (MLP) as base learners, with a random forest (RF) serving as the second-stage nonlinear fusion model. Rather than relying solely on bulk physical parameterization, the framework aims to represent the nonlinear influence of tropical cyclone-related environmental factors on duct strength. Evaluated over 1996–2024, the CNRF attains a test-set R² of 0.791 and a root mean square error (RMSE) of 5.350 M-unit, corresponding to a 23.5% improvement in RMSE over the Naval Postgraduate School (NPS) numerical model. For Hurricane Fiona (2022), the model achieves an RMSE of 6.260 M-unit, and the inclusion of tropical cyclone descriptors improves RMSE by approximately 17.0% relative to a model that excludes tropical cyclone information. The proposed framework facilitates quantitative assessment of extreme-weather-driven duct variability and supports robust design and operation of duct-enabled maritime communication systems. Full article