Search Results (182)

Under the background of global warming, high-tide floods pose growing threats to China’s coastal ecosystems, infrastructure and freshwater supplies. Although the occurrence of high-tide flooding events is widely recognized as being related to relative sea-level rise, tides, and residuals, the analysis and attribution of individual events remain relatively scarce. Based on tide-gauge data and numerical simulations, this study conducted a quantitative analysis of the high-tide flooding events along China’s southern coast around 19 November 2024 and provides mitigation recommendations. Results indicate that coastal sea levels south of the Yangtze River Estuary in November 2024 hit the third-highest November value on record. Sea levels south of the Taiwan Strait were 26 cm above those of normal years, with the highest monthly level since that recorded in 1980. Around 19 November, the coastal area levels coincided with the astronomical spring tide period, with the astronomical high water levels in Shanwei (Guangdong), Dongfang (Hainan), and Beihai (Guangxi) reaching 116 cm, 186 cm, and 292 cm above local mean sea level, respectively. Additionally, influenced by the outer circulation of the tropical cyclone Man-Yi and a cold-air process, an extensive coastal surge occurred, with 30~80 cm surges persisting for nearly 30 h. The combined effects of high sea levels, spring tides, and abnormal surges triggered extreme sea levels that broke historical records, with multiple stations reaching once-in-20-year levels. The contributions of astronomical tides to the extreme sea levels in Shanwei, Dongfang and Beihai were 49.5%, 69.3%, and 77.8%, respectively, while the contributions of surges were 23.6%, 6.4%, and 4.6%. This high-tide flooding event affected multiple coastal areas in Guangdong, Guangxi, and Hainan. Developing a comprehensive adaptation strategy encompassing emergency observation and early warning, risk assessment and zoning, coastal protection, coastal adaptive planning, and freshwater resources management is crucial for effectively addressing the risks of high-tide flooding events. Full article

Fujian sea areas suffer frequent disastrous wave events in southeast China. Research on wave characteristics are crucial for marine engineering and coastal disaster risk reduction. Based on TOMAWAC hindcast wave data, this study analyzes the spatiotemporal variations in wave parameters in the Fujian sea areas during 1980–2023. Six typical feature points are selected for comparative analysis to clarify wave climate features across different water depths. Results indicate that the maximum significant wave height (SWH) in the Fujian sea area declines from offshore to inshore and from north to south, with a peak of 15 m off Ningde. Seasonally, maximum SWH is induced by tropical cyclones in summer and autumn, generally exceeding 10 m. Under the influence of the East Asian monsoon, the mean SWH reaches its annual maximum of 2.5 m during the winter season. Severe waves show a stepped increasing from inshore to offshore seas, with the longest duration in autumn. The Taiwan Strait is characterized by a widespread high SWH region, where severe wave events persist for more than 15 h. Fujian sea wave variations are governed by water depth-topography effects and seasonal wind-swell regimes. Full article

In the context of global climate warming, sea surface temperature (SST) rise and sea level (SL) rise are projected to amplify typhoon-related marine dynamic disaster risks. These are idealized sensitivity experiments designed to isolate the individual effects of SST warming and SL rise, not full climate projections. This study investigates Super Typhoon Doksuri (2023) using the WRF-SWAN-ROMS coupled model, with sensitivity experiments designed for SST (+0.8 °C, +2.0 °C, +3.5 °C) and SL rise (+0.4 m, +0.6 m, +0.8 m) scenarios referenced to IPCC AR6 projections. Results indicate that SST rise enhances typhoon intensity by approximately 16% at +3.5 °C, elevates mean wave height by 25.0%, and increases extreme significant wave height by 24.0%, with the extreme wave height sensitivity approximately 2.75 times that of the mean. Storm surge exhibits a nonlinear response, with the extreme surge sensitivity approximately 13.2 times that of the mean. SL rise has relatively minor effects on open sea areas but affects coastal regions notably, expanding the inundation area by approximately 47% under the 0.8 m scenario. The Taiwan Strait channeling effect amplifies wave heights and surges on the right side of the track. Comparative analysis suggests that SST indirectly amplifies disasters by enhancing typhoon intensity, while SL rise directly constrains nearshore dynamics through static water level elevation. These findings offer process-based insights into the contrasting physical mechanisms through which SST rise and SL rise affect coastal hazards in semi-enclosed regions and may inform future ensemble-based climate impact assessments. Full article

