W. Erick Rogers

Swell and sea in the emerging Arctic Ocean

Ocean surface waves (sea and swell) are generated by winds blowing over a distance (fetch) for a duration of time. In the Arctic Ocean, fetch varies seasonally from essentially zero in winter to hundreds of kilometers in recent summers. Using in situ observations of waves in the central Beaufort Sea, combined with a numerical wave model and satellite sea ice observations, we show that wave energy scales with fetch throughout the seasonal ice cycle. Furthermore, we show that the increased open water of 2012 allowed waves to develop beyond pure wind seas and evolve into swells. The swells remain tied to the available fetch, however, because fetch is a proxy for the basin size in which the wave evolution occurs. Thus, both sea and swell depend on the open water fetch in the Arctic, because the swell is regionally driven. This suggests that further reductions in seasonal ice cover in the future will result in larger waves, which in turn provide a mechanism to break up sea ice and accelerate ice retreat.

In situ measurements of an energetic wave event in the Arctic marginal ice zone

R/V Lance serendipitously encountered an energetic wave event around 77°N, 26°E on 2 May 2010. Onboard GPS records, interpreted as the surface wave signal, show the largest waves recorded in the Arctic region with ice cover. Comparing the measurements with a spectral wave model indicated three phases of interaction: (1) wave blocking by ice, (2) strong attenuation of wave energy and fracturing of ice by wave forcing, and (3) uninhibited propagation of the peak waves and an extension of allowed waves to higher frequencies (above the peak). Wave properties during fracturing of ice cover indicated increased groupiness. Wave-ice interaction presented binary behavior: there was zero transmission in unbroken ice and total transmission in fractured ice. The fractured ice front traveled at some fraction of the wave group speed. Findings do not motivate new dissipation schemes for wave models, though they do indicate the need for two-way, wave-ice coupling.

Observation-Consistent Input and Whitecapping Dissipation in a Model for Wind-Generated Surface Waves: Description and Simple Calculations

A new wind-input and wind-breaking dissipation for phase-averaged spectral models of wind-generated surface waves is presented. Both are based on recent field observations in Lake George, New South Wales, Australia, at moderate-to-strong wind-wave conditions. The respective parameterizations are built on quantitative measurements and incorporate new observed physical features, which until very recently were missing in source terms employed in operational models. Two novel features of the wind-input source functionarethosethataccountfortheeffectsoffullairflowseparation(andthereforerelativereductionofthe input at strongwindforcing) andfor nonlinear behaviorofthis term. Thebreakingtermalsoincorporatestwo new features evident from observational studies; the dissipation consists of two parts—a strictly local dissipation term and a cumulative term—and there is a threshold for wave breaking, below which no breaking occurs. Four variants of the dissipation term are selected for evaluation, with minimal calibration to each. These fourmodels areevaluatedusing simplecalculationsherein.Resultsaregenerallyfavorable.Evaluation for more complex situations will be addressed in a forthcoming paper.

Dissipation of wind waves by pancake and frazil ice in the autumn Beaufort Sea

A model for wind-generated surface gravity waves, WAVEWATCH IIIR , is used to analyze and interpret buoy measurements of wave spectra. The model is applied to a hindcast of a wave event in sea ice in the western Arctic, 11–14 October 2015, for which extensive buoy and ship-borne measurements were made during a research cruise. The model, which uses a viscoelastic parameterization to represent the impact of sea ice on the waves, is found to have good skill—after calibration of the effective viscosity—for prediction of total energy, but over-predicts dissipation of high frequency energy by the sea ice. This shortcoming motivates detailed analysis of the apparent dissipation rate. A new inversion method is applied to yield, for each buoy spectrum, the inferred dissipation rate as a function of wave frequency. For 102 of the measured wave spectra, visual observations of the sea ice were available from buoy-mounted cameras, and ice categories (primarily for varying forms of pancake and frazil ice) are assigned to each based on the photographs. When comparing the inversion-derived dissipation profiles against the independently derived ice categories, there is remarkable correspondence, with clear sorting of dissipation profiles into groups of similar ice type. These profiles are largely monotonic: they do not exhibit the ‘‘roll-over’’ that has been found at high frequencies in some previous observational studies.

Evaluations of Global Wave Prediction at the Fleet Numerical Meteorology and Oceanography Center

It is a major challenge to determine whether bias in operational global wave predictions is predominately due to the wave model itself (internal error) or due to errors in wind forcing (an external error). Another challenge is to characterize bias attributable to errors in wave model physics (e.g., input, dissipation, and nonlinear transfer). In this study, hindcasts and an evaluation methodology are constructed to address these challenges. The bias of the wave predictions is evaluated with consideration of the bias of four different wind forcing fields [two of which are supplemented with the NASA Quick Scatterometer (QuikSCAT) measurements]. It is found that the accuracy of the Fleet Numerical Meteorology and Oceanography Center’s operational global wind forcing has improved to the point where it is unlikely to be the primary source of error in the center’s global wave model (WAVEWATCH-III). The hindcast comparisons are specifically designed to minimize systematic errors from numerics and resolution. From these hindcasts, insight into the physics-related bias in the global wave model is possible: comparison to in situ wave data suggests an overall positive bias at northeast Pacific locations and an overall negative bias at northwest Atlantic locations. Comparison of frequency bands indicates a tendency by the model physics to overpredict energy at higher frequencies and underpredict energy at lower frequencies.

