Nearshore Sea Research Articles

Spatial pattern and coupling characteristics analysis of maritime traffic and economic development based on shipping big data

The rapid development of maritime transport and the gradual increase in the number of ports, ships and shipping routes can produce direct economic benefits for regional development, and a profound grasp of the actual situation of maritime transport makes it possible to make practical plans for economic development and thus rationally develop and use marine resources. However, there is a lack of research on maritime transport, so this study is based on the AIS, waterways, routes and ports data in the near-shore sea area of Guangdong Province. Using GIS spatial analysis technology and various mathematical models, we refer to the evaluation method of road traffic dominance. It analyses and proposes the evaluation indexes of maritime traffic advantages, such as the density of maritime traffic network and the proximity of ports. Based on the actual situation of the study regions, the indicators were quantitatively evaluated and analyzed. The economic development level of each region was also quantitatively evaluated using principal component analysis, and the study regions were classified based on the coupling-coordination model. The results show that the coastal area of Guangdong Province is divided into four types of zones according to the coupling-coordination type of zoning criteria. Corresponding development suggestions are put forward for different zones, and the research results provide certain practical guidelines for promoting the benign cycle development of maritime traffic and economy, and have important guiding significance and application value for the organization and safety of maritime traffic.

Back to the past: long-term persistence of bull kelp forests in the Strait of Georgia, Salish Sea, Canada

The Salish Sea, a dynamic system of straits, fjords, and channels in southwestern British Columbia, is home to ecologically and culturally important bull kelp (Nereocystis luetkeana) forests. Yet the long-term fluctuations in the area and the persistence of this pivotal coastal marine habitat are unknown. Using very high-resolution satellite imagery to map kelp forests over two decades, we present the spatial changes in kelp forest area within the Salish Sea, before (2002 to 2013) and after (2014 to 2022) the ‘Blob,’ an anomalously warm period in the Northeast Pacific. This analysis was spatially constrained by local environmental conditions. Based on nearshore sea surface temperatures (SSTs) from four decades (1984–2022), we found two periods of distinct increases in SST, one starting in 2000 and another in 2014. Further, the highest SST anomalies occurred on warmer coastlines in the enclosed inlets and the Strait of Georgia, while smaller anomalies were found on colder coastlines near the Strait of Juan de Fuca and the Discovery Passage. The total area of bull kelp forests from 2014 to 2022 has decreased compared to 2002 to 2013, particularly in the northern sector of the Salish Sea. Using the satellite-derived kelp data, we also present an analysis of kelp persistence compared with historical distribution of kelp forests depicted on British Admiralty Nautical Charts from 1858 to 1956. This analysis shows that warm, sheltered areas experienced a considerable decrease in persistence of kelp beds when compared to satellite-derived distribution of modern kelp, confirming a century-scale loss. In particular, the presence of kelp forests in the Strait of Georgia and on the warmest coasts has decreased considerably over the century, likely due to warming temperatures. While the coldest coasts to the south have maintained their centennial persistence, the northern Salish Sea requires further research to understand its current dynamics. This research contributes to a wider understanding of temporal and spatial factors for kelp from the regional perspective of the Salish Sea.

Sea Fog Recognition near Coastline Using Millimeter-Wave Radar Based on Machine Learning

Sea fog is a hazardous natural phenomenon that reduces visibility, posing a threat to ports and nearshore navigation, making the identification of nearshore sea fog crucial. Millimeter-wave radar has significant advantages over satellites in capturing sudden and localized sea fog weather. The use of millimeter-wave radar for sea fog identification is still in the exploratory stage in operational fields. Therefore, this paper proposes a nearshore sea fog identification algorithm that combines millimeter-wave radar with multiple machine learning methods. Firstly, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is used to partition radar echoes, followed by the K-means clustering algorithm (KMEANS) to divide the partitions into recognition units. Then, Sea-Fog-Recognition-Convolutional Neural Network (SFRCNN) is used to classify whether the recognition units are sea fog areas, and finally, the partition coverage algorithm is employed to improve identification accuracy. The experiments conducted using millimeter-wave radar observation data from the Pingtan Meteorological Observation Base in Fujian, China, achieved an identification accuracy of 96.94%. The results indicate that the proposed algorithm performs well and expands the application prospects of such equipment in meteorological operations.

