Towards a dynamical description of the sea ice field
Abstract
The sea ice cover is a crucial element of the Arctic climate system. Similar to both the oceanic and atmospheric flows driving its motion, it involves a wide range of scales making both measuring its evolution and implementing models to predict its future state very complex. The problem is twofold. First, in situ field measurements are sparse and satellite remote sensing observations are not homogeneous, spanning a wide range of spatial resolutions and acquisition periods. Second, the implementation of sea ice in models has been based on continuum descriptions. While this yields realistic results at large scales, the complex trajectories of so-called ice floes highlight the need to incorporate Lagrangian statistics at small spatial scales. As a result of both a lack of a unified comprehensive observational network and a suitable numerical approach to represent the sea ice field, a robust framework to validate numerical models against observations is yet to be developed. The floe size distribution (FSD) is an important metric to characterize the sea ice cover and assess model performance. It is hypothesized to have a tight connection to atmosphere-ocean interactions in polar regions as well as hold key information to infer the mechanical properties of sea ice. Historically, FSDs have been assessed at fixed locations over very short periods of at most a few days. New studies have proposed to estimate the evolution of FSDs based on relating waveform acquisitions from radar altimeter data to ice floe chords (from which their sizes are computed). However, these have yet to be rigorously validated. To circumvent this issue and fulfill the Navy’s mission readiness, we will employ our unique ice floe tracking method to develop a description of the sea ice field that connects commonly used statistical metrics of sea ice with the underlying dynamics. The products of this investigation will be readily applicable for assimilation in state-of-the-art numerical models and complement the ongoing Multidisciplinary University Research Initiative (MURI) on the “Integrated Foundations of Sensing, Modeling, and Data Assimilation for Sea Ice Prediction" and the ongoing Sea Ice Dynamic Experiment (SIDEx) campaign funded by the O
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 03, 2022
- Source ID
- N000142212722
Entities
People
- Monica Muñoz Martinez
Organizations
- Brown University
- Office of Naval Research
- United States Navy