Going with the floe: tracking CESM Large Ensemble sea ice in the Arctic provides context for ship-based observations
In recent decades, Arctic sea ice has shifted toward younger, thinner, seasonal ice regime. Studying and understanding this “New” Arctic will be the focus of a year-long ship campaign beginning in autumn 2019. Lagrangian tracking of sea ice floes in the Community Earth System Model Large Ensemble (C...
| Main Authors: | , , , , , |
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| Format: | Text |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/tc-2019-145 https://www.the-cryosphere-discuss.net/tc-2019-145/ |
| Summary: | In recent decades, Arctic sea ice has shifted toward younger, thinner, seasonal ice regime. Studying and understanding this “New” Arctic will be the focus of a year-long ship campaign beginning in autumn 2019. Lagrangian tracking of sea ice floes in the Community Earth System Model Large Ensemble (CESM-LE) allow for understanding conditions that a floe will experience throughout the calendar year. These model tracks can assist with campaign planning, put into context a single year of observations, and provide guidance on how observations can help with model development. The modelled floe tracks show a Transpolar Drift trajectory is likely, providing guidance for coordinating satellite, airborne, and ground observations. However, there is a smaller possibility of high-risk tracks, including possible melt of the floe before the end of a calendar year. Because of high variability in the melt season sea ice conditions, we recommend in-situ sampling over a large range of ice conditions for a more complete understanding of how ice type or surface condition affect processes. We find that sea ice predictability emerges rapidly during the autumn freeze-up and anticipate that process-based observations during this period may help elucidate the processes leading to this change in predictability. Accurate seasonal cycle comparison of sea ice conditions between point-based observations a model requires the model to use a Lagrangian framework. |
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