Search Results (84)

Tidal-scale wave modulation is a critical yet complex process in macro-tidal estuaries. This study investigates semidiurnal wave modulations in the Changjiang River Estuary (CRE) using unique, long-term in situ observations and high-resolution ADCIRC–SWAN coupled simulations. Pronounced semidiurnal signals are identified in significant wave height (H_s), mean wave period, and wave direction. Observational results demonstrate that the modulation intensity is highest in Hangzhou Bay and the CRE mouth, decreasing gradually offshore. A key finding is that semidiurnal H_s maxima systematically coincide with peak flood currents and precede high water by approximately three hours. Long-term records confirm that this modulation persists year-round and intensifies during energetic events such as typhoons. The expression of the tidal signal depends on wave composition: wind-sea-dominated conditions exhibit stronger period modulation, whereas swell-dominated conditions favor coherent H_s modulation as kinematic tidal effects remain more apparent in the absence of strong local wind forcing. Numerical sensitivity experiments demonstrate that tidal currents are the primary driver of the observed wave modulation, while water-level effects are largely confined to shallow shoals. The results highlight that accurately reproducing the observed frequency–directional structure requires the inclusion of current-induced Doppler shifts and refraction. Beyond the classical following-current effects, the analysis suggests that the spatial deceleration of currents along the wave path acts as a kinematic trap that focuses wave action and sustains H_s intensification. This mechanism provides a physically plausible explanation for the observed phase relationship and points to the non-local nature of estuarine wave dynamics, where the wave state appears as an integrated response to cumulative current gradients along the propagation path. These findings emphasize the necessity of incorporating wave–current coupling in future coastal modeling and hazard forecasting. Full article

In complex marine environments, the safety and efficiency of ship navigation face dual challenges from static obstacles, such as shallow waters and islands, and extreme dynamic meteorological threats, such as typhoons. Existing path-planning algorithms often struggle to achieve an optimal balance between computational efficiency and risk-avoidance effectiveness when addressing high-frequency dynamic meteorological changes. To address this limitation, this study proposes a Time-Dynamic Theta* (TDM-Theta*) approach. From an algorithmic perspective, this method extends traditional any-angle path planning by introducing a temporal dimension to the search space. For maritime application, it integrates real-time significant wave height as a spatio-temporal dynamic constraint, thereby dynamically evaluating the actual impact of marine meteorology on ship navigability. Simulation tests were conducted through nine experimental cases designed under three typical navigation scenarios: unrestricted waters, complex terrains, and typhoon transits. The results demonstrate that the TDM-Theta* algorithm not only efficiently generates the shortest paths in statically complex terrains but also achieves a 100% proactive risk avoidance rate within the boundaries of the evaluated extreme weather scenarios with multiple concurrent typhoons, incurring negligible computational overhead and low path costs. This research provides robust theoretical and methodological support for real-time safe route decision-making for intelligent ships in complex and volatile environments. Full article

Typhoon track prediction is an important research direction in weather forecasting. Although deep learning methods have achieved some progress in this field, challenges remain, including insufficient fusion of meteorological features, limited capability in modeling temporal and spatial evolution, and high computational cost of some models. To address these issues, this paper proposes a dual-path, multi-modal typhoon track prediction model that incorporates a gated axial Transformer to enhance the modeling of deep structural features in the meteorological environment. Numerical experimental results show that the proposed model achieves higher prediction accuracy than comparative methods in typhoon track prediction tasks across multiple time scales, demonstrating the effectiveness of the approach. Full article

Slow-moving landslides can trigger severe disasters when activated by earthquakes, torrential rains, or typhoons. Early detection is crucial for mitigating loss of life and property damage. Interferometric Synthetic Aperture Radar (InSAR) technology is among the most effective techniques for detecting slow-moving landslides, though its accuracy can be further improved through integration with optical imagery and Digital Elevation Models (DEM). Current machine learning approaches that combine InSAR and optical data suffer from limited efficiency, poor transferability, and challenges in regional-scale application. To address these limitations, this study proposes a multimodal dual-path network that integrates InSAR products with textural information from optical imagery to detect slow-moving landslides. One path processes InSAR deformation rates and topographic factors, while the other incorporates texture information and auxiliary data. Together, these paths extract semantic information from high-dimensional spatial features and condense it into low-dimensional representations. A pyramid pooling module is employed to capture multi-scale features during low-level semantic extraction. For feature fusion, a rate-constrained adaptive module is introduced to enhance the contribution of deformation rates to slow-moving landslides. According to the results, the proposed method improves the F1-score for landslide detection by 6% compared to using InSAR products alone. These results provide reliable technical support for regional landslide inventory compilation and disaster management, as well as new insights for regional-scale surveys in slow-moving landslide-prone areas. Full article

