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