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Abstract Antarctic sea ice exhibits considerable regional variability that is influenced by ocean and atmospheric conditions. Previous studies have suggested that this variability may be predictable on seasonal-to-interannual time scales. Here, we use initial-value predictability experiments of the Community Earth System Model, version 2 (CESM2), paired with analysis of the CESM2 large ensemble, to further assess the inherent predictability in regional Antarctic sea ice conditions. As in previous studies, we find that Antarctic sea ice area predictability is high for several months after initialization. It is then lost when ice retreats, and predictability is regained in the following ice advance period. In our simulations, this process acts on multiyear time scales with little sensitivity to the seasonal initialization timing but has a strong regional dependence. Long-lived ocean temperature anomalies in the vicinity of the winter ice edge are the primary source of sea ice predictability. Different predictability characteristics occur across regions, depending on how these ocean temperature anomalies are advected relative to regional sea zones. Our results show that sea ice predictability can impart predictability to primary productivity in the Southern Ocean due to its impact on light availability. This has implications for the understanding and management of Southern Ocean marine ecosystems.
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Quantifying the Potential Predictability of Arctic Marine Primary Production
Abstract Phytoplankton in the Arctic Ocean and sub‐Arctic seas support a rich marine food web that sustains Indigenous communities as well as some of the world's largest fisheries. As sea ice retreat leads to further expansion of these fisheries, there is growing need for predictions of phytoplankton net primary production (NPP), which will likely allow better management of food resources in the region. Here, we use perfect model simulations of the Community Earth System Model version 2 (CESM2) to quantify short‐term (month to 2 years) predictability of Arctic Ocean NPP. Our results indicate that NPP is potentially predictable during the most productive summer months for at least 2 years, largely due to the highly predictable Arctic shelves where fisheries in the Arctic are projected to expand. Sea surface temperatures, which are an important limitation on phytoplankton growth and also are predictable for multiple years, are the most important physical driver of this predictability. Finally, we find that the predictability of NPP in the 2030s is enhanced relative to the 2010s, indicating that the utility of these predictions may increase in the near future. This work indicates that operational forecasts using Earth system models may provide moderately skillful predictions of NPP in the Arctic, possibly aiding in the management of Arctic marine resources.
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- Award ID(s):
- 1752724
- PAR ID:
- 10598519
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 130
- Issue:
- 4
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2024JC021668
