Estimation of Available Wave Energy in the Barents Sea

Myslenkov, Stanislav; Markina, Margarita; Киселева, С. В.; Stoliarova, Elena; Архипкин, В. С.; Umnov, P. M.

doi:10.1134/s0040601518070054

Cited by 4 publications

(6 citation statements)

References 6 publications

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“…1). Previously, this grid was successfully used for wave modeling (Myslenkov et al, 2018b(Myslenkov et al, , 2019. The need to take the swell propagating from Atlantic ocean into account when calculating the height of significant waves in the Barents Sea was clearly shown in the previous work by Myslenkov et al (2015).…”

Section: Wave Modelingmentioning

confidence: 99%

The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling

2021

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Abstract. This paper investigates the impact of sea waves on turbulent heat fluxes in the Barents Sea. The Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm, meteorological data from reanalysis and wave data from the WAVEWATCH III wave model results were used. The turbulent heat fluxes were calculated using the modified Charnock parameterization for the roughness length and several parameterizations that explicitly account for the sea wave parameters. A catalog of storm wave events and a catalog of extreme cold-air outbreaks over the Barents Sea were created and used to calculate heat fluxes during extreme events. The important role of cold-air outbreaks in the energy exchange between the Barents Sea and the atmosphere is demonstrated. A high correlation was found between the number of cold-air outbreak days and turbulent fluxes of sensible and latent heat, as well as with the net flux of longwave radiation averaged over the ice-free surface of the Barents Sea during a cold season. The differences in the long-term mean values of heat fluxes calculated using different parameterizations for the roughness length are small and are on average 1 %–3 % of the flux magnitude. The parameterizations of Taylor and Yelland (2001) and Oost et al. (2002) lead to an increase in the magnitude of the fluxes on average, and the parameterization of Drennan et al. (2003) leads to a decrease in the magnitude of the fluxes over the entire sea compared with the Charnock parameterization. The magnitude of heat fluxes and their differences during the storm wave events exceed the mean values by a factor of 2. However, the effect of explicitly accounting for the wave parameters is, on average, small and multidirectional, depending on the parameterization used for the roughness length. With respect to the climatic aspect, it can be argued that explicitly accounting for sea waves in the calculations of heat fluxes can be neglected. However, during the simultaneously observed storm wave events and cold-air outbreaks, the sensitivity of the calculated values of fluxes to the parameterizations used increases along with the turbulent heat transfer increase. In some extreme cases, during storms and cold-air outbreaks, the difference exceeds 700 W m−2.

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Section: Wave Modelingmentioning

confidence: 99%

The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling

2021

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“…A more detailed description of the model configuration, the main features of the experiments with the unstructured mesh is presented in [46][47][48]. As a model output, we got the wind wave fields for every three hours from 1979 to 2017 (total 39 years).…”

Section: Wave Modelingmentioning

confidence: 99%

Thirty-Nine-Year Wave Hindcast, Storm Activity, and Probability Analysis of Storm Waves in the Kara Sea, Russia

Myslenkov

Platonov

Kislov

et al. 2021

Water

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The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

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“…Wave climate and storm activity in the Barents Sea was previously investigated using this wave reanalysis [32,35,36]. However, the spatial resolution of the wave model and atmospheric forcing was not sufficient to adequately reproduce orographic winds [9,37].…”

Section: Wave Reanalysismentioning

confidence: 99%

Influence of Novaya Zemlya Bora on Sea Waves: Satellite Measurements and Numerical Modeling

2020

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This paper investigates for the first time sea waves during Novaya Zemlya bora—a downslope windstorm on the western coast of the archipelago during eastern winds—using a statistical and case-study approach. Statistical analysis of altimeter data off the western coast of Novaya Zemlya during bora shows that, despite strong wind forcing, the frequency of hazard wave heights was low due to the limited fetch. This result was confirmed by the high-resolution numerical simulations of two severe bora episodes. However, the influence of bora on sea waves in some cases was significant: bora increased wave height at a distance from shore greater than 200 km and wave height anomaly was up to 2–3 m. The influence of the wind input parametrization choice during bora is great in the coastal region; however, parametrizations with fetch-limited modifications and strong-wind adopted aerodynamic drag coefficient do not improve the modeling results in the open sea where altimeter data are available.

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Estimation of Available Wave Energy in the Barents Sea

Cited by 4 publications

References 6 publications

The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling

The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling

Thirty-Nine-Year Wave Hindcast, Storm Activity, and Probability Analysis of Storm Waves in the Kara Sea, Russia

Influence of Novaya Zemlya Bora on Sea Waves: Satellite Measurements and Numerical Modeling

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