Arctic Continental-Shelf Sediment Dynamics.

Sediments covering Arctic continental shelves are uniquely impacted by ice processes. Delivery of sediments is generally limited to the summer, when rivers are ice free, permafrost bluffs are thawing, and sea ice is undergoing its seasonal retreat. Once delivered to the coastal zone, sediments follow complex pathways to their final depocenters-for example, fluvial sediments may experience enhanced seaward advection in the spring due to routing under nearshore sea ice; during the open-water season, boundary-layer transport may be altered by strong stratification in the ocean due to ice melt; during the fall storm season, sediments may be entrained into sea ice through the production of anchor ice and frazil; and in the winter, large ice keels more than 20 m tall plow the seafloor (sometimes to seabed depths of 1-2 m), creating a type of physical mixing that dwarfs the decimeter-scale mixing from bioturbation observed in lower-latitude shelf systems. This review summarizes the work done on subtidal sediment dynamics over the last 50 years in Arctic shelf systems backed by soft-sediment coastlines and suggests directions for future sediment studies in a changing Arctic. Reduced sea ice, increased wave energy, and increased sediment supply from bluffs (and possibly rivers) will likely alter marine sediment dynamics in the Arctic now and into the future.

GWSM4C-NS: improving the performance of GWSM4C in nearshore sea areas

GWSM4C-NS: improving the performance of GWSM4C in nearshore sea areas

Coastal resilience and shoreline dynamics: assessing the impact of a hybrid beach restoration strategy in Puducherry, India

Puducherry, a Union Territory of India, has been strongly affected by severe erosion after the construction of the Puducherry port in 1989. To mitigate this cause, the National Institute of Ocean Technology, Chennai, and the Puducherry government implemented a beach restoration strategy involving a hybrid solution in 2017 for coastal protection/stabilization and the restoration of the lost beach. The strategy involved deploying a steel reef into the nearshore sea and implementing beach nourishment processes. To monitor the coastal morphological changes after implementing the coastal protection strategy, the Digital Shoreline Analysis System, was adopted to calculate the rate of shoreline change statistics for the years 2016 to 2022. It uses spatio-temporal shoreline positions from multi-temporal satellite imagery. The shorelines are extracted from the Sentinel-2A satellite images by a Normalized Differential Water Index based semi-automated model. Statistical parameters in DSAS analyze the shorelines to determine the shoreline changes in this area. The results reveal the remarkable resilience of a newly restored beach, where the linear regression rate statistics in Zone A show an average accretional rate of 2.92m/yr. Alternatively, Zone B exhibits an average erosion rate of -0.23m/yr, with intermittent sandy beaches experiencing maximum erosion rates of -1.63m/yr. The influence of longshore current direction and sediment transport on shoreline movement is evident in seasonal analysis, with shoreline development and recession primarily observed near shore protection structures. The study’s outcome provides valuable insights for coastal management, offering a reliable approach for shoreline monitoring post-implementation of mitigation projects.

