Mean Significant Wave Height Research Articles

Relation analysis of ship speed & environmental conditions: Can historic AIS data form a baseline for autonomous determination of safe speed?

AbstractAs no internationally agreed-upon method for determining safe speed values currently exists, collecting vast amounts of information on conventional ship behaviour could be used to train autonomous ship intelligence in determining safe speeds in different conditions. This requires speed data collected from conventional ships to resemble what can be described as safe speeds. To test this, the Automatic Identification System (AIS) and environmental data – namely visibility, mean wind speed and significant wave height – were collected and merged for two study areas in Norway in the period between 27 March 2014 and 1 January 2021. Regression analyses based on 47,490 unique vessel transits were conducted and supplemented by two graphical methods for revealing relationships between variables. Contrary to the contemporary understanding of safe speed, reduced visibility did not lead to significantly reduced transit speeds. Wind and waves caused a reduction in speed in the open ocean, but not in coastal waters. Transit speeds were lower in coastal waters than in the open ocean.

Pemodelan Kekuatan Gelombang di Pesisir Barat Kecamatan Kuta, Bali


 
 
 
 The coastal area is an important area with many different functions for both human and marine organisms. Still, coastal regions are vulnerable to changes caused by various things, including waves. Waves can cause shoreline changes and erode coastal regions. Kuta District is one of the coastal areas on the island of Bali that are threatened with constant sediment erosion every year. One way to increase understanding of the wave and its effect on the coastal areas is through numerical modeling. This study aimed to determine the pattern of wave and wave strength distribution on the west coast of the Kuta district. The Finite Volume Coastal Ocean Model and SWAVE (FVCOM-SWAVE) coupling model that was used in this study utilized the Finite Volume method of computation with the unstructured triangular grid. The results showed that in West Season (December-January-February), the range of mean significant wave heights on the west coast of Kuta District is 0.05 - 0.2 m, and the wave power ranged from 1 to 30 W/m with the most considerable value of significant wave heights and wave power were encountered in January. Water areas near land have greater wave heights and wave power than areas far from land, except around Ngurah Rai International Airport. The movement of waves primarily comes from the southwest, the Bali Strait, to the east and is divided by the runway into following the northern and southern parts of the coast. Thus, the most significant wave height ??and wave power values are found in the waters near Kuta beach and Legian beach.
 
 
 

Validation of Nadir SWH and Its Variance Characteristics from CFOSAT in China’s Offshore Waters

The offshore waters of China are a typical monsoon−affected area where the significant wave height (SWH) is strongly influenced by the different seasonal mean flow in winter and summer. However, limited in situ validations of the SWH have been performed on the China–France Oceanography Satellite (CFOSAT) in these waters. This study focused on validating CFOSAT nadir SWH data with SWH data from in situ buoy observations for China’s offshore waters and the Haiyang−2B (HY−2B) satellite, from July 2019 to December 2021. The validation against the buoy data showed that the relative absolute error has a seasonal cycle, varying in a narrow range near 35%. The RMSE of the CFOSAT nadir SWH was 0.29 m when compared against in situ observations, and CFOSAT was found to be more likely to overestimate the SWH under calm sea conditions. The sea−surface winds play a key role in calm sea conditions. The spatial distributions of the CFOSAT and HY−2B seasonal SWHs were similar, with a two−year mean SWH−field correlation coefficient of 0.98. Moreover, the coherence between the two satellites’ SWH variance increased with SWH magnitude. Our study indicates that, in such typical monsoon−influenced waters, attention should be given to the influence of sea conditions on the accuracy of CFOSAT SWH, particularly in studies that combine data from multiple, long−duration space−based sensors.

