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This study is part of an effort to improve the Navy's ability to forecastwind-generated ocean waves in ice-infested regions, and here we are attemptingto further this goal by improving prediction of dissipation of wave energy bysea ice. Rogers et al. (2021) presented new estimates of frequency-dependentdissipation of wave energy by sea ice, based on model-data inversion, andstudied the correlation with various other parameters, such as ice thicknessand sea state variables. Here, we use that dataset to propose a new dissipationparameterization which explicitly incorporates the dependence on the icethickness, in addition to the wave frequency. The goal is to determine whethera parameterization dependent on wave frequency and ice thickness can be moreaccurate than one dependent only on wave frequency. Due to the dominant impactof frequency and confounding difficulties of field measurements, this is not aforegone conclusion. A parameterization is developed using thenon-dimensionalization approach proposed by Yu et al. (2019). We find that thenon-dimensionalization does result in significant scale collapse of the data,and inclusion of ice thickness does improve accuracy, most evidenced by reducedscatter when applied to the same dataset. However, evaluations againstindependent datasets are mixed. Possible reasons for this are discussed.

Incorporating dependence on ice thickness in empirical parameterizations of wave dissipation by sea ice