Surface-deployed wireless sensor networks (WSNs) provide a flexible platform for ocean monitoring, but ocean-current-dominant marine forcing causes persistent topology evolution, backbone distortion, and route breakage. This paper proposes an event-driven self-healing routing and topology-maintenance mechanism for drift-prone surface WSNs. The design combines dual-threshold cluster-head handover, CH-HELP backbone repair, Node-HELP member reattachment, loop-free upstream reselection, and conditional global reclustering as a low-frequency corrective layer for long-term topology degradation. Unlike fixed-round reorganization, the proposed framework prioritizes local repair and triggers global refresh only when backbone quality persistently deteriorates. Simulations driven by Taiwan Strait current-dominant flow–wind data show that the full Proposed-Hybrid method reduces the CH-disconnection rate from 8.15% in DARCR to 5.15%, whereas the local-only configuration without conditional global reclustering yields 9.13%. Conditional global reclustering further suppresses late-stage topology degradation, reducing the final-third mean CH-disconnection rate from 16.32% to 8.51% and the late-stage 95th-percentile peak from 34.43% to 17.21%. DARCR remains competitive in some late-stage metrics because of its fixed-period global reorganization. Full article

The seasonal monsoon reversal drives runoff and current variability along the East Asian coast, intensifying eutrophication from terrestrial nutrients. However, phytoplankton responses to these combined pressures remain poorly understood. This study analyzed their effects using partial least-squares path modeling (PLS-PM) and generalized additive models (GAMs), based on 2021 data from Shantou Bay in the Taiwan Strait, a region with complex currents and significant nutrient inputs. A total of 359 phytoplankton species were identified, with seasonal mean abundances ranging from 6.76 × 10⁶ to 57.36 × 10⁶ cells m⁻³. Ocean currents and riverine runoff drive the seasonal turnover of dominant species by modulating the temperature and salinity. In summer, the exceptionally high phytoplankton abundance in the southwestern Taiwan Strait is driven by nutrient-rich terrestrial inputs, upwelling-induced thermal inhibition, and thermocline stratification from upwelling and offshore warm waters. The phytoplankton abundance and distribution were strongly correlated with the seasonal current and runoff-driven water masses. The PLS-PM results confirm that phytoplankton dynamics are regulated by currents and terrestrial nutrient inputs altering the hydrological and chemical environments, highlighting temperature and salinity as dominant controlling factors in eutrophic coastal zones. Full article

Accurately capturing the Kuroshio’s main axis and its multiscale frontal variations remains challenging due to the constraints of traditional fixed-section extraction methods. Here, we develop an adaptive iterative tracking algorithm utilizing high-resolution reanalysis data (2002–2024) that dynamically adjusts search directions and cross-sections via local velocity vectors, integrated with a dynamic step size and two-dimensional validation. Applying a multiscale variability decomposition framework across four key regions reveals distinct spatiotemporal dynamics. The North Equatorial Current bifurcation zone exhibits a significant strengthening trend driven by seasonal zonal and decadal meridional flows. Conversely, the Kuroshio east of Taiwan is dominated by high-frequency mesoscale processes (~70%) with a semi-annual cycle and no long-term trend. The East China Sea front maintains a highly stable seasonal meridional signal (25%). Crucially, the Luzon Strait intrusion shows a significant long-term weakening trend (~0.0029 m·s⁻¹·a⁻¹, p < 0.01), characterized by eastward strengthening and northward weakening, with ENSO significantly modulating its seasonal cycle. This approach substantially reduces systematic extraction errors compared to traditional fixed-section methods, as independently verified using satellite SST frontal gradients (median deviation < 0.2°), providing critical observational evidence for understanding western boundary current–marginal sea interactions and their dynamical responses under global warming. Full article