Forecasting Impacts on Vulnerable Shorelines: Vulnerability Assessment along the Coastal Zone of Messolonghi Area—Western Greece

The coastal areas of the Mediterranean have been extensively affected by the transgressive event that followed the Last Glacial Maximum, with many studies conducted regarding the stratigraphic configuration of coastal sediments around the Mediterranean. The coastal zone of the Messolonghi area, western Greece, consists of low-relief beaches, containing low cliffs and eroded dunes, a fact that, in combination with the rising sea levels and tectonic subsidence of the area, has led to substantial coastal erosion. Coastal vulnerability assessment is a useful means of identifying areas of coastline that are vulnerable to impacts of climate change and coastal processes, highlighting potential problem areas. Commonly, coastal vulnerability assessment takes the form of an “index” that quantifies the relative vulnerability along a coastline. Here, the Coastal Vulnerability Index (CVI) methodology by Thieler and Hammar-Klose was employed, by considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates, and mean significant wave height as well as mean tide range, to assess the present-day vulnerability of the coastal zone of the Messolonghi area. In light of this, an impact assessment is performed under three different sea-level-rise scenarios. This study contributes toward coastal zone management practices in low-lying coastal areas that have little data information, assisting decision-makers in adopting best adaptation options to overcome the impact of sea-level rise on vulnerable areas, similar to the coastal zone of Messolonghi.

Improvement of a coastal vulnerability index and its application along the Calabria Coastline, Italy

The present paper further develops a coastal vulnerability index formulation (CVI) previously proposed by the authors by integrating a new variable and redefining three variables to improve the suitability of the index for low-lying coasts. Eleven variables are divided into three typological groups: geological, hydro-physical process and vegetation. The geological variables are: geomorphology, shoreline erosion/accretion rates, coastal slope, emerged beach width, and dune. The hydro-physical process group includes: river discharge, sea-level change, mean significant wave height and mean tide range. The vegetation variables are: vegetation behind the back-beach and coverage of Posidonia oceanica. The index was applied to a stretch of the Ionian coast in the province of Crotone in the Calabria region (Southern Italy), and a vulnerability map was produced. A geography information system (GIS) platform was used to better process the data. For the case study area, the most influential variables are shoreline erosion/accretion rates, coastal slope, emerged beach width, dune, vegetation behind the back-beach, and coverage of Posidonia oceanica. The most vulnerable transects are those near urban areas characterized by the absence of dunes and vegetation. Statistical and sensitivity analyses were performed, and the proposed CVI was compared with the previous formulation proposed by the authors and with two other CVI methods present in the literature.

Trend detection by innovative polygon trend analysis for winds and waves

It is known that densely populated coastal areas may be adversely affected as a result of the climate change effects. In this respect, for coastal protection, utilization, and management it is critical to understand the changes in wind speed (WS) and significant wave height (SWH) in coastal areas. Innovative approaches, which are one of the trend analysis methods used as an effective way to examine these changes, have started to be used very frequently in many fields in recent years, although not in coastal and marine engineering. The Innovative Polygon Trend Analysis (IPTA) method provides to observe the one-year behavior of the time series by representing the changes between consecutive months as well as determining the trends in each individual month. It is not also affected by constraints such as data length, distribution type or serial correlation. Therefore, the main objective of this study is to investigate whether using innovative trend methods compared to the traditional methods makes a difference in trends of the climatological variables. For this goal, trends of mean and maximum WS and SWH series for each month at 33 coastal locations in Black Sea coasts were evaluated. Wind and wave parameters WS and SWH were obtained from 42-year long-term wave simulations using Simulating Waves Nearshore (SWAN) model forced by the Climate Forecast System Reanalysis (CFSR). Monthly mean and maximum WS and SWH ​​were calculated at all locations and then trend analyses using both traditional and innovative methods were performed. Low occurrence of trends were detected for mean SWH, maximum SWH, mean WS, and maximum WS according to the Mann-Kendall test in the studied months. The IPTA method detected more trends, such as the decreasing trend of the mean SWH at most locations in May, July and November December. The lowest (highest) values were seen in summer (winter), according to a one-year cycle on the IPTA template for all variables. According to both methods, most of the months showed a decreasing trend for the mean WS at some locations in the inner continental shelf of the southwestern and southeastern Black Sea. The IPTA method can capture most of the trends detected by the Mann-Kendall method, and more missed by the latter method.