Quantifying spatiotemporal variations in tidal flats and coastal land use in Jiangsu Radial Sandbars through remote sensing

The Jiangsu Radial Sandbars in China have experienced significant changes due to extensive human activities in past decades. This study provides new insights by coupling multitemporal remote sensing analysis with landscape pattern assessment to comprehensively evaluate tidal flat evolution and land use suitability from 1984 to 2020. The integrated remote sensing approach enabled continuous high-resolution mapping of tidal flats, revealing a 25.9% area loss equaling 123.2 km2, driven mostly by land reclamation, while also quantifying coastline accretion patterns through shoreline position analysis. The coastal landscape analysis systematically assessed land use changes and human impacts through metrics such as diversity and fragmentation, which revealed intensified seaward expansion and increased fragmentation of unused land and underdeveloped nearshore sea areas. The suitability evaluation considered land resources, ecological factors and socioeconomics to assess four key land use types. The method of coupling with landscape analysis provided integrated insights, including 1) identifying ecologically sensitive zones for prioritized conservation based on landscape patterns; 2) quantifying the intensity and spatial pattern of human activities and their impacts; and 3) comprehensively evaluating land use suitability by integrating landscape analysis with other factors. Future research should explore management strategies, assess the impact of climate change, and make predictions to inform policy-making.

Validating Landsat Analysis Ready Data for Nearshore Sea Surface Temperature Monitoring in the Northeast Pacific

In the face of global ocean warming, monitoring essential climate variables from space is necessary for understanding regional trends in ocean dynamics and their subsequent impacts on ecosystem health. Analysis Ready Data (ARD), being preprocessed satellite-derived products such as Sea Surface Temperature (SST), allow for easy synoptic analysis of temperature conditions given the consideration of regional biases within a dynamic range. This is especially true for SST retrieval in thermally complex coastal zones. In this study, we assessed the accuracy of 30 m resolution Landsat ARD Surface Temperature products to measure nearshore SST, derived from Landsat 8 TIRS, Landsat 7 ETM+, and Landsat 5 TM thermal bands over a 37-year period (1984–2021). We used in situ lighthouse and buoy matchup data provided by Fisheries and Oceans Canada (DFO). Excellent agreement (R2 of 0.94) was found between Landsat and spring/summer in situ SST at the farshore buoy site (>10 km from the coast), with a Landsat mean bias (root mean square error) of 0.12 °C (0.95 °C) and a general pattern of SST underestimation by Landsat 5 of −0.28 °C (0.96 °C) and overestimation by Landsat 8 of 0.65 °C (0.98 °C). Spring/summer nearshore matchups revealed the best Landsat mean bias (root mean square error) of −0.57 °C (1.75 °C) at 90–180 m from the coast for ocean temperatures between 5 °C and 25 °C. Overall, the nearshore image sampling distance recommended in this manuscript seeks to capture true SST as close as possible to the coastal margin—and the critical habitats of interest—while minimizing the impacts of pixel mixing and adjacent land emissivity on satellite-derived SST.

Interpolation of China’s Nearshore Sea Surface Temperature Based on Information Diffusion with Small Sample Sizes

Addressing the issue of data sparsity and gaps caused by missing values, this study employs an information diffusion approach to effectively spread information from sparse sample points to monitoring locations. By thoroughly extracting insights from a limited dataset, it achieves more precise interpolation outcomes. To validate the superiority of the information diffusion interpolation technique under conditions of sparse samples, we utilize sea surface temperature (SST) data from the offshore waters of China as a case study. We compare three interpolation methods: Kriging, Gaussian information diffusion, and asymmetric information diffusion. The calculations and comparisons of interpolation results are conducted across varying sample sizes. The findings indicate that in situations with relatively sparse samples, asymmetric information diffusion yields the most favorable results, with Kriging and Gaussian diffusion exhibiting comparable performance. In cases of extremely sparse samples, asymmetric information diffusion yields the lowest interpolation error, followed by Gaussian diffusion, while Kriging performs the least effectively. Thus, when confronted with sample sparsity, the application of the information diffusion interpolation method can yield notably improved results.