Wide-swath satellite altimetry from the Surface Water and Ocean Topography (SWOT) mission provides an unprecedented opportunity to directly observe kilometer-scale ocean dynamics in two dimensions. In this study, we identify an atypical bimodal seasonal cycle of submesoscale processes in the Kuroshio Large Meander (KLM) region south of Japan using SWOT observations during 2023–2025. Submesoscale eddy kinetic energy (EKE) displays a pronounced winter maximum (December–January) as expected for midlatitude oceans, but also a distinct secondary maximum in late summer (August–September) that coincides with the Northwest Pacific typhoon season. SWOT-based eddy statistics reveal that cyclonic and anticyclonic eddies exhibit enhanced occurrence and intensity in winter and late summer. MITgcm LLC4320 outputs demonstrate that the late-summer EKE peak is primarily driven by typhoons, which rapidly deepen the mixed layer and intensify frontal gradients, leading to an intensification of submesoscale eddies. The Kuroshio path further modulates this response. During the KLM state, buoyancy gradients and mixed-layer available potential energy are amplified, allowing storm forcing to generate strong submesoscale activity. Together, typhoon forcing and current-path variability modify the traditionally winter-dominated submesoscale regime. These findings highlight the unique capability of SWOT to resolve submesoscale processes in western boundary currents during extreme weather events. Full article

Global Navigation Satellite System Reflectometry (GNSS-R) provides a vital means for sea surface wind speed retrieval, yet its application under extreme typhoon conditions remains challenging. Conventional geophysical models (GMFs) saturate in high wind speed regimes (>20 m/s), and deep learning models (e.g., CNNs) are constrained by data sparsity and feature complexity in typhoon environments. To address these issues, we propose a Comparative Learning method of CNN-Transformer with GMF fusion (CLCTG). The CNN branch extracts local coupling patterns, the Transformer branch models global dependencies, and Kullback–Leibler (KL) divergence loss is used for contrastive learning to heighten sensitivity to complex typhoon wind fields. The GMF branch serves as a physical reference/anchor in the low- to moderate-wind-speed range (<20 m/s) to guide the learning of data-driven branches and avoid overfitting by any single data-driven path. The adaptive fusion branch dynamically reweights the three branch outputs, combining local statistical characteristics to improve performance over approximately 0–30 m/s and extending the range of reliable GNSS-R retrieval from about 20 m/s to about 30 m/s; it should be noted that CLCTG exhibits a performance bottleneck in the extreme >30 m/s range. To further improve high-wind-speed predictions, we introduce environmental features based on their correlation with wind speed; ablation experiments demonstrate that the combined use of environmental parameters and CYGNSS features maximizes overall accuracy. Testing on five typhoons from the Eastern and Western Hemispheres confirms CLCTG’s generalization across diverse geographic contexts, and branch-wise comparisons validate its structural advantages. Buoy observations show peripheral errors below 3 m/s and physically consistent wind speed gradients in the core region. These results indicate that multi-source fusion of CYGNSS and environmental data, coupled with contrastive learning and physical reference, offers a reliable and efficient solution for typhoon wind speed retrieval. Full article

Although previous studies composited response of sea surface temperature (SST) to typhoon sea surface wind (SSW) forcing around typhoon center, how SST responded spatiotemporally along the typhoon track over the ocean remains unclear. Through Empirical Orthogonal Function (EOF) analysis, several isolated typhoons in the Western North Pacific (WNP) from 2021 to 2024 were investigated. Two SSW forcing modes and two SST response modes were identified. The first SSW mode spatially reflects the overall distribution of SSW along the track, centering at its maturation position. And the first SST mode exhibits a high spatial correlation ($\left|R\right|>0.85$) with this SSW mode. The second SSW mode displays a distinct track-long scale dipole pattern along the path of the typhoon, representing its intensity variation during the “development–maturation–decay” lifecycle. Similarly, the second SST response mode shows a significant but lower correlation with this second SSW mode. Both corresponding SST response modes typically lag behind their respective wind-forcing by approximately 2 to 4 days, indicating that these SST response modes are direct reactions to SSW forcing. These cases implies that two track-long scale SSW modes are generally present during the lifecycle of typhoons and that their corresponding SST responses are dominated accordingly. Full article

