Date of Award

8-17-2024

Document Type

Thesis

Abstract

Landfast ice in Alaska is experiencing rapid changes in extents and duration, impacting the safety and utility of the ice for Arctic coastal communities. This study presents findings from an updated landfast ice dataset spanning from 1996 to 2023, comprising 7797 Seaward Landfast Ice Edge (SLIE) images derived from a combination of sources including prior work by Mahoney et al. (2014) and new analysis of operational ice charts produced by the National Weather Service Alaska Sea Ice Program (ASIP) and National Ice Center (NIC). We referred to this new dataset as the EM2024 dataset. Analysis of the entire EM2024 dataset reveals a declining trend in landfast ice extent and season length across Alaska. To better understand the nature of these changes and explore options for more robust detection of landfast ice for future datasets, we compared the EM2024 data for the winter period of 2017-2021 with SLIE data derived from Interferometric Synthetic Aperture Radar (InSAR). We used coherence to identify areas of landfast ice and the interferograms to derive the phase gradient as a proxy for estimating the relative stability of the landfast ice. We built on a pervious study by Dammann et al. (2019) by assigning quantitative phase gradient values to identify 3 distinct stability regimes of landfast ice: Bottomfast (|▽ϕ| < 0.14 radians/pixel), Stabilized (0.14 ≤ |▽ϕ| ≤ 0.47 radians/pixel), and Nonstabilized (|▽ϕ| > 0.47 radians/pixel). The monthly average phase gradient decreases as the season progresses, achieving the maximum stability in April or May depending on the region. This study provides an updated assessment of landfast ice conditions in Alaska and introduces a novel approach to identify relatively stable areas of landfast ice using InSAR. These findings have implications for enhancing the safety and planning of activities on landfast ice for Arctic coastal communities.

Handle

http://hdl.handle.net/11122/15497

Download

Share

COinS