GIS based coastal vulnerability assessment and adaptation barriers to coastal regulations in Dakshina Kannada district, India

Coastal areas represent fragile and complex ecosystems. Changes in climate, increasing urbanization and industrialization are creating immense pressure on the coastal environment. Coastal erosion, sea level rise, changing morphology of the coastal areas and extreme weather events are some of the threats that coastal regions are experiencing globally. While various studies have assessed the vulnerability of coastal regions quantitatively and spatially, there is a need to supplement these findings with qualitative insights based on human experiences. Thus, the present study carried out a coastal vulnerability assessment along the coastline of Dakshina Kannada district in Karnataka, India using Shannon’s Entropy by including eight parameters i.e., slope, elevation, geomorphology, bathymetry, sea level rise, mean tidal range, mean significant wave height and shoreline change. The study also explored the experiences and perceptions of stakeholders regarding adaptation barriers to climate change vulnerabilities for understanding the ground complexities. Coastal vulnerability index (CVI) revealed that nearly 39.7 km of the coastline is vulnerable including areas along Sasihtlu beach, Munda, New Mangalore Port Batapady beach, Uchilla, Kotekar, Ullal beach, Netravati River Area and Mukka beach. Rainfall induced coastal erosion, lack of coordination among the various stakeholders, policy makers and practitioners regarding a common framework for climate change adaptation strategies were identified adaptation barriers. The findings of CVI and adaptation barriers may be used by practitioners and policy makers for framing the adaptation measures for mitigating the implications of the coastal region.

Evaluation of the performance of a dynamic wave climate ensemble simulated using with EURO‐CORDEX winds in the Black Sea and Sea of Azov

AbstractThis study evaluates the performance of a dynamic ensemble of wave climate simulations for the Black Sea. The ensemble members (and ensemble means) are evaluated for the historical period (1979–2005). The spectral wave model (simulating waves nearshore [SWAN]) was forced with eight Coupled Model Intercomparison Project Phase 5 (CMIP5) based Regional Climate Models (RCMs) wind fields to obtain each of the eight ensemble members. The RCM‐forcings used belongs to the European branch of the Coordinated Regional Downscaling Experiment (EURO‐CORDEX). The ensemble members' historical wave climate is thoroughly compared against the ERA5 reanalysis, in situ observations, and altimeter measurements. In addition to the individual evaluation of ensemble members, the results for the 8‐member ensemble mean are also examined. The performance of the ensemble members in reproducing the mean and extreme significant wave heights, mean wave periods, and mean wave directions is found to be good, with differences generally between +25 and −15% in comparison to ERA5. Differences between +10% and −30% were found for the comparison with altimeter measurements. We conclude that the ensemble better represents the wave climate of the Black Sea, than its individual members. The 8‐member ensemble provides a more balanced dataset for the Black Sea wave climate and a better representation of the associated uncertainty. Thus, further wave climate projections for the Black Sea should rely on the use of an ensemble.

Projected wave climate of Bass Strait and south-east Australia by the end of the twenty-first century

A high-resolution third-generation wave model based on unstructured grids, WAVEWATCH III (WW3), was used to study the projected future wave climate of Bass Strait and south-east Australia under two different greenhouse gas emission scenarios (SSP1-2.6 and SSP5-8.5). The wave model, forced with winds from the Australian ACCESS-CM2 Global Climate Model, shows good agreement with coastal long-term buoy observations and an independent WW3 hindcast dataset over the historical period 1985–2014. The projected mean significant wave height (H_{s}) for SSP5-8.5 by the end of the twenty-first century (2071–2100) shows a robust increase for the majority of the domain, but a decrease in nearshore regions, mainly due to projected decreases in local wind speed. The increase in H_{s} for SSP1-2.6 is relatively small. Seasonal variations show that H_{s} (SSP5-8.5) is primarily influenced by Southern Ocean swell in spring and winter and local winds prevail in summer and autumn. Hs percentiles show a stronger increase in extreme wave climate for SSP5-8.5 than for SSP1-2.6. Extreme value H_{s} for SSP1-2.6 shows a projected decrease in western regions of the domain and an increase in the east. Extreme value H_{s} for SSP5-8.5 shows a decrease in the nearshore areas of Victoria. This study shows that projected wave climate changes in south-east Australia may have potential implications for Tasmanian and Victorian coastline stability.

