Trends in wind-wave climate over the head Bay of Bengal region

2016 ◽  
Vol 36 (13) ◽  
pp. 4222-4240 ◽  
Author(s):  
Anindita Patra ◽  
Prasad K. Bhaskaran
Keyword(s):  
Bay Of Bengal ◽  
Wind Wave ◽  
Wave Climate ◽  
Head Bay Of Bengal

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.

scholarly journals Dynamical Downscaling of ERA5 Data on the North-Western Mediterranean Sea: From Atmosphere to High-Resolution Coastal Wave Climate

2021 ◽  
Vol 9 (2) ◽  
pp. 208
Author(s):  
Valentina Vannucchi ◽  
Stefano Taddei ◽  
Valerio Capecchi ◽  
Michele Bendoni ◽  
Carlo Brandini
Keyword(s):  
Mediterranean Sea ◽  
Wind Wave ◽  
Dynamical Downscaling ◽  
Wave Climate ◽  
Western Mediterranean ◽  
Limited Area ◽  
Computational Domain ◽  
Wave Hindcast ◽  
The North ◽  
Western Mediterranean Sea

A 29-year wind/wave hindcast is produced over the Mediterranean Sea for the period 1990–2018. The dataset is obtained by downscaling the ERA5 global atmospheric reanalyses, which provide the initial and boundary conditions for a numerical chain based on limited-area weather and wave models: the BOLAM, MOLOCH and WaveWatch III (WW3) models. In the WW3 computational domain, an unstructured mesh is used. The variable resolutions reach up to 500 m along the coasts of the Ligurian and Tyrrhenian seas (Italy), the main objects of the study. The wind/wave hindcast is validated using observations from coastal weather stations and buoys. The wind validation provides velocity correlations between 0.45 and 0.76, while significant wave height correlations are much higher—between 0.89 and 0.96. The results are also compared to the original low-resolution ERA5 dataset, based on assimilated models. The comparison shows that the downscaling improves the hindcast reliability, particularly in the coastal regions, and especially with regard to wind and wave directions.

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>

scholarly journals On the concordance of 21st century wind-wave climate projections

2018 ◽  
Vol 167 ◽  
pp. 160-171 ◽  
Author(s):  
Joao Morim ◽  
Mark Hemer ◽  
Nick Cartwright ◽  
Darrell Strauss ◽  
Fernando Andutta
Keyword(s):  
21St Century ◽  
Wind Wave ◽  
Wave Climate ◽  
Climate Projections

scholarly journals Evaluation of a CMIP5 derived dynamical global wind wave climate model ensemble

2016 ◽  
Vol 103 ◽  
pp. 190-203 ◽  
Author(s):  
Mark A. Hemer ◽  
Claire E. Trenham
Keyword(s):  
Climate Model ◽  
Wind Wave ◽  
Wave Climate ◽  
Model Ensemble

scholarly journals Robustness and uncertainties in global multivariate wind-wave climate projections

2019 ◽  
Vol 9 (9) ◽  
pp. 711-718 ◽  
Author(s):  
Joao Morim ◽  
Mark Hemer ◽  
Xiaolan L. Wang ◽  
Nick Cartwright ◽  
Claire Trenham ◽  
...  
Keyword(s):  
Wind Wave ◽  
Wave Climate ◽  
Climate Projections

Role of mangroves in wind-wave climate modeling – A review

2020 ◽  
Vol 24 (2) ◽  
Author(s):  
Parvathy Krishnapillai Geethakumari Amma ◽  
Prasad Kumar Bhaskaran
Keyword(s):  
Wind Wave ◽  
Climate Modeling ◽  
Wave Climate

Long-Term Estimation of Wave Climate Variability in the Western Bay of Bengal

2020 ◽  
Vol 45 (3) ◽  
pp. 871-886
Author(s):  
Biplab Sadhukhan ◽  
Arun Chakraborty ◽  
K. Jossia Joseph ◽  
R. Venkatesan
Keyword(s):  
Climate Variability ◽  
Bay Of Bengal ◽  
Wave Climate ◽  
Western Bay Of Bengal

scholarly journals Impact of tropical cyclones on modeled extreme wind‐wave climate

2017 ◽  
Vol 44 (3) ◽  
pp. 1393-1401 ◽  
Author(s):  
Ben Timmermans ◽  
Dáithí Stone ◽  
Michael Wehner ◽  
Harinarayan Krishnan
Keyword(s):  
Tropical Cyclones ◽  
Wind Wave ◽  
Wave Climate ◽  
Extreme Wind
Sign in / Sign up

Export Citation Format

Share Document