Spectral attenuation of gravity wave and model calibration in pack ice

Cheng, Sukun; Stopa, Justin E.; Ardhuin, Fabrice; Shen, Hayley H.

doi:10.5194/tc-2019-290

Cited by 2 publications

(2 citation statements)

References 37 publications

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“…Adopting the viscoelastic model, wave attenuation

{bold-italicS}_{i c e}

due to ice alone may be obtained by solving the velocity potential

ϕ \sim e^{i (|, k_{r} + i k_{i}) x - i σ t}

(Wang & Shen, ). The relation between the energy attenuation coefficient

α

and the imaginary wave number

k_{i}

is (Cheng et al, ; Rogers et al, ):

α = {2 k}_{i} normalC,

shown as the grey curve in Figure . It represents how

{bold-italicS}_{i c e}

damps waves energy without the influence of other source terms.…”

Section: Discussionmentioning

confidence: 99%

Rollover of Apparent Wave Attenuation in Ice Covered Seas

Kohout

Doble

et al. 2017

JGR Oceans

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Wave attenuation from two field experiments in the ice‐covered Southern Ocean is examined. Instead of monotonically increasing with shorter waves, the measured apparent attenuation rate peaks at an intermediate wave period. This “rollover” phenomenon has been postulated as the result of wind input and nonlinear energy transfer between wave frequencies. Using WAVEWATCH III®, we first validate the model results with available buoy data, then use the model data to analyze the apparent wave attenuation. With the choice of source parameterizations used in this study, it is shown that rollover of the apparent attenuation exists when wind input and nonlinear transfer are present, independent of the different wave attenuation models used. The period of rollover increases with increasing distance between buoys. Furthermore, the apparent attenuation for shorter waves drops with increasing separation between buoys or increasing wind input. These phenomena are direct consequences of the wind input and nonlinear energy transfer, which offset the damping caused by the intervening ice.

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“…Adopting the viscoelastic model, wave attenuation

{bold-italicS}_{i c e}

due to ice alone may be obtained by solving the velocity potential

ϕ \sim e^{i (|, k_{r} + i k_{i}) x - i σ t}

(Wang & Shen, ). The relation between the energy attenuation coefficient

α

and the imaginary wave number

k_{i}

is (Cheng et al, ; Rogers et al, ):

α = {2 k}_{i} normalC,

shown as the grey curve in Figure . It represents how

{bold-italicS}_{i c e}

damps waves energy without the influence of other source terms.…”

Section: Discussionmentioning

confidence: 99%

Rollover of Apparent Wave Attenuation in Ice Covered Seas

Kohout

Doble

et al. 2017

JGR Oceans

Self Cite

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“…The basic idea of using the SeaState data to calibrate the viscoelastic wave dispersion model was illustrated in Cheng et al (), in which four pairs of buoy time series were used. In the present study the full buoy datasets are analyzed.…”

Section: Introductionmentioning

confidence: 99%

Calibrating a Viscoelastic Sea Ice Model for Wave Propagation in the Arctic Fall Marginal Ice Zone

et al. 2017

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This paper presents a wave‐in‐ice model calibration study. Data used were collected in the thin ice of the advancing autumn marginal ice zone of the western Arctic Ocean in 2015, where pancake ice was found to be prevalent. Multiple buoys were deployed in seven wave experiments; data from four of these experiments are used in the present study. Wave attenuation coefficients are calculated utilizing wave energy decay between two buoys measuring simultaneously within the ice covered region. Wavenumbers are measured in one of these experiments. Forcing parameters are obtained from simultaneous in‐situ and remote sensing observations, as well as forecast/hindcast models. Cases from three wave experiments are used to calibrate a viscoelastic model for wave attenuation/dispersion in ice cover. The calibration is done by minimizing the difference between modeled and measured complex wavenumber, using a multi‐objective genetic algorithm. The calibrated results are validated using two methods. One is to directly apply the calibrated viscoelastic parameters to one of the wave experiments not used in the calibration and then compare the attenuation from the model with measured data. The other is to use the calibrated viscoelastic model in WAVEWATCH III® over the entire western Beaufort Sea and then compare the wave spectra at two remote sites not used in the calibration. Both validations show reasonable agreement between the model and the measured data. The completed viscoelastic model is believed to be applicable to the fall marginal ice zone dominated by pancake ice.

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Spectral attenuation of gravity wave and model calibration in pack ice

Cited by 2 publications

References 37 publications

Rollover of Apparent Wave Attenuation in Ice Covered Seas

Rollover of Apparent Wave Attenuation in Ice Covered Seas

Calibrating a Viscoelastic Sea Ice Model for Wave Propagation in the Arctic Fall Marginal Ice Zone

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