WAVE CLIMATE OF THE BLACK SEA’S COASTAL WATERS DURING THE LAST THREE DECADES

2017 ◽  
Author(s):  
Fedor Gippius ◽  
Fedor Gippius ◽  
Stanislav Myslenkov ◽  
Stanislav Myslenkov ◽  
Elena Stoliarova ◽  
...  
Keyword(s):  
Wind Speed ◽  
Cell Size ◽  
Coastal Waters ◽  
Wind Wave ◽  
Spatial Scales ◽  
Wave Model ◽  
Wave Climate ◽  
Computational Grid ◽  
Coastal Areas ◽  
Wave Parameters

This study is focused on the alterations and typical features of the wind wave climate of the Black Sea’s coastal waters since 1979 till nowadays. Wind wave parameters were calculated by means of the 3rd-generation numerical spectral wind wave model SWAN, which is widely used on various spatial scales – both coastal waters and open seas. Data on wind speed and direction from the NCEP CFSR reanalysis were used as forcing. The computations were performed on an unstructured computational grid with cell size depending on the distance from the shoreline. Modeling results were applied to evaluate the main characteristics of the wind wave in various coastal areas of the sea.

WAVE CLIMATE OF THE BLACK SEA’S COASTAL WATERS DURING THE LAST THREE DECADES

2017 ◽  
Author(s):  
Fedor Gippius ◽  
Fedor Gippius ◽  
Stanislav Myslenkov ◽  
Stanislav Myslenkov ◽  
Elena Stoliarova ◽  
...  
Keyword(s):  
Wind Speed ◽  
Cell Size ◽  
Coastal Waters ◽  
Wind Wave ◽  
Spatial Scales ◽  
Wave Model ◽  
Wave Climate ◽  
Computational Grid ◽  
Coastal Areas ◽  
Wave Parameters

This study is focused on the alterations and typical features of the wind wave climate of the Black Sea’s coastal waters since 1979 till nowadays. Wind wave parameters were calculated by means of the 3rd-generation numerical spectral wind wave model SWAN, which is widely used on various spatial scales – both coastal waters and open seas. Data on wind speed and direction from the NCEP CFSR reanalysis were used as forcing. The computations were performed on an unstructured computational grid with cell size depending on the distance from the shoreline. Modeling results were applied to evaluate the main characteristics of the wind wave in various coastal areas of the sea.

Projected changes in wind wave directional spectra and their impact on coastal processes

2021 ◽  
Author(s):  
Hector Lobeto ◽  
Melisa Menendez ◽  
Iñigo J. Losada ◽  
Ottavio Mazzaretto
Keyword(s):  
Wave Energy ◽  
Wind Wave ◽  
Wave Climate ◽  
Wave Period ◽  
Standard Approach ◽  
Coastal Processes ◽  
Full Spectrum ◽  
Wave Parameters ◽  
Future Behavior ◽  
Projected Changes

<p>The assessment of the projected changes in wave climate due to climate change has been subject of study during the last two decades (Morim et al., 2018), largely due to the severe impacts these changes may have on coastal processes such as flooding and erosion. The wind wave climate is fully described by the sea surface elevation spectrum, which represents the distribution of energy resulting from the contributions of several superimposed waves with different periods and directions. Nevertheless, to this day the standard approach to address the future behavior of wind waves is based on the use of integrated wave parameters (e.g. significant wave height, mean wave period, mean wave direction) as a representation of the full spectrum. In this study, we analyze the changes in wave energy from directional spectra discretized in 24 directions and 32 frequencies in a number of locations distributed across all ocean basins, shedding light on the added value that an assessment based on the full spectrum offers with respect to the standard approach. In addition, the ESTELA method (Pérez et al., 2014) is applied to ease the understanding of the changes obtained in wave energy at the locations of study.</p><p>The spectral approach helps to assess the projected change in the energy of each wave system that reach a specific location. Results demonstrate that the use of integrated wave parameters can mask important information about the sign, magnitude and uncertainty of the actual projected changes in mean wave climate due to the offset of the expected variations in the different wave systems that integrate the spectrum. It is especially relevant at locations where an increase in the wave period or wave energy is hidden by the application of the standard approach, as these parameters are proven to play a key role in coastal processes. In addition, we reach relevant conclusions about the future behavior of swell systems. For instance, a robust increase in the energy carried by swells generated below 40°S can be observed in every ocean basin and both hemispheres, even beyond 30°N. Similarly, a decrease in the energy carried by northern swells can be observed close to the equator.</p>