Numerical Prediction of Tower Loading of Floating Offshore Wind Turbine Considering Effects of Wind and Wave

For the design of floating offshore wind turbines (FOWT), all the load cases need to be calculated by using a coupled model of wind turbine and platform, while the uncoupled approach will help to reduce the number of simulations for the design and optimization of floating offshore wind turbines. In this study, the effects of the wind and wave actions on the tower loading of a FOWT were investigated and an uncoupled approach for the load calculation was proposed and verified by comparing with the result of coupled simulation. First, the effect of elastic platform was considered by tuning the Young’s modulus of the tower material when rigid platform model was used in the analysis. The effect of wind and wave actions on the loading of the tower was then investigated. It was found that the difference of the wind load between fixed and floating wind turbines is observed only in the mean component and can be predicted by considering the hydrostatic stiffness of the platform and mooring stiffness. The standard deviation of the fore-aft tower moment increased as the significant wave heights increased when the mean wind speeds and peak wave periods were fixed. This is caused by the increase of the inertia force induced by the pitch and surge motions of the platform and the increase of the fluctuating pitch angle. On the other hand, the standard deviation of the fore-aft tower moment decreased as the peak periods increased when the mean wind speeds and significant wave heights were fixed. The increase of the peak period caused the decrease of the pitch and surge accelerations of the platform and results in the decrease of the inertia force. Finally, the tower loading in extreme sea states during power production was carried out by using the proposed uncoupled approach and the results showed good agreement with those by the coupled approach, and the simulation time was reduced to 1/40.

Assessment of the Coastal Vulnerability Index (CVI) for disaster mitigation strategies in some coastal tourism areas in Gunungkidul, Yogyakarta-Indonesia

South coastal area of Gunungkidul, Yogyakarta-Indonesia has a high tourism development due to the unique physical conditions of coastal typology. However, during the last few years, extreme wave height associated with cyclones damaged many tourist facilities there. Coastal management for ecosystem sustainability requires disaster mitigation, which one considering the aspect of vulnerability. This study aims to assess the level of coastal vulnerability according to coastal typology of Baron-Pok Tunggal section and to determine the coastal management model based on the level of vulnerability. The Coastal Vulnerability Index (CVI) is used in vulnerability assessment. The variable formulation of CVI is divided into hydrodynamic factors (mean significant wave heights, mean tide range, and mean sea level rise) and morphodynamics factors, i.e. geomorphology, coastal slope, and average width of emerged beach. The morphodynamics data were obtained through observation, direct measurements in the field by systematic sampling, extraction from aerial photographs and digital surface model (DSM). The results of modeling and predictions by several agencies are derived to obtain the hydrodynamics data. The result of this study revealed that marine deposition coast typology have a high and moderate vulnerability (twelve and eleven coastal units, respectively). Meanwhile, a low vulnerability can be found in the cliff coast or wave erosion coast typology (24 units). The convex or concave beaches tend to be more vulnerable than beaches with the straight form. The beaches of Buluk, Drini, Kosakora, Sarangan and all beaches from Krakal to Indrayanti have a high vulnerability. Geomorphological variables, significant wave height, and sea level rise have the strongest influence on vulnerability. Coastal management in the marine deposition coast typology can be carried out either in a protective manner or by accommodative approach, such as by observing changes in natural conditions due to sea level rise.

Wave storm events in the Western Mediterranean Sea over four decades

The rising intensity and recurrence of wave storm events can seriously impact navigation and coastal and offshore structures in the Western Mediterranean Sea. Therefore, the present study is focused on wave storm events in the Western Mediterranean Sea, over the last four decades. The spatial decadal variations of wave storm events are shown, considering variations in the parameters that characterise wave storms, such as significant wave height (SWH), wave storm duration, and wave storm direction. Additionally, the decadal variation in wave storm intensities is evaluated through the storm power index (SPI) and the total storm wave energy (TSWE). The study is based on a wave hindcast, developed using a calibrated SWAN model. The wave storm events are obtained based on the SWH time series for 24 325 locations, distributed over an unstructured grid, covering the entire Western Mediterranean Sea. The decadal variation in the number of wave storm events, maximum and mean wave storm duration, SPI, and TSWE were observed in large parts of the West Mediterranean Sea during the last four decades. However, variations in mean SWH during these storms are low, and do not show a real implication in the decadal changes in the wave storm intensity (SPI and TSWE). Locations of significant increasing changes in SPI and TSWE show a dependence on changes in the wave storm duration. They may be related to variations in wave storm direction in some areas. Increases in wave storm duration are mainly responsible for increases in wave storm intensities over the last decade.