Advancing Sea Turtle Monitoring at Nesting and Near Shore Habitats with UAVs, Data Loggers, and State of the Art Technologies

In the face of environmental change, high-quality and fine-scale information is essential in order to monitor the highly dynamic environments on land and sea. While traditional approaches to data collection face a number of practical limitations, advanced technologies could supplement and further improve our efforts. Taking sea turtles as a modeling organism, we present a novel methodological framework for monitoring species by means of advanced technologies, including Unmanned Aerial Vehicles coupled with image and temperature sensors. Diverse monitoring protocols were refined through pilot studies conducted in both terrestrial and nearshore sea turtle habitats. Our approach focuses on the collection of information for critical biological parameters concerning species reproduction and habitat use, following the complex life cycle of the species. Apart from biological information, our framework encompasses also the collection of information on crucial environmental factors that might be changing due to current and future human-derived pressures, such as beach erosion and temperature profile, as well as highly important human activities such as recreational use within nesting beaches that could undermine habitat quality for the species. This holistic and standardized approach to monitoring using advanced technologies could foster our capacity for conservation, resolving difficulties previously addressed and improving the collection of biological and environmental data in the frame of an adaptive management scheme.

Ingestion and accumulation of microplastics in small marine fish and potential human exposure: case study of Binh Dinh, Vietnam

The present study investigates microplastic (MP) accumulation in five small marine fish species living in the nearshore sea of Binh Dinh, Vietnam that are commonly consumed by the local coastal communities. Fish (Oxyurichthys ophthalmonema, Stolephorus commersonnii, Decapterus macrosoma, Upeneus moluccensis, Sardinella gibbosa) were collected from four sites in the nearshore sea of Binh Dinh in rainy and dry seasons. The temporal, spatial, and species variations in MP accumulation were evaluated to understand environmental exposure of MPs to fish and potential human exposure to MPs via fish consumption. Microplastics of different types, sizes, and colors were found in the digestive system of the fish species. Microplastic composition included polyethylene, polyvinyl ether, polymethacrylate, polydichloroethylene, polydivinyl ester, poly ester, polyfluoroethylene, and other additives of plastic materials. Microplastic abundance in the fish was dependent on species, site, and season. Overall, microfiber was the dominant MPs. The average total MP abundance range was 4.70–23.80 particles/fish or 0.29–6.21 particles/g fish. There were statistically significant differences in MP abundances between fish species, sites, and seasons. The presence of MPs in the digestive system of fish suggests that MPs are in the nearshore environment of Binh Dinh. The local communities along the coast of Binh Dinh can ingest MPs from consuming small fish at a weekly rate equivalent to one five-hundredth number of rice grains they consume/week.

Suspended sediment change along the Zhejiang-Fujian coast revealed using MODIS 250-m imagery

Suspended sediment concentration (SSC) is one of the important parameters in the ecological environment evaluation of marine water bodies, as it provides an important basis for research on the ecological environment of nearshore sea areas, shoreline beach erosion and deposition, water quality of coastal zones and nearshore sedimentation zones. In recent years, the amount of sediment carried by the Yangtze has declined dramatically due to the Three-Gorges Dam (TGD), which might change the sediment supply to the sea and thus affect sediment transport to the coasts of Zhejiang and Fujian. This study aims to both develop specific algorithms and reveal the interannual and seasonal dynamics of the suspended sediment belt from the Yangtze Estuary to the Zhejiang-Fujian provincial shoal using MODIS 250 m data from 2000 to 2020. MODIS time-series analysis shows that the suspended sediments were originally from the Yangtze Estuary and formed a suspended sediment belt in the winter season. Moreover, driven by monsoon winds and coastal current dynamics, the sediment belt has obvious seasonality. Furthermore, we also suggest that the coastal sediment area has a tendency to shrink in winter, and the lifetime of the sediment belt also shortens, showing early disconnection in spring and delayed recovery in autumn, in response to the decline in sediment discharge from the Yangtze River basin to the sea. Impressively, the impact of the TGD in 2003 led to a drop in the sediment concentration in the coastal area. In addition, further analysis confirms that a sudden decrease in suspended sediment concentration was observed at Zhoushan (S2), Wenling (S4), Minjiang River Mouth (S7), Pingtan Island (S8), and many other stations along the coast in 2003, and the closer to the Yangtze Estuary, the more serious this phenomenon becomes, on the basis of monthly SSC analysis. These findings can assist us in better understanding the new pattern of the sediment belt from the Yangtze Estuary to the Zhejiang-Fujian coastal area. The findings of this study have theoretical and practical implications for the study of the hydrological sediment field in offshore areas, the protection of the marine ecological environment, changes in the shoreline and mudflats, and the maintenance of waterways and ports in estuaries.

