Abstract
Climate models are sophisticated computer programs that simulate the mathematical equations representing the known physics of the climate system, which includes the atmosphere, ocean, land surface and ice. Climate models are used for a variety of purposes from studying the dynamics, interactions and feedbacks in the climate system, quantifying the climate variability in the past and present, to predicting and projecting future climate change. The overall objective of ARCPATH is to combine improved regional climate predictions with enhanced understanding of environmental, societal, and economic interactions in order to supply new knowledge on potential “pathways to action”. In ARCPATH climate modelling is one of the most important methods applied to understand how climate in the Arctic affects, and is affected by, the rest of the global climate system. Here we introduce the basic concept of climate modelling with examples from the two models used in the ARCPARTH project: the Norwegian Earth System Model (NorESM) and the European Earth System Model (EC-Earth).
ARCPATH applies decadal climate prediction and regional high-resolution models to provide more accurate information on climate change in the Arctic and Nordic Seas over the next few years. Decadal climate prediction is a new research area that uses advanced statistical methods and ocean and sea ice measurements to better synchronize climate models to observed climate for obtaining reliable climate forecasts. We present the ARCPATH research in these new fields aimed to better meet society demands for local and regional adaptation measures such as fishery, shipping and whale-watching tourism.
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Yang, S., Gao, Y., Torben, K., Keenlyside, N., Counillon, F. (2021). The Climate Model: An ARCPATH Tool to Understand and Predict Climate Change. In: Nord, D.C. (eds) Nordic Perspectives on the Responsible Development of the Arctic: Pathways to Action. Springer Polar Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-52324-4_8
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DOI: https://doi.org/10.1007/978-3-030-52324-4_8
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