Directional Validation of Wave Predictions

Abstract A methodology for quantitative, directional validation of a long-term wave model hindcast is described and applied. Buoy observations are used as ground truth and the method does not require the application of a parametric model or data-adaptive method to the observations. Four frequency ranges, relative to the peak frequency, are considered. The validation of the hindcast does not suggest any systematic bias in predictions of directional spreading at or above the spectral peak. Idealized simulations are presented to aid in the interpretation of results.

Wave-Breaking Turbulence in the Ocean Surface Layer

AbstractObservations of winds, waves, and turbulence at the ocean surface are compared with several analytic formulations and a numerical model for the input of turbulent kinetic energy by wave breaking and the subsequent dissipation. The observations are generally consistent with all of the formulations, although some differences are notable at winds greater than 15 m s−1. The depth dependence of the turbulent dissipation rate beneath the waves is fit to a decay scale, which is sensitive to the choice of vertical reference frame. In the surface-following reference frame, the strongest turbulence is isolated within a shallow region of depths much less than one significant wave height. In a fixed reference frame, the strong turbulence penetrates to depths that are at least half of the significant wave height. This occurs because the turbulence of individual breakers persists longer than the dominant period of the waves and thus the strong surface turbulence is carried from crest to trough with the wave orb...

Spatial characteristics of ocean surface waves

The spatial variability of open ocean wave fields on scales of O (10km) is assessed from four different data sources: TerraSAR-X SAR imagery, four drifting SWIFT buoys, a moored waverider buoy, and WAVEWATCH IIIⓇ model runs. Two examples from the open north-east Pacific, comprising of a pure wind sea and a mixed sea with swell, are given. Wave parameters attained from observations have a natural variability, which decreases with increasing record length or acquisition area. The retrieval of dominant wave scales from point observations and model output are inherently different to dominant scales retrieved from spatial observations. This can lead to significant differences in the dominant steepness associated with a given wave field. These uncertainties have to be taken into account when models are assessed against observations or when new wave retrieval algorithms from spatial or temporal data are tested. However, there is evidence of abrupt changes in wave field characteristics that are larger than the expected methodological uncertainties.

Adjoint-Free Variational Data Assimilation into a Regional Wave Model

AbstractA variational data assimilation algorithm is developed for the ocean wave prediction model [Wave Model (WAM)]. The algorithm employs the adjoint-free technique and was tested in a series of data assimilation experiments with synthetic observations in the Chukchi Sea region from various platforms. The types of considered observations are directional spectra estimated from point measurements by stationary buoys, significant wave height (SWH) observations by coastal high-frequency radars (HFRs) within a geographic sector, and SWH from satellite altimeter along a geographic track. Numerical experiments demonstrate computational feasibility and robustness of the adjoint-free variational algorithm with the regional configuration of WAM. The largest improvement of the model forecast skill is provided by assimilating HFR data (the most numerous among the considered types). Assimilating observations of the wave spectrum from a moored platform provides only moderate improvement of the skill, which disappear...

Wind and wave influences on sea ice floe size and leads in the Beaufort and Chukchi Seas during the summer-fall transition 2014

Sea ice floe size distribution and lead properties in the Beaufort and Chukchi Seas are studied in the summer-fall transition 2014 to examine the impact on the sea ice cover from storms and surface waves. Floe size distributions are analyzed from MEDEA, Landsat8, and RADARSAT-2 imagery, with a resolution span of 1–100 m. Landsat8 imagery is also used to identify the orientation and spacing of leads. The study period centers around three large wave events during August–September 2014 identified by SWIFT buoys and WAVEWATCH III® model data. The range of floe sizes from different resolutions provides the overall distribution across a wide range of ice properties and estimated thickness. All cumulative floe size distribution curves show a gradual bending toward shallower slopes for smaller floe sizes. The overall slopes in the cumulative floe size distribution curves from Landsat8 images are lower than, while those from RADARSAT-2 are similar to, previously reported results in the same region and seasonal period. The MEDEA floe size distributions appeared to be sensitive to the passage of storms. Lead orientations, regardless of length, correlate slightly better with the peak wave direction than with the mean wave direction. Their correlation with the geostrophic wind is stronger than with the surface wind. The spacing between shorter leads correlates well with the local incoming surface wavelengths, obtained from the model peak wave frequency. The information derived shows promise for a coordinated multisensor study of storm effects in the Arctic marginal ice zone.