Biodiversity assessment in the near-shore waters of Tianjin city, China based on the Pressure-State-Response (PSR) method.

Parameters regarding water quality, biology, marine disasters, and anthropogenic factors were collected and analyzed from 2020 to 2021 to evaluate the marine biodiversity of Tianjin's near-shore sea area accurately. A total of 29 indicators obtained from the surveys were selected to form the biodiversity evaluation system. The Pressure-State-Response (PSR) framework model combined with the ecological environment characteristics was used as the assessment method. The analytic hierarchy process (AHP) determined the weights of each indicator. The results showed that the main influencing factors of the water environment for species diversity monitoring were dissolved inorganic nitrogen (DIN) and chemical oxygen demand (COD), and all water quality monitoring items were relatively stable without obvious pollution. The biomass of biological species in the near-shore sea area of Tianjin was relatively low, the species distribution was uneven, and the structure and function of the ecosystem need to be improved since environmental problems still existed.

Variation in Trace Element Concentrations with Size in Sea Urchin Skeletal Components

Environmental ecotoxicology studies use sea urchin skeletal components to examine potential changes in concentrations of trace element pollutants. To date, such studies have not considered how body size may alter the innate concentrations of trace elements in a given skeletal component. The present study examines this issue using the common nearshore sea urchin Lytechinus variegatus as a model species. Concentrations of barium, boron, manganese, and strontium was measured using ICP-OES in three major skeletal subcomponents (Aristotle's lantern, spines, and test) of individuals' representative of five size cohorts spanning the late juvenile to adult. Concentrations of three of the four elements, barium, boron, and manganese, varied significantly with body size, largely declining as test diameter increased. As concentrations of trace elements was normalized to skeletal mass originated from collections of individuals in pristine bay waters and from the same population at the same time, differences in trace element concentrations are innately ontogenetic. Accordingly, future ecotoxicological studies employing skeletal subcomponents of sea urchins should consider the relationship between trace element concentration and body size when designing sampling regimes.

Environment‐triggered demographic changes cascade and compound to propel a dramatic decline of an Antarctic seabird metapopulation

While seabirds are well-known for making a living under some of the harshest conditions on the planet, their capacity to buffer against unfavourable conditions can be stretched in response to ecosystem change. During population increases, overlap between conspecifics can limit population growth through competition for breeding or feeding resources. What is less well understood is the role that intrinsic processes play during periods of population decline or under a changing environment. We interrogate key demographic parameters and their biophysical drivers to understand the role of intrinsic and extrinsic drivers during a recent near halving of a large Adélie penguin (Pygoscelis adeliae) metapopulation. The loss of 154,000 breeding birds along the 100-km East Antarctic coastline centred around 63°E over the last decade diverges from a sustained increase over preceding decades and is contrary to recent models that predict a continued increase. The decline was initially triggered by changed environmental conditions: more extensive near-shore sea ice caused a reduction in breeding success. The evidence suggests this decline was exacerbated by feedback processes driving an inverse density-dependent decrease in fledgling survival in response to smaller cohort size. It appears that the old adage of safety in numbers may shape the fledgling penguins' chances of survival and, if compromised over multiple years, could exacerbate difficulties during population decline or if feedback processes arise. The likely interplay between demographic parameters meant that conditions were more unfavourable and negative effects more rapid than would be expected if demographic processes acted in isolation or independently. Failure to capture both intrinsic and extrinsic drivers in predictive population models may mean that the real impacts of climate change on species' populations are more severe than projections would lead us to believe. These results improve our understanding of population regulation during periods of rapid decline for long-lived marine species.

