A new method for parameterization of wave dissipation by sea ice

Abstract. Observations of wave dissipation and dispersion in sea ice are a necessity for the development and validation of wave-ice interaction models. As the composition of the ice layer can be extremely complex, most models treat the ice layer as a continuum with effective, rather than independently measurable, properties. While this provides opportunities to fit the model to observations, it also obscures our understanding of the wave-ice interactive processes, particularly, it hinders our ability to identify under which environmental conditions these processes are of significance. Here, we aimed to reduce the number of free variables available by studying wave dissipation in landfast ice. That is, in continuous sea ice, such as landfast ice, the effective properties of the continuum ice layer should revert to the material properties of the ice. We present observations of wave dispersion and dissipation from a field experiment on landfast ice in the Arctic and Antarctic. Independent laboratory measurements were performed on sea ice cores from a neighbouring fjord in the Arctic to estimate the ice viscosity. Results show that the dispersion of waves in landfast ice is well described by theory of a thin elastic plate and such observations could provide an estimate of the elastic modulus of the ice. Observations of wave dissipation in landfast ice are about an order of magnitude larger than in ice floes and broken ice. Comparison of our observations against models suggests that wave dissipation is attributed to the viscous dissipation within the ice layer for short waves only, whereas turbulence generated through the interactions between the ice and waves is the most likely process for the dissipation of wave energy for long periods. The separation between short and long waves in this context is expected to be determined by the ice thickness through its influence on the lengthening of short waves. Further studies are required to measure turbulence underneath the ice independently of observations of wave attenuation to confirm our interpretation of the results.

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Method for predicting the ice cover parameters in the waters of the Far-Eastern Seas with a long lead time

Izvestiya TINRO ◽

10.26428/1606-9919-2018-194-239-250 ◽

2018 ◽

Vol 194 ◽

pp. 239-250 ◽

Cited By ~ 1

Author(s):

G. I. Anzhina ◽

A. N. Vrazhkin

Keyword(s):

Sea Ice ◽

Lead Time ◽

Japan Sea ◽

Ice Cover ◽

New Method ◽

Average Accuracy ◽

Ice Edge ◽

Long Term Forecasting ◽

Far Eastern ◽

Far Eastern Seas

New method for long-term forecasting of mean month and mean 10-days values of the ice cover and position of the ice edge in the Far-Eastern Seas is presented. The sea ice regime is formed under influence of thermal and dynamic patterns in the atmosphere and hydrosphere, though mechanisms of its forming and evolution are not yet completely clear, so the sea ice forecasting is based mainly on statistical methods. The new method is developed for the ice parameters prediction for the period with stable ice cover. It uses a physical-statistical model with ensemble approach. The minimum lead time of this method is 7 months. The model assimilates the data on absolute topography of 500 GPa surface, atmospheric pressure at the sea level, air temperature at 850 GPa surface and at the sea surface, relative topography of 500/1000 GPa surfaces, and the South Oscillation index. Archives of these fields for the Northern Hemisphere from 1961 to 2017 are loaded. The ensemble of predictions is formed using the criterion of their maximum accuracy on independent data sets. The method is tested for the winter seasons of 2015/2016 and 2016/2017. The most accurate by 3 parameters are the forecasts for the Okhotsk Sea with the average accuracy 75–83 % that is much better than the accuracy of climatic forecasts (61–67 %). The forecast of the mean month ice cover only is satisfactory for the Japan Sea, and the forecast of the ice edge position only (65 % accuracy) exceeds the climate forecasting accuracy for the Bering Sea, while the climatic forecasting shows better results for the ice cover. The average accuracy of forecasting with new method (all parameters for all seas) exceeds 70 %, that allows to recommend the method for practical using. A prognostic product could be proposed as charts of the sea ice edge for future winter with estimations of the ice cover for each sea by months and 10-days.

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Reducing Errors in Satellite-Derived Arctic Sea Ice Thicknesses

Eos ◽

10.1029/2017eo087179 ◽

2017 ◽

Author(s):

Sarah Witman

Keyword(s):

Sea Ice ◽

Arctic Sea Ice ◽

New Method ◽

Ice Thickness ◽

Sea Ice Thickness ◽

Arctic Sea ◽

Arctic Sea Ice Thickness

Salty snow throws off satellite-based estimates of Arctic sea ice thickness by up to 25%. A new method seeks to fix that.