A global approach to hierarchical classification of coastal waters at different spatial scales: the NEA case

2016 ◽  
Vol 97 (3) ◽  
pp. 465-476 ◽  
Author(s):  
José A. Juanes ◽  
Araceli Puente ◽  
Elvira Ramos
Keyword(s):  
Coastal Waters ◽  
Spatial Scales ◽  
Atlantic Coast ◽  
Coastal Areas ◽  
Biological Information ◽  
Management Tool ◽  
Global Approach ◽  
Ne Atlantic ◽  
Wide Range

Ecological classification of coastal waters has become increasingly important as one of the basic issues in the biology of conservation. Management and protection of coastal areas take place at different spatial scales. Thus, proper classification schemes should integrate equivalent information at various levels of definition in order to show its feasibility as a useful tool for assessment of coastal environments at the required scales. In this work, a global approach applied to the classification of the NE Atlantic coast is analysed in order to discuss pros and cons regarding different conceptual and technical issues for effective implementation of such a management tool. Using the hierarchical system applied at three different geographic scales: Biogeographic (NE Atlantic coast), Regional (Bay of Biscay) and Local (Cantabria region), five different topics were considered for debating strengths and weaknesses of the methodological alternatives at those spatial scales, using for validation the rocky shore macroalgae as a representative biological element of benthic communities. These included: (i) the spatial scales; (ii) the physical variables and indicators; (iii) the classification methodologies; (iv) the biological information; and (v) the validation procedure. Based on that analysis, the hierarchical support system summarized in this paper provides a management framework for classification of coastal systems at the most appropriate resolution, applicable to a wide range of coastal areas. Further applications of the physical classification for management of biodiversity in different environmental scenarios are also analysed.

Projected Changes in the Occurrence of Extreme and Rogue Waves in Future Climate in the North Atlantic

2017 ◽  
Author(s):  
Odin Gramstad ◽  
Elzbieta Bitner-Gregersen ◽  
Erik Vanem
Keyword(s):  
North Atlantic ◽  
Wave Spectrum ◽  
Wave Model ◽  
Rogue Waves ◽  
Wave Climate ◽  
Future Climate ◽  
The North ◽  
Wave Parameters ◽  
The Future ◽  
The North Atlantic

We investigate the future wave climate in the North Atlantic with respect to extreme events as well as on wave parameters that have previously not been considered in much details in the perspective of wave climate change, such as those associated with occurrence of rogue waves. A number of future wave projections is obtained by running the third generation wave model WAM with wind input derived from several global circulation models. In each case the wave model has been run for the 30-year historical period 1971–2000 and the future period 2071–2100 assuming the two different future climate scenarios RCP 4.5 and RCP 8.5. The wave model runs have been carried out by the Norwegian Meteorological Institute in Bergen, and the climate model result are taken from The Coupled Model Intercomparison Project phase 5 - CMIP5. In addition to the standard wave parameters such as significant wave height and peak period the wave model runs provided the full two-dimensional wave spectrum. This has enabled the study of a larger set of wave parameters. The focus of the present study is the projected future changes in occurrence of extreme sea states and extreme and rogue waves. The investigations are limited to parameters related to this in a few selected locations in the North Atlantic. Our results show that there are large uncertainties in many of the parameters considered in this study, and in many cases the different climate models and different model scenarios provide contradicting results with respect to the predicted change from past to future climate. There are, however, some situations for which a clearer tendency is observed.

Numerical Study of Wave Climate in Jiangsu Sea Area

2014 ◽  
Vol 501-504 ◽  
pp. 2099-2106
Author(s):  
Liang Ding ◽  
Fei Fan ◽  
Jia Rui Li
Keyword(s):  
Wave Height ◽  
Flow Model ◽  
Numerical Study ◽  
Wave Model ◽  
Wave Climate ◽  
Wave Condition ◽  
Wave Parameters ◽  
Average Wave ◽  
Buoy Data ◽  
Sea Area