New wind-wave climate records in the Western Mediterranean Sea

This study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analysed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends. Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilisation to prevent probable catastrophic wave storms and ensure sustainable and economic development.

Coastal Vulnerability Index for Kuwaiti Coast

Kuwait is investing significantly for the development of coastal infrastructures in many of its coastal areas. It is essential to know the vulnerability of the coast of Kuwait for the future sea level rise and other physically influencing parameters. For this purpose, a detailed study is carried out and the Coastal Vulnerability Index (CVI) is established for the Kuwaiti coast including the coasts of Islands. The CVI is assessed based on the data on coastal geomorphology, historical shoreline change rate, landward side of the coastal slope, mean significant wave height, mean tidal range and the particle size of the sediments along the beach. The total Kuwaiti coastline of 499 km is divided into two groups with a total of 162 coastal segments. The group 1 contains 138 segments and covers the mainland, Boubyan and Failaka Island. The group 2 contains 24 locations and covers Umm Al-Maradim, Qaru and Kubbar Islands. Field data collection is carried out for all these segments. From this study it is found that 5% of the Kuwaiti coastal area in group 1 are very low vulnerable; 34% low vulnerable; 31% moderately vulnerable; 18% highly vulnerable and 12% are very highly vulnerable. Similar results are obtained for group 2 coastal segments. The results of this study will be useful while preparing the Integrated Coastal Zone Management plan for Kuwaiti coast and for its sustainable coastal infrastructure development.

Analysis of the Makran Coastline of Iran’s Vulnerability to Global Sea-Level Rise

The SE coast of Iran is of great economic and environmental importance. Global climate change affects this coastline through sea level rise (SLR), compounded by a decrease in sediment budgets in coastal areas. This study developed a Coastal Vulnerability Index (CVI) for the SE coast of Iran using satellite, instrumental and field data. Eight risk variables were defined: coastal slope, regional coastal elevation, mean tidal range, mean significant wave height, rate of relative sea-level change, rate of shoreline change, environmental sensitivity and socio-economic sensitivity. The coast was divided into 27 segments based on geomorphic, environmental and socioeconomic traits. Coastal segments were categorized based on their vulnerability to each risk factor using a CVI. The resulting maps highlighted the vulnerability of each coastal segment to SLR. Approximately 50% of the coast is comprised of mostly rocky shores, which are less vulnerable to SLR. Approximately 33% of the coastal length, including sandy beaches, tidal flats and mangrove forests, were determined to be highly vulnerable to SLR. Approximately 12% of the coastline was determined to be moderately vulnerable. Population centers and infrastructure were ranked as highly-to-moderately vulnerable to SLR. This study highlighted the high vulnerability of low-lying areas, such as lagoons and mangroves, in the western part of the Iranian coast of Makran. Proper coastal management and mitigation plans are essential in the future to protect coastal societies and environments.

Spatiotemporal variations and extreme value analysis of significant wave height in the South China Sea based on 71-year long ERA5 wave reanalysis

A thorough understanding of the long-term trends and extreme characteristics in the significant wave height (SWH) contributes greatly to coastal and offshore engineering activities and mitigation of marine disasters. In this study, the annual spatiotemporal variability of the SWH in the South China Sea (SCS) and the return periods for six locations are evaluated based on ERA5 wave reanalysis in a long time period (1950–2020). Long-term trends are estimated by using a popular non-parametric method, the Theil-Sen estimator, and then mapped to show the spatial variability of mean and extreme SWH. Basin-averaged analysis is also performed to investigate the general tendency of the mean SWH in the SCS, with an increasing rate of 0.11 cm/year. The well-known Mann-Kendall test is used to assess the significance of the trends. Significant positive trends in extreme SWH are mainly distributed in the eastern part of the central SCS around the Luzon Strait and the southwestern part of the SCS. In the extreme value analysis, by comparing 2 classical extreme value distribution models combined with 5 sampling methods, the Generalized Pareto Distribution incorporating the Peak Over Threshold (GPD-POT) method has turned out to be suitable for evaluating the return periods in the SCS based on 71-year SWH dataset. Extreme value analysis for different time lengths shows a correlation between the return level and the time span. Small and medium samples may lead to unstable parameter estimation and increased errors. The 100-year return values obtained by GPD-POT using the 71-year wave reanalysis are more credible at P1-P6 with 8.86, 11.79, 11.35, 10.52, 6.50 and 7.71 m, respectively. Both the estimated return periods and the number of extreme events quantified by the Method of Independent Storms (MIS) indicate that extreme events are closely related to the number of tropical cyclones. Seasonally, most extreme events in the SCS occur from June to December, with the summertime maximum SWH situated above the 15th degree of northern latitude and rapidly shifting to south in the fall.