Hurricane Ida (2021): Rapid Intensification Followed by Slow Inland Decay

Abstract Hurricane Ida recently became one of the strongest hurricanes to hit Louisiana on record, with an estimated landfalling maximum sustained wind of 130 kt (1 kt ≈ 0.51 m s−1). Although Hurricane Ida made landfall at a similar time of year and landfall location as Hurricane Katrina (2005), Ida’s postlandfall decay rate was much weaker than Hurricane Katrina. This manuscript includes a comparative analysis of pre- and postlandfall synoptic conditions for Hurricane Ida and other historical major landfalling hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale) along the Gulf Coast since 1983, with a particular focus on Hurricane Katrina. Abundant precipitation in southeastern Louisiana prior to Ida’s landfall increased soil moisture. This increased soil moisture along with extremely weak overland steering flow likely slowed the storm’s weakening rate postlandfall. Offshore environmental factors also played an important role, particularly anomalously high nearshore sea surface temperatures and weak vertical wind shear that fueled the rapid intensification of Ida just before landfall. Strong nearshore vertical wind shear weakened Hurricane Katrina before landfall, and moderate northward steering flow caused Katrina to move inland relatively quickly, aiding in its relatively fast weakening rate following landfall. The results of this study improve our understanding of critical factors influencing the evolution of the nearshore intensity of major landfalling hurricanes in the Gulf of Mexico. This study can help facilitate forecasting and preparation for inland hazards resulting from landfalling hurricanes with nearshore intensification and weak postlandfall decay.

High-resolution bathymetry models for the Lena Delta and Kolyma Gulf coastal zones

Abstract. Arctic river deltas and deltaic near-shore zones represent important land–ocean transition zones influencing sediment dynamics and nutrient fluxes from permafrost-affected terrestrial ecosystems into the coastal Arctic Ocean. To accurately model fluvial carbon and freshwater export from rapidly changing river catchments as well as assess impacts of future change on the Arctic shelf and coastal ecosystems, we need to understand the sea floor characteristics and topographic variety of the coastal zones. To date, digital bathymetrical data from the poorly accessible, shallow, and large areas of the eastern Siberian Arctic shelves are sparse. We have digitized bathymetrical information for nearly 75 000 locations from large-scale (1:25 000–1:500 000) current and historical nautical maps of the Lena Delta and the Kolyma Gulf region in northeastern Siberia. We present the first detailed and seamless digital models of coastal zone bathymetry for both delta and gulf regions in 50 and 200 m spatial resolution. We validated the resulting bathymetry layers using a combination of our own water depth measurements and a collection of available depth measurements, which showed a strong correlation (r>0.9). Our bathymetrical models will serve as an input for a high-resolution coupled hydrodynamic–ecosystem model to better quantify fluvial and coastal carbon fluxes to the Arctic Ocean, but they may be useful for a range of other studies related to Arctic delta and near-shore dynamics such as modeling of submarine permafrost, near-shore sea ice, or shelf sediment transport. The new digital high-resolution bathymetry products are available on the PANGAEA data set repository for the Lena Delta (https://doi.org/10.1594/PANGAEA.934045; Fuchs et al., 2021a) and Kolyma Gulf region (https://doi.org/10.1594/PANGAEA.934049; Fuchs et al., 2021b), respectively. Likewise, the depth validation data are available on PANGAEA as well (https://doi.org/10.1594/PANGAEA.933187; Fuchs et al., 2021c).

