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Abstract The Arctic region is experiencing significant changes due to climate change, and the resulting decline in sea ice concentration and extent is already impacting ocean dynamics and exacerbating coastal hazards in the region. In this context, numerical models play a crucial role in simulating the interactions between the ocean, land, sea ice, and atmosphere, thus supporting scientific studies in the region. This research aims to evaluate how different sea ice products with spatial resolutions varying from 2 to 25 km influence a phase averaged spectral wave model results in the Alaskan Arctic under storm conditions. Four events throughout the Fall to Winter seasons in 2019 were utilized to assess the accuracy of wave simulations generated under the dynamic sea ice conditions found in the Arctic. The selected sea ice products used to parameterize the numerical wave model include the National Snow and Ice Data Center (NSIDC) sea ice concentration, the European Centre for Medium‐Range Weather Forecasts (ECMWF) Re‐Analysis (ERA5), the HYbrid Coordinate Ocean Model‐Community Ice CodE (HYCOM‐CICE) system assimilated with Navy Coupled Ocean Data Assimilation (NCODA), and the High‐resolution Ice‐Ocean Modeling and Assimilation System (HIOMAS). The Simulating WAves Nearshore (SWAN) model's accuracy in simulating waves using these sea ice products was evaluated against Sea State Daily Multisensor L3 satellite observations. Results show wave simulations using ERA5 consistently exhibited high correlation with observations, maintaining an accuracy above 0.83 to the observations across all events. Conversely, HIOMAS demonstrated the weakest performance, particularly during the Winter, with the lowest correlation of 0.40 to the observations. Remarkably, ERA5 surpassed all other products by up to 30% in accuracy during the selected storm events, and even when an ensemble was assessed by combining the selected sea ice products, ERA5's individual performance remained unmatched. Our study provides insights for selecting sea ice products under different sea ice conditions for accurately simulating waves and coastal hazards in high latitudes.
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Tracking Multiyear Sea‐Ice Variation in the Arctic Ocean Over Decades With Microseism
Abstract We construct a linear model of microseism power as a function of sea‐ice concentration and ocean‐wave activity with a seismic station located on northern Ellesmere Island. The influence of wind‐ice‐ocean interactions on microseism has been taken into account. We find the increase in microseism power over the last 32 years reflects the long‐term loss of sea ice and increasing ocean‐wave activity in the Arctic Ocean likely associated with climate change. We further assess model performance to determine a representative region over which sea‐ice concentration and ocean‐wave activity most directly influence the microseism power. The seismological methods developed here suggest that there is the potential to augment or refine observations of sea‐ice conditions obtained from satellites and fromin‐situobservations. Seismological methods may thus help determine properties such as sea‐ice thickness, which are less amenable to conventional observations, under a changing climate, particularly in remote areas like the High Arctic.
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- Award ID(s):
- 2336786
- PAR ID:
- 10576204
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 52
- Issue:
- 2
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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