Global coastal attenuation of wind-waves observed with radar altimetry

Coastal studies of wave climate and evaluations of wave energy resources are mainly regional and based on the use of computationally very expensive models or a network of in-situ data. Considering the significant wave height, satellite radar altimetry provides an established global and relatively long-term source, whose coastal data are nevertheless typically flagged as unreliable within 30 km of the coast. This study exploits the reprocessing of the radar altimetry signals with a dedicated fitting algorithm to retrieve several years of significant wave height records in the coastal zone. We show significant variations in annual cycle amplitudes and mean state in the last 30 km from the coastline compared to offshore, in areas that were up to now not observable with standard radar altimetry. Consequently, a decrease in the average wave energy flux is observed. Globally, we found that the mean significant wave height at 3 km off the coast is on average 22% smaller than offshore, the amplitude of the annual cycle is reduced on average by 14% and the mean energy flux loses 38% of its offshore value.

Bidirectional Modeling of Surface Winds and Significant Wave Heights in the Caribbean Sea

Though the ocean is sparsely populated by buoys that feature co-located instruments to measure surface winds and waves, their data is of vital importance. However, due to either minor instrumentation failure or maintenance, intermittency can be a problem for either variable. This paper attempts to mitigate the loss of valuable data from two opposite but equivalent perspectives: the conventional reconstruction of significant wave height (SWH) from Caribbean Sea buoy-observed surface wind speeds (WSP) and the inverse modeling of WSP from SWH using the long short-term memory (LSTM) network. In either direction, LSTM is strongly able to recreate either variable from its counterpart with the lowest correlation coefficient (r2) measured at 0.95, the highest root mean square error (RMSE) is 0.26 m/s for WSP, and 0.16 m for SWH. The highest mean absolute percentage errors (MAPE) for WSP and SWH are 1.22% and 5%, respectively. Additionally, in the event of complete instrument failure or the absence of a buoy in a specific area, the Simulating WAves Nearshore (SWAN) wave model is first validated and used to simulate mean and extreme SWH before, during, and after the passage of Hurricane Matthew (2016). Synthetic SWH is then fed to LSTM in a joint SWAN—LSTM model, and the corresponding WSP is reconstructed and compared with observations. Although the reconstruction is highly accurate (r2 > 0.9, RMSE < 1.3 m/s, MAPE < 0.8%), there remains great room for improvement in minimizing error and capturing high-frequency events.

COASTAL VULNERABILITY MAPPING OF KALIANDA COAST, SOUTH LAMPUNG, USING COASTAL VULNERABILITY INDEX (CVI) METHOD

The coastal region is a strategic area that has enormous potential. Kalianda is one of the coastal areas in South Lampung which has great potential with the main activities are fisheries and marine tourism, but it is also vulnerable to physical effects. The purpose of this study was to assess the vulnerability of physical parameters and to analyze the level of Coastal Vulnerability Index (CVI) in Kalianda, South Lampung. The results showed that the vulnerability level of the Kalianda Coast based on the rate of shoreline change and geomorphological parameters were at a very high level of vulnerability. Whereas based on the parameters of the mean significant wave height, the average tidal tides and beach slope, the Kalianda Coast was at a low level of vulnerability. Overall, the results of the analysis indicated that CVI value ranged from 3.10 to 9.94, which categorized as low and medium vulnerability levels. Distribution of Kalianda coastal vulnerability level along 3.30 km (11.29%) was at low vulnerability level and along 25.98 km (88.71%) was categorized as medium vulnerability level.

Evaluating the Accuracy of ERA5 Wave Reanalysis in the Water Around China

Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height (SWH) of ERA 5 and that of the buoy varies from −0.35 m to 0.30 m for the three shallow locations; for the three deep locations, the variation ranges from −0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large (about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from −1.31s to 0.4s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water.