This paper studied the wave condition of Jiangsu Sea area with wave model SWAN, which was driven by the wind field from 1990.01.01 to 2011.12.30. Firstly, tidal current of Jiangsu sea area was simulated by the Delft3D flow model. Then, wave parameters of East China Sea and Jiangsu sea area were computed, and then buoy data was used to compared with the modeled, they validated well. Last, the average wave height and period are calculated, and the distribution of wave height on each direction was studied. The result shows that the largest annually average wave height of Jiangsu is up to 1.6m. The average wave height is decreasing from southeast to northwest. The wave height in winter is larger than other seasons. In this sea area, waves mainly come from NE and SE directions. Strong waves come from NE or NNE direction.

scholarly journals The Wave Climate of the Southern Ocean

2020 ◽  
Vol 50 (5) ◽  
pp. 1417-1433
Author(s):  
Ian R. Young ◽  
Emmanuel Fontaine ◽  
Qingxiang Liu ◽  
Alexander V. Babanin
Keyword(s):  
Wind Speed ◽  
Southern Ocean ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Wave Climate ◽  
Altimeter Data ◽  
Local Wind ◽  
Significant Wave ◽  
Individual Wave

AbstractThe wave climate of the Southern Ocean is investigated using a combined dataset from 33 years of altimeter data, in situ buoy measurements at five locations, and numerical wave model hindcasts. The analysis defines the seasonal variation in wind speed and significant wave height, as well as wind speed and significant wave height for a 1-in-100-year return period. The buoy data include an individual wave with a trough to crest height of 26.4 m and suggest that waves in excess of 30 m would occur in the region. The extremely long fetches, persistent westerly winds, and procession of low pressure systems that traverse the region generate wave spectra that are unique. These spectra are unimodal but with peak frequencies that propagate much faster than the local wind. This situation results in a unique energy balance in which waves at the spectra peak grow as a result of nonlinear transfer without any input from the local wind.

scholarly journals Typhoon/Hurricane–Generated Wind Waves Inferred from SAR Imagery

2018 ◽  
Vol 10 (10) ◽  
pp. 1605 ◽  
Author(s):  
Lei Zhang ◽  
Guoqiang Liu ◽  
William Perrie ◽  
Yijun He ◽  
Guosheng Zhang
Keyword(s):  
Wind Speed ◽  
Wind Wave ◽  
Wind Waves ◽  
Wave Mode ◽  
Parametric Models ◽  
Data Sets ◽  
Wave Parameters ◽  
Limited Function ◽  
Sar Imagery ◽  
Mean Square Errors

The wide-swath mode of synthetic aperture radar (SAR) is a good way of detecting typhoon/hurricane winds with a cross-polarization mode. However, its ability to detect wind waves is restricted because of its spatial resolution and nonlinear imaging mechanisms. In this study, we use the SAR-retrieved wind speed, Sentinel-1 SAR wave mode and buoy data to examine fetch- and duration-limited parametric models (denoted H-models), to estimate the wave parameters (significant wave height Hs, dominant wave period Tp) generated by hurricanes or typhoons. Three sets of H-models, in total 6 models, are involved: The H-3Sec model simulates the wave parameters in 3 sections of a given storm (right, left and back); H-LUT models, including the H-LUTI model and H-LUTB model, provide a better resolution of the azimuthal estimation of wind waves inside the storm by analyzing the dataset from Bonnie 1998 and Ivan 2004; and the third set of models is called the H-Harm models, which consider the effects of the radius of the maximum wind speed rm on the wave simulation. In the case of typhoon Krovanh, the comparison with wave-mode measurements shows that the duration-limited models underestimate the high values for the wind-wave Hs, while the fetch models’ results are more accurate, especially for the H-LUTI model. By analyzing 86 SAR wave mode images, it is found that the H-LUTI model is the best among the 6 H-models, and can effectively simulate the wind-wave Hs, except in the center area of the typhoon; root mean square errors (rmse) can reach 0.88 m, and the coefficient correlation (R2) is 0.86. The H-Harm models add rm as an additional factor to be considered, but this does not add significant improvement in performance compared to the others. This limitation is probably due to the fact that the data sets used to develop the H-Harm models have only a limited coverage range, with respect to rm. Applying H-models to RADARSAT-2 ScanSAR mode data, we compare the retrieved wave parameters to collected buoy measurements, showing good consistency. The H-LUTI model, using a fetch-limited function, does the best among these 6 H-models, whose rmse and R2 are 0.86 m and 0.77 for Hs, and 1.06 s and 0.76 for Tp, respectively. Results indicate the potential for H-models to simulate waves generated by typhoons/hurricanes.

