Lessons from the past to improve the understanding and modelling of Arctic sea ice changes
Fluctuations in the Arctic Ocean sea ice budget are not only a consequence of climate change; they also contribute to shifts in regional (and even global) climate systems through the impact of the ice on oceanic and atmospheric feedback mechanisms. The uncertainty in a majority of numerical climate...
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| Format: | Conference Object |
| Language: | unknown |
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2012
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| Online Access: | https://epic.awi.de/id/eprint/31366/ https://hdl.handle.net/10013/epic.40193 |
| Summary: | Fluctuations in the Arctic Ocean sea ice budget are not only a consequence of climate change; they also contribute to shifts in regional (and even global) climate systems through the impact of the ice on oceanic and atmospheric feedback mechanisms. The uncertainty in a majority of numerical climate models to properly represent the current and recent sea ice coverage in the High Latitudes thus calls for an improvement of the respective climate simulations. Such an improvement may be achieved through comparison and cross-evaluation attempts between proxy-based palaeo sea ice reconstructions and model experiments. Besides sea ice related microfossil or sedimentological data, the novel sea ice biomarker IP25 - a direct indicator of past (spring) sea ice coverage - seems to provide a unique opportunity to satisfactorily track palaeo sea ice variations. In fact, this biomarker repeatedly has been applied to reconstruct the various sea ice conditions that characterised the Arctic Ocean during e.g. glacial, deglacial and Holocene times. With the further development of the PIP25 index even a quantitative assessment of palaeo sea ice coverage could be enabled. Ideally, these palaeo sea ice data may either serve for comparative purposes to validate palaeo sea ice models or they may even display boundary conditions for simulations of sea ice associated changes in oceanic and/or atmospheric circulation patterns. In this regard, major issues that require consideration and discussion are the understanding and the applicability of suitable proxies, the definition of model boundary conditions, and the spatial and temporal resolution that may be covered by proxy and model attempts. |
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