Assessment of Oceanic Anomalies of Predictive Potential (D2.5)

Climate prediction is the challenge to forecast climatic conditions months to decades into the future with a skill and regional detail that is of practical use. Will, for example, Arctic sea ice cover increase the next winter? Will Scandinavian hydroclimate be particularly beneficial for hydropower...

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Bibliographic Details
Main Authors: Eldevik Tor, Årthun Marius
Format: Text
Language:unknown
Published: Zenodo 2019
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Online Access:https://dx.doi.org/10