Antarctic ice-shelf advance driven by anomalous atmospheric and sea-ice circulation

The disintegration of the eastern Antarctic Peninsula’s Larsen A and B ice shelves has been attributed to atmosphere and ocean warming, and increased mass losses from the glaciers once restrained by these ice shelves have increased Antarctica’s total contribution to sea-level rise. Abrupt recessions in ice-shelf frontal position presaged the break-up of Larsen A and B, yet, in the ~20 years since these events, documented knowledge of frontal change along the entire ~1,400-km-long eastern Antarctic Peninsula is limited. Here, we show that 85% of the seaward ice-shelf perimeter fringing this coastline underwent uninterrupted advance between the early 2000s and 2019, in contrast to the two previous decades. We attribute this advance to enhanced ocean-wave dampening, ice-shelf buttressing and the absence of sea-surface slope-induced gravitational ice-shelf flow. These phenomena were, in turn, enabled by increased near-shore sea ice driven by a Weddell Sea-wide intensification of cyclonic surface winds around 2002. Collectively, our observations demonstrate that sea-ice change can either safeguard from, or set in motion, the final rifting and calving of even large Antarctic ice shelves. Most of the eastern Antarctic Peninsula’s coastline has undergone uninterrupted advance since the early 2000s due to enhanced near-shore sea ice, according to satellite observations and reanalysis data.

Modelling present and future climate in the Mediterranean Sea: a focus on sea-level change

We present results of three simulations of the Mediterranean Sea climate: a hindcast, a historical run, and a RCP8.5 scenario simulation reaching the year 2100. The simulations are performed with MED16, a new, tide-including implementation of the MITgcm model, which covers the Mediterranean—Black Sea system with a resolution of 1/16°, further increased at the Gibraltar and Turkish Straits. Validation of the hindcast simulation against observations and numerical reanalyses has given excellent results, proving that the model is also capable of reproducing near-shore sea level variations. Moreover, the spatial structure of the elevation field compares well with altimetric observations, especially in the Western basin, due to the use of improved sea level information at the Atlantic lateral boundary and to the adequate treatment of the complex, hydraulically driven dynamics across the Gibraltar Strait. Under the RCP8.5 future scenario, the temperature is projected to generally increase while the surface salinity decreases in the portion of the Mediterranean affected by the penetration of the Atlantic stream, and increases elsewhere. The warming of sea waters results in the partial inhibition of deep-water formation. The scenario simulation allows for a detailed characterization of the regional patterns of future sea level, arising from ocean dynamics, and indicates a relative sinking of the Mediterranean with respect to the Atlantic more pronounced than the current one.

GMDH-based wave prediction model for one-week nearshore waves using one-week forecasted global wave data

Wave forecasting up to 168 h (one-week) ahead is crucial to the operational management of shipping and construction in the marine work site. The present study proposes a method of areal-time One-week Wave Forecast of Nearshore Waves (OWFNW) at 13 stations on the Japanese coast. For each station, two Group Method of Data Handling (GMDH) based wave prediction models for the wave height and period are developed to transform the global wave data into nearshore waves. For each GMDH-based wave prediction model, four models are trained with four different training data sets using the one-week global wave forecast data released in real-time by the Japan Meteorological Agency (JMA), National Oceanic and Atmospheric Administration (NOAA), and European center for Medium-Range Weather Forecasts (ECMWF). The study conducts a series of training and testing GMDH-based wave prediction models at each station, and examines the accuracy of predictions. The best performing GMDH-based wave prediction model selected among the four models is compared to the best global wave forecast data. It was found that the best performance GMDH-based wave prediction model varies for different locations. On average, the best performing GMDH-based wave height model is able to improve the accuracy of nearshore wave predictions up to 38% compared to that of the best global wave height forecast with 168 h lead time. The best GMDH-based wave period model improves the prediction error up to 65% compared to the 168 h ahead error of the best global wave period forecasts. The present methodology to get OWFNW can be applied to other nearshore seas where global wave forecast data and corresponding observed one are available.