The chlorophyll-a (chl-a) concentration is a major indicator of marine ecosystem status, harmful algal blooms, and marine primary productivity. In coastal waters, however, complex hydrodynamic and ecological conditions lead to highly variable chl-a dynamics, driven by diverse and interacting mechanisms, posing substantial challenges for chl-a forecasts. To assess the applicability of machine learning approaches in predicting chl-a under complex coastal environments, we present a case study in the Taiwan Strait, where harmful algal blooms occur a few times every year. Based on satellite remote sensing data, a spatiotemporal imputation and prediction framework (STIMP), temporal models (Transformer, CrossFormer, Tsmixer), and spatiotemporal models (MTGNN and PredRNN) were applied to simulate chl-a spatiotemporal variability. A hydrodynamic–biogeochemical model was compared with these machine learning approaches to assess the model skills in coastal chl-a simulations. Results indicate that machine learning models trained with satellite data exhibit reasonable predictive skill offshore with pronounced seasonal variability and low data missing ratio, while their performance weakens in regions where seasonal signals are masked by short-term chl-a fluctuations with more missing data. In contrast, the hydrodynamic–biogeochemical model represents short-term variations in chl-a in nearshore regions with higher temporal resolution and accounts for the underlying mechanisms of phytoplankton biomass accumulation and die-off. When trained with model output, the machine learning approach shows improved performance in coastal chl-a forecasts, with much higher computational efficiency compared to the hydrodynamic–biogeochemical model. This study highlights the advantage of mechanistic and machine learning models in deciphering the spatiotemporal scales and governing mechanisms of chl-a variability in coastal regions and extracting spatiotemporal variability with computational efficiency, respectively. With input data of sufficient temporal resolution (e.g., daily to 3 days) and duration (5–10 years), a combination of the machine learning and mechanistic modeling approaches is recommended for operational coastal phytoplankton bloom forecasting. Full article

Salt tolerance is a key factor limiting coastal vegetation restoration. In backshore areas, foliage is frequently exposed to salt mist and wave splash, which severely constrains plant survival and restoration outcomes. While root salt tolerance under short-term stress has been widely studied, foliar salt tolerance remains poorly understood. Here, using a self-developed experimental apparatus, we investigated the salt tolerance mechanisms of the coastal shrub Volkameria inermis through a long-term (159-day) foliar salt stress experiment (0–3.0% NaCl), followed by a 64-day recovery period. Field suitability was also evaluated at different coastal locations in Quanzhou Bay, Fujian Province. The results show that: (1) trait plasticity (e.g., leaf thickening), resource redirection (e.g., reduced growth rate, and new bud emergence in unstressed parts), and strong recovery capacity together enhance V. inermis adaptation to long-term foliar salt stress; (2) V. inermis exhibits adaptability to salinity ≤2.0% and survival under 3.0% despite severe injury; (3) besides osmotic adjustment, proline accumulation helps alleviate oxidative damage; and (4) field data demonstrated that leaf thickness and leaf water content were significantly associated with distance from the sea and elevation, thereby validating the salt-adaptation strategies observed under controlled conditions. This study provides a novel methodological framework and practical insights for selecting salt-tolerant species in coastal restoration. Full article

Based on ERA5 reanalysis data, best-track data of tropical cyclones, and satellite nighttime light data from 1995 to 2024, this study employs a statistical composite method to analyse spatiotemporal evolution characteristics and impact mechanisms of gale events in the South China Sea. The results indicate: ① The gale days exhibit a pattern of ‘high in the northeast and southwest, low in the middle’ with three high-value regions located in the Taiwan Strait, the Bashi Strait, and the offshore region southeast of Vietnam, where the average wind speed at the centres reaches 8 m/s. Maximum wind speeds show a ‘high in the north, low in the south’ pattern, with the dividing line near 10° N. The number of gale days peaks in winter, while maximum wind speeds are higher in summer and autumn than in winter and spring. ② The spatial distribution of gales is primarily influenced by the combined effects of land–sea topography and weather systems. Cold air masses in winter and spring are the dominant cause of gales in the South China Sea. Although typhoons in summer and autumn occur less frequently, they are more likely to trigger extreme gales. ③ Most regions of the South China Sea show an increasing trend in the gale days, while a few areas in the south and near Guangdong exhibit a decrease. The overall increase is primarily attributed to the intensification of the subtropical high, whereas the reduction near Guangdong is mainly due to increased surface roughness caused by urbanisation, which enhances friction and suppresses wind speeds. Full article