This study analyzes wave data from Typhoons Hinnamnor and Muifa in 2022, improves the traditional one-dimensional wind–wave and swell separation method (PM method), and proposes a wind–wave and swell separation strategy suitable for the Dafeng sea area during typhoon events. Combining this with the WH enables high-precision separation of wind–wave and swell. A numerical model of MIKE21 SW waves was established based on the superposition of the Holland typhoon wind field and the ERA5 background wind field. Furthermore, the study conducts controlled variable experiments through numerical simulations to systematically quantify the differential effects of the maximum wind speed radius (RMW), translation speed, and track geometry. The mathematical model in this study couples MIKE 21 SW and MIKE 21 FM, importing hydrodynamic conditions through FM as key variables into the SW model. This enables real-time data exchange during the computational process, thereby yielding results that better align with physical reality. The results from factorial sensitivity experiments demonstrate that the significant wave height and average period of offshore waves, far from the typhoons, significantly increase with the expansion of the maximum wind speed radius, with wave heights at offshore points reaching a maximum of 7.5 m. Specifically, when the RMW increased by 50%, the wave height increased by 2.5 m. The wave characteristics of landing typhoons are more influenced by terrain effects and the location of typhoon landfall. Additionally, changes in typhoon translation speed lead to a first increase and then a decrease in significant wave height. The typhoon’s path significantly affects the propagation direction and energy distribution of waves. In the Dafeng area, distant typhoons often generate long-period swells, which continuously exert high loads on actual engineering foundations. These findings inform early warning systems and the design of shelf-aware port and coastal infrastructure in northern Jiangsu and similar regions. Full article

A series of multi-parameter, multi-layer observations was conducted to study possible electromagnetic precursors associated with the M 6.7 earthquake that struck Iburi, Hokkaido, Japan, at 18:07:59 UT on 5 September 2018. The most significant observation is seismogenic lower-ionospheric perturbations in the propagation anomalies of sub-ionospheric VLF/LF signals recorded in Japan and Russia. Other substantial observations include the GIM-TEC irregularities, the intensification of stratospheric atmospheric gravity waves (AGWs), and the satellite and ground monitoring of air temperature (T), relative humidity (RH), atmospheric chemical potential (ACP), and surface latent heat flux (SLHF). We have found that there were very remarkable VLF/LF anomalies indicative of lower-ionospheric perturbations observed on 4 and 5 September just before the EQ date and even after it from the observations in Japan and Russia. In particular, the anomaly was detected for a particular propagation path from the JJY transmitter (Fukushima) to a VLF station at Wakkanai one day before the EQ, i.e., on 4 September, and is objectively confirmed by machine/deep learning analysis. An anomaly in TEC occurred only on 5 September, but it is unclear whether it is related to a pre-EQ effect or a minor geomagnetic storm. We attempted to determine whether any seismo-related atmospheric gravity wave (AGW) activity occurred in the stratosphere. Although numerous anomalies were detected, they are most likely associated with convective weather phenomena, including a typhoon. Finally, the Earth’s surface parameters based on satellite monitoring seem to indicate some anomalies from 29 August to 3, 4, and 5 September, a few days prior to EQ data, but the ground-based observation close to the EQ epicenter has indicated a clear T/RH and ACP on 2 September with fair weather, but no significant data on subsequent days because of severe meteorological activities. By integrating multi-layer observations, the LAIC (lithosphere–atmosphere–ionosphere coupling) process for the Hokkaido earthquake appears to follow a slow diffusion-type channel, where ionospheric perturbations arise a few days after ground thermal anomalies. This study also provides integrated evidence linking concurrent lower-ionospheric, atmospheric, and surface thermal anomalies, emphasizing the diagnostic value of such multi-parameter observations in understanding EQ-associated precursor signatures. Full article

This paper reports on the study of turbulence at various locations in Hong Kong during Typhoon Wipha in July 2025, including turbulence intensity based on Doppler Light Detection and Ranging (LIDAR) systems and radiosondes, observations by microclimate stations, and low-level windshear and turbulence at the Hong Kong International Airport (HKIA) by LIDAR, flight data, and pilot reports. Although the observation period was primarily limited to 20 July 2025, passage of a typhoon over a densely instrumented urban area is uncommon; these observations on turbulent flow associated with typhoons therefore can serve as valuable benchmarks for similar studies on turbulent flow associated with typhoons in other coastal areas, particularly for operational alerts in aviation. To assess the predictability of turbulence, the eddy dissipation rate (EDR) was derived from a high-resolution numerical weather prediction (NWP) model using diagnostic and reconstruction approaches. Compared with radiosonde data, both approaches performed similarly in the shear-dominated low-level atmosphere, while the diagnostic approach outperformed when buoyancy became important. This result highlights the importance of incorporating buoyancy effects in the reconstruction approach if the EDR diagnostic is not available. The high-resolution NWP was also used to provide time-varying boundary conditions for computational fluid dynamics simulations in urban areas, and its limitations were discussed. This study also demonstrated the difficulty of capturing low-level windshear encountered by departing aircraft in an operational environment and demonstrated that a trajectory-aware method for deriving headwind could align more closely with onboard measurements than the standard fixed-path product. 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

