The role of dynamic sea ice in a simplified general circulation model used for palaeoclimate studies
[EN] Observational records provide a strong basis for constraining sea ice models within a narrow range of climate conditions. Given current trends away from these conditions, models need to be tested over a wider range of climate states. The past provides many such examples based on paleoclimate da...
| Published in: | Proceedings of the YIC 2021 - VI ECCOMAS Young Investigators Conference |
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| Main Authors: | , , |
| Other Authors: | |
| Format: | Book Part |
| Language: | English |
| Published: |
Editorial Universitat Politècnica de València
2022
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10251/186607 https://doi.org/10.4995/YIC2021.2021.12383 |
| Summary: | [EN] Observational records provide a strong basis for constraining sea ice models within a narrow range of climate conditions. Given current trends away from these conditions, models need to be tested over a wider range of climate states. The past provides many such examples based on paleoclimate data, including abrupt, large-amplitude climate events. However, the millennial-duration of typical paleoclimate simulations necessitates balancing the inclusion and sophistication of model processes against computational cost. This is why many simplified models used for multi-millennial simulation only feature representations of thermodynamic sea ice processes, while representing sea ice dynamics is essential for more complex general circulation models. We investigate the impact on climate mean states and variability of introducing sea ice dynamics into the simplified general circulation model PlaSim-LSG. We extend the default thermodynamic sea ice component in PlaSim-LSG with one that includes also dynamic sea ice processes. We adapt the structure and parallelization scheme of this new submodel originating from the MITgcm, a more complex state–of–the–art general circulation model. Then, we evaluate the impact of sea ice dynamics on the simulated climate. Comparing climatologies and the variability of the extended model to control simulations of the pre-existing setup, we find that the standard model overestimates sea ice extent, concentration and thickness. The extended model, however, is biased towards low sea ice amounts and extent. Modifying individual parameters in initial tests of the newly added component is not sufficient to compensate for this bias. Still, the general ability of the model to represent positive and negative biases of the sea ice cover provides a promising starting point for the tuning of PlaSim-LSG with sea ice dynamics. Eventually, the extended model can be used to investigate the role of sea ice for past climate oscillations. This research has been funded by the Deutsche ... |
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