High-Frequency (HF) radar remote sensing offers a unique capability to detect mesoscale air-sea interactions under strong monsoon conditions. This study leveraged HF radar-derived surface currents, buoy observations, and reanalysis data to systematically investigate the driving mechanism of the sea–land breeze (SLB) on surface currents in the Taiwan Strait during the strong winter monsoon. To address the challenge of extracting weak signals from a dominant background flow, we employed the Separation of the Regional Wind Field (SRWF) method and the complex demodulation spectrum shifting technique. The results demonstrate that HF radar observations confirm the presence of regular SLB activity even under the strong monsoon, with its intensity modulated by the land–sea temperature difference influenced by cloud cover. Spatial correlation analysis reveals that the SLB significantly drives diurnal variations in the surface current, with its impact extending up to 110 km offshore and a maximum amplitude of approximately 2.2 cm/s. Additionally, the analysis reveals that the duration of SLB events critically influences the current response: events lasting 7 days produce a stronger and more spatially coherent correlation with the diurnal currents than shorter 5-day events. Furthermore, harmonic analysis indicates that the SLB’s energy primarily affects the non-tidal residual current, with no significant impact on the principal diurnal tidal constituents ($O_1$, $K_1$). This work not only quantifies the SLB-current coupling during sustained SLB events in a strong monsoon regime but, more importantly, demonstrates the capability of HF radar remote sensing for resolving weak signals in complex, high-energy environments, providing a robust methodological framework and valuable insights for regional marine environmental forecasting. Full article

Coastal regions played a key role in the emergence of Early Neolithic cultures. Fluctuating sea levels shaped prehistoric human migration, settlement patterns, and adaptation strategies. The lower reaches of the Min River in Fujian were a major centre of activity. During the Middle to Late Neolithic, marine communities such as the Keqiutou (6500–5500 cal. a BP) and Tanshishan (5500–4300 cal. a BP) cultures flourished. However, the scarcity of earlier remains has limited understanding of Early Neolithic life before 8000 cal. a BP. We dated stratigraphic layers at the newly excavated Niutoushan site using radiocarbon dating and optically stimulated luminescence (OSL). OSL results indicate the site’s Neolithic culture layer between 9.3 ± 0.7 ka and 8.1 ± 0.5 ka, with radiocarbon dates clustering around 8300–7000 cal. a BP. Based on the younger bounds of the dating results and kernel density estimation, the Neolithic remains at the site are dated to approximately 8000–7000 cal. a BP, identifying Niutoushan as one of the earliest Neolithic sites in the region. Combined with sea-level reconstructions, the findings suggest that the rapid Early Holocene sea-level rise drove human migration along China’s eastern coast before 8000 cal. a BP. The Niutoushan culture was influenced by Neolithic cultures from northern coastal regions and potentially by those located to its south across the exposed Taiwan Strait from the Last Glacial Maximum to the Early Holocene. This points to complex interactions among Early Neolithic cultures in both northern and southern coastal China, warranting further investigation for validation. Full article

Wind energy is an important form of clean energy, and its rational utilization represents a crucial solution for mitigating the energy crisis and global warming. In this study, wind energy potential and its long-term changes in the South China Sea (SCS) are evaluated using ERA5 100 m wind data from 1944 to 2023, validated against ASCAT observations. High wind speeds and high wind power density (WPD) are concentrated southwest of Taiwan and southeast of Vietnam. Annual wind availability exceeds 6457 h across most regions, reaching up to 8283 h in optimal locations. WPD and capacity factor peak in winter (up to 2.4 × 10⁸ Wh·m⁻² and >50% capacity factor), with the most stable conditions occurring in the southwestern Taiwan Strait, southeast of the Pearl River Delta, and the Beibu Gulf. Empirical orthogonal function analysis reveals that the first mode of winter WPD accounts for 65.7% of the total variance, with a statistically significant increasing trend since 1990. The interannual variation in wind energy resources in the SCS during winter is controlled by the combined effects of sea surface temperature (SST) anomalies in the tropical Pacific and the Arctic Barents Sea. Specifically, in the years with strong wind anomalies in the SCS, mega-La Niña-type SST patterns in the tropical Pacific trigger anomalous cyclonic circulation in the SCS and the eastern Philippine Sea, while warm anomalies in the Arctic Barents Sea surface drive a wave-like structure of “anticyclone–cyclone–anticyclone” from Siberia to South China. The coupling of the two systems jointly promotes the strengthening of the South China Sea monsoon, leading to increased wind speeds and elevated WPD in the northern SCS. These findings provide a scientific basis for wind farm siting and long-term operational planning in the region. Full article

