arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2104.01246physics.ao-ph
收藏

在海冰消波的经验参数化中对冰厚的依赖性

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

W. Erick Rogers, Jie Yu, David W. Wang

摘要:

这项研究是努力提高海军的能力,预测风产生的海浪在冰出没的地区,在这里,我们正试图进一步通过提高预测波浪能耗散的海冰这一目标的一部分。Rogers等人(2021年)提出了基于模型数据反演的海冰对波浪能的频率依赖性耗散的新估计,并研究了与冰厚和海况变量等各种其他参数的相关性。在这里,我们使用该数据集提出了一个新的耗散参数化,其中明确纳入了依赖于冰的厚度,除了波频。目的是确定依赖于波频和冰厚的参数化是否比仅依赖于波频的参数化更准确。由于频率的主要影响和现场测量的混淆困难,这不是一个必然的结论。使用Yu等人提出的无量纲化方法开发了参数化。(2019)。我们发现,无量纲化确实会导致数据的显着规模崩溃,包括冰厚度确实提高了准确性,最明显的是减少分散时,应用于同一数据集。然而,对独立数据集的评价好坏参半。可能的原因进行了讨论。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