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Using models and observations to understand Arctic sea ice loss
Arctic sea ice is undergoing a period of pronounced decline. Attribution of the decline to greenhouse house gases is usually performed through evaluations with climate model simulations, that incorporate both natural climate variability and greenhouse gas forcing. However, an isolated analysis of climate-model simulations does not usually allow one to assess whether these simulations capture the main processes that govern the evolution of the sea ice system, just as an isolated analysis of observations does not allow one to understand the processes that are responsible for the observed ice loss. However, using both climate models and observations, an enhanced understanding behind the observed evolution of sea ice can be obtained, while observations allow assessments of how realistically the models represent the processes that govern sea-ice evolution in the real world. Models and observations agree well on the sensitivity of Arctic sea ice to global warming and on the main drivers for the observed retreat. In contrast, a robust reduction of the uncertainty range of future sea-ice evolution remains difficult, in particular since the observational record is often too short to robustly examine the impact of internal variability on model biases. Process-based model evaluation and model evaluation based on seasonal-prediction systems provide promising ways to overcome these limitations.
Part of the 2016 Earth Planetary and Space Sciences Institute (EPSSI) Seminar Series
Annual seminar series on topics related to Earth Planetary and Space Sciences and course UN 4000 REMOTE SENSING.
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