scholarly journals A multi-decadal wind-wave hindcast for the North Sea 1949–2014: coastDat2

2017 ◽  
Author(s):  
Nikolaus Groll ◽  
Ralf Weisse
Keyword(s):  
Climate Variability ◽  
North Sea ◽  
Wind Wave ◽  
Wave Model ◽  
Wave Climate ◽  
Climate Variability And Change ◽  
Data Set ◽  
Wave Hindcast ◽  
The North ◽  
The North Sea

Abstract. Long and consistent wave data are important for analysing wave climate variability and change. Moreover, such statistics are also needed in coastal and offshore design and for addressing safety-related issues at sea. Using the third-generation spectral wave model WAM a multi-decadal wind-wave hindcast for the North Sea covering the period 1949–2014 was produced. The hindcast is part of the coastDat database representing a consistent and homogenous met-ocean data set. It is shown that despite not being perfect, data from the wave hindcast are generally suitable for wave climate analysis. In particular comparisons of hindcast data with in situ and satellite observations show on average a reasonable agreement while a tendency towards overestimation of the highest waves could be inferred. Despite these limitations, the wave hindcast still provides useful data for assessing wave climate variability and change as well as for risk analysis, in particular when conservative estimates are needed. Hindcast data are stored at the World Data Center for Climate (WDCC) and can be freely accessed using the https://doi.org/10.1594/WDCC/coastDat-2_WAM-North_Sea (Groll and Weisse, 2016) or via the coastDat web-page http://www.coastdat.de.

Transferring Wave Conditions From Offshore to Nearshore: The Case of Nordfold

2014 ◽  
Author(s):  
Christos N. Stefanakos ◽  
Grim Eidnes
Keyword(s):  
Wave Model ◽  
Wave Climate ◽  
Third Generation ◽  
Satellite Altimeter ◽  
Northern Norway ◽  
Area Of Interest ◽  
Wave Parameters ◽  
Long Time ◽  
Wave Conditions ◽  
Offshore Wave

In the present work, an analysis of the wave climate in Nord-fold area in the northern Norway has been performed. The analysis was carried out by transferring offshore wave conditions to the nearshore area of interest by successive applications of the well-known third-generation wave model SWAN. The area presents a particular interest, since it has a very deep and complex bathymetry near the coast and a very complicated coastline. Analysis has been carried out using a very detailed bathymetry of the area provided by the Norwegian Mapping Authority. Moreover, as input, five year long time series of directional spectra of offshore wave parameters have been used, after being calibrated using the best available satellite altimeter dataset.

scholarly journals CMIP5-Derived Single-Forcing, Single-Model, and Single-Scenario Wind-Wave Climate Ensemble: Configuration and Performance Evaluation

2018 ◽  
Vol 6 (3) ◽  
pp. 90 ◽  
Author(s):  
Alvaro Semedo ◽  
Mikhail Dobrynin ◽  
Gil Lemos ◽  
Arno Behrens ◽  
Joanna Staneva ◽  
...  
Keyword(s):  
Climate Model ◽  
Wind Wave ◽  
Global Climate Model ◽  
Wave Model ◽  
Wave Climate ◽  
Global Ocean ◽  
Climate Change Signal ◽  
Single Model ◽  
Historic Period

A Coupled Model Intercomparison Project Phase 5 (CMIP5)-derived single-forcing, single-model, and single-scenario dynamic wind-wave climate ensemble is presented, and its historic period (1979–2005) performance in representing the present wave climate is evaluated. A single global climate model (GCM)-forcing wave climate ensemble was produced with the goal of reducing the inter GCM variability inherent in using a multi-forcing approach for the same wave model. Seven CMIP5 EC-Earth ensemble runs were used to force seven WAM wave model realizations, while future wave climate simulations, not analyzed here, were produced using a high-emission representative concentration pathway 8.5 (RCP8.5) set-up. The wave climate ensemble’s historic period was extensively compared against a set of 72 in situ wave-height observations, as well as to ERA-Interim reanalysis and Climate Forecast System Reanalysis (CFSR) hindcast. The agreement between the wave climate ensemble and the in situ measurements and reanalysis of mean and extreme wave heights, mean wave periods, and mean wave directions was good, in line with previous studies or even better in some areas of the global ocean, namely in the extratropical latitudes. These results give a good degree of confidence in the ability of the ensemble to simulate a realistic climate change signal.

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