Cloud liquid water content (CLWC) based on microwave radiometer data was investigated in this study. First, its consistency with radiosonde-based CLWC was established. Integrated CLWC was also checked against the liquid water path. CLWC performance in four weather types was considered: dense fog, clouds in spring, rainstorms, and typhoons. CLWC provides new insights into weather events. In particular, it could be useful for nowcasting low visibility associated with sea fog. It was also found to be inversely proportional to visibility in two cases of low visibility in Hong Kong. In springtime, low-level clouds and liquid water were found to exist extensively inside clouds. In rainstorm cases, supercooled cloud liquid water was absent during heavy rain but may exist within clouds when rain stops or light rain occurs. Similar observations were made in typhoon cases, namely during the direct impact of Typhoon Wipha on Hong Kong. Supercooled cloud liquid was present when outer rainbands of the typhoon affected Hong Kong with a smaller amount of rainfall. However, when Hong Kong was hit by a typhoon’s eyewall, rain was heavier, and supercooled liquid water was absent. These features are consistent with the radiosonde-based CLWC profiles. Radiometer-based CLWC is pseudocontinuous and provides additional insight into liquid water distribution in clouds under various weather conditions. Full article

In recent years, frequent typhoon-induced disasters have significantly increased the risk of power grid outages, posing severe challenges to the secure and stable operation of distribution grids with high penetration of distributed photovoltaic (PV) systems. Furthermore, during post-disaster recovery, the dual uncertainties of distributed PV output and the charging/discharging behavior of flexible resources such as electric vehicles (EVs) complicate the configuration and scheduling of mobile energy storage systems (MESS). To address these challenges, this paper proposes a two-stage robust optimization framework for dynamic recovery of distribution grids: Firstly, a multi-stage decision framework is developed, incorporating MESS site selection, network reconfiguration, and resource scheduling. Secondly, a spatiotemporal coupling model is designed to integrate the dynamic dispatch behavior of MESS with the temporal and spatial evolution of disaster scenarios, enabling dynamic path planning. Finally, a nested column-and-constraint generation (NC&CG) algorithm is employed to address the uncertainties in PV output intervals and EV demand fluctuations. Simulations on the IEEE 33-node system demonstrate that the proposed method improves grid resilience and economic efficiency while reducing operational risks. Full article

Severe Typhoon Danas over the northern part of the South China Sea and seas near Taiwan in early July 2025 had an erratic path that had not been observed before, according to historical data in the region. Its formation, movement, and intensification posed significant challenges to the timely tropical cyclone (TC) warning services. This paper documents the observational aspect and forecasting aspect of this cyclone. There are key findings: (a) when Danas interacted with the Central Mountain Range of Taiwan, a “secondary cyclone” appeared over the northeastern part of Taiwan, which was observed by both weather radars and meteorological satellite winds, and was simulated to a certain extent by a mesoscale numerical weather prediction (NWP) model; (b) data-driven AI global models performed better than physics-based global NWP models in capturing the formation and the rather erratic track of Danas a couple of days earlier, although AI models generally underestimate the intensity forecasts; and (c) an atmosphere–ocean–wave coupled model was found to perform the best in capturing both the track changes of Danas (because of being driven by an AI global model) and its intensity changes (because of better physical representation of the oceanic impact on the intensity of this TC), whereas AI global models, though with various recent enhancements, still tended to underestimate the strength of Danas. This paper serves as a reference of this rather unusual TC for the weather forecasting services in the region. Full article

The large-scale integration of wind power into coastal power systems introduces significant challenges to reserve planning, especially under the threat of typhoons, which can cause extensive generation loss and threaten system security. Conventional reserve planning methods often fail to account for such extreme typhoon events. To fill the gap, this paper proposes a novel two-stage reserve planning framework that integrates economic optimization with operational security verification. In the first stage, a diverse set of high-impact typhoon scenarios are generated using a multivariate Markov chain Monte Carlo (MMCMC)–based path reconstruction method, which captures the dynamic evolution of key typhoon characteristics. In the second stage, the economically optimal reserve capacity is identified through cost-benefit analysis and then validated against the typhoon scenarios via N − 1 security verification. A case study on the modified IEEE RTS79 test system indicates that economically optimal reserve may be inadequate for ensuring security under severe typhoon conditions. However, a small increase in reserve capacity can effectively enhance system resilience with minimal additional cost. These results highlight the importance of incorporating typhoon scenario-based security verification into reserve planning especially for high-penetration wind power systems in coastal regions. Full article