The northeast monsoon prevailing over southeastern China in late seasons, generally from October to March, frequently generates water level anomalies upstream of the Taiwan Strait (TWS) that reach the coastal waters of Guangdong in South China, and, with compounding astronomical high tides, elevate coastal flood risk over the region. The risk of coastal flooding or sea inundation is further heightened when monsoon forcing co-occurs with storm surge brought by late-season tropical cyclones (TCs). This study integrates tide gauge observations from Hong Kong (HK) and its vicinity together with Delft3D Flexible Mesh simulations to diagnose a tide-modulated anomaly wave mechanism. Observations show that anomalies originating in or near TWS arrive in HK with station-dependent phasing. These water level anomalies exhibit a characteristic ~6 h periodicity west of the Taiwan Shoal, and display peaks that systematically align with the astronomical high tide. Time–frequency analysis reveals a wave period transformation from ~12 h north of Dongshandao over the coast of southeastern China to ~6 h west of the Taiwan Shoal. We test the hypothesis that wind-forced water anomalies generated in or near TWS undergo shoal-modulated nonlinear tide–wind interaction and tidal-current advection that transform their dominant period and phase-lock them to the tide, producing four anomaly peaks per day downstream and station-dependent phasing in HK. Hindcasts of the November 2024 monsoon episode reproduce the observed timing, periodicity, and spatial transition, while constituent experiments demonstrate that semi-diurnal forcing entering via the TWS is the primary driver of the ~6 h signal, with the Taiwan Shoal acting as the modulation locus. Accurate water level forecasts for the Guangdong coast, therefore, need to incorporate upstream wind forcing over the TWS and bathymetric controls around the Taiwan Shoal, with practical implications for compound flood risk during spring tides and co-occurring monsoon and/or TC events. Full article

Mierspenaeopsis hardwickii (Miers, 1878) represents an important economic resource for coastal artisanal fishers and small-scale fisheries operations. However, very little is known about the distribution patterns related to environmental factors and migration routes of M. hardwickii. In this study, we employed research vessels to obtain CPUE_w (weight in catch per unit effort) and CPUE_n (abundance in catch per unit effort) data in 2018–2019. Our results showed that the largest number was found at 20–40 m in spring and summer, extending in autumn (40–90 m) and shrinking in winter (40–60 m). The scattered distribution pattern of M. hardwickii was observed in spring with sea bottom temperature (SBT) 11–18 °C and sea bottom salinity (SBS) 32–34 and winter (SBT 9–19 °C, SBS 32–35); most individuals were observed in summer (SBT 26–28 °C, SBS 30–31) and autumn (SBT 19–22 °C, SBS 32–35). The annual mean CPUE_w and CPUE_n were 3624 g·h^–1 and 799.4 ind·h^–1, respectively. We hypothesize that in spring, most parent cohorts aggregate in Dasha in the southern Yellow Sea, while many cohorts gather in the coastal waters of the East China Sea, with sharply reduced abundance in the offshore deeper waters. In summer, the parent cohorts produced offspring in Lvsi in the southern Yellow Sea, the Yangtze River estuary, and coastal water areas of the East China Sea. In autumn, juveniles in the coastal waters migrated to the offshore water area. In winter, a few individuals were sparsely distributed in the offshore water areas of the southern Yellow and East China Seas, and part of the recruitment in the Taiwan Strait might migrate northward to Yushan and Wentai fishing grounds for the nursery. The present investigations provide baseline data that will enable fishers and policymakers to better manage and conserve this resource for future use. Full article

The evaluation of offshore wind energy resources is important to the construction of offshore wind power facilities. In this paper, using four models from CMIP6 and the ERA5 reanalysis dataset, a deep learning model termed SwinWind was developed and proposed to evaluate future offshore wind energy resources in Southeastern China for the periods 2020–2050 and 2070–2100. The feature extraction capability of the Swin Transformer was utilized to construct a bias correction and downscaling framework. This approach achieves performance comparable to existing high-cost models while significantly reducing computational costs and complexity. The SwinWind model corrected most of the biases and effectively learned spatial relationships, successfully performing the downscaling task. Based on future wind speed projections derived from the SwinWind model, this study presents a comprehensive evaluation of offshore wind resources, examining five critical dimensions: resource abundance, efficiency, stability, the impact of extreme winds, and economic feasibility. It is projected that offshore wind resources around Shanghai, Jiangsu and Zhejiang will experience a decline in the 21st century, while offshore wind resources around the Guangdong, Fujian and the Beibu Gulf show an increasing trend. The evaluation index shows that the coastal areas of Guangdong and the southern coastline of Taiwan are the most suitable locations for wind power exploitation. The Taiwan Strait, which has the highest wind energy density, is not the best spot due to its extreme wind speed and unstable wind resources. This study provides an important reference for the location of wind farms with practical application value. Full article