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Consistently Estimating Internal Climate Variability from Climate Model Simulations

Journal of Climate ◽

10.1175/jcli-d-16-0428.1 ◽

2017 ◽

Vol 30 (23) ◽

pp. 9555-9573 ◽

Cited By ~ 24

Author(s):

Dirk Olonscheck ◽

Dirk Notz

Keyword(s):

Climate Variability ◽

Sea Ice ◽

Climate Model ◽

Surface Air Temperature ◽

Internal Variability ◽

Arctic Sea Ice ◽

New Method ◽

Polar Regions ◽

Internal Climate Variability ◽

Ensemble Simulations

This paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multimodel ensemble. The method regresses each model’s estimate of internal variability from the preindustrial control simulation on the variability derived from a model’s ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multimodel consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics, and polar regions, and extremely likely decreases in midlatitudes. Applying the method to sea ice volume and area shows that their respective internal variability likely or extremely likely decreases proportionally to their mean state, except for Arctic sea ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice, the method confirms that internal variability can explain most of the models’ deviation from observed trends but often not the models’ deviation from the observed mean states. The new method benefits from a large number of models and long preindustrial control simulations, but it requires only a small number of ensemble simulations. The method allows for consistent consideration of internal variability in multimodel studies and thus fosters understanding of the role of internal variability in a changing climate.

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A Method to Estimate Reflection and Directional Spread Using Rotary Spectra from Accelerometers on Large Ice Floes

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-16-0219.1 ◽

2017 ◽

Vol 34 (5) ◽

pp. 1125-1137 ◽

Cited By ~ 2

Author(s):

Graig Sutherland ◽

Jean Rabault ◽

Atle Jensen

Keyword(s):

Sea Ice ◽

Length Scale ◽

Wave Spectra ◽

Robust Method ◽

Wave Direction ◽

Wave Dissipation ◽

Model Free ◽

Directional Wave ◽

The Mean ◽

Ice Floes

AbstractThe directional wave spectra in sea ice are an important aspect of wave evolution and can provide insights into the dominant components of wave dissipation, that is, dissipation due to scattering or dissipation due to viscous processes under the ice. A robust method for the measurement of directional wave spectra parameters in sea ice from a three-axis accelerometer—or a heave, pitch, and roll sensor—is proposed. The method takes advantage of certain aspects of sea ice and makes use of rotary spectra techniques to provide model-free estimates for the mean wave direction, directional spread, and reflection coefficient. The method is ideally suited for large ice floes—that is, where the ice floe length scale is much greater than the wavelength—but a framework is provided to expand the parameter space where the method may be effective.

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A New Method to Filter Out Radio-Frequency Interference (RFI) from SMOS Level 1C Data for Sea Ice Applications

Towards an Interdisciplinary Approach in Earth System Science - Springer Earth System Sciences ◽

10.1007/978-3-319-13865-7_11 ◽

2015 ◽

pp. 91-98 ◽

Cited By ~ 1

Author(s):

Marcus Huntemann ◽

Georg Heygster

Keyword(s):

Sea Ice ◽

Radio Frequency ◽

New Method ◽

Radio Frequency Interference

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Can Antarctic sea-ice extent be determined from whaling records?

Polar Record ◽

10.1017/s0032247400016831 ◽

2000 ◽

Vol 36 (199) ◽

pp. 345-347 ◽

Cited By ~ 8

Author(s):

Stephen Vaughan

Keyword(s):

Sea Ice ◽

Accurate Method ◽

Reliable Information ◽

New Method ◽

Sea Ice Extent ◽

Antarctic Sea Ice ◽

The Subject ◽

Ice Edge ◽

Sea Ice Edge ◽

Sighting Data

SummeryThe subject of retreating global sea-ice extent is a matter of grave concern, and any new method that promises reliable information about past ice-extent parameters must be welcomed. However, the method proposed by De la Mare should be viewed with caution for four reasons. First, his predictions of sea-ice extent do not correspond with known observations of sea-ice extent from research published in 1936 and 1972. Second, his predictions correlate much more closely with the whale-sighting data recorded by Hansen (1936). Third, since Hansen's sea-ice extent data do not correspond closely with his whalesighting data, it must be questioned whether whale-based data should be used for retrospective predictions relating to sea-ice extent. And finally, information from the IWC indicates that De la Mare's datasets are not considered accurate. Predicting sea-ice edge extent is complex, and, it would seem, a purely biological approach is not necessarily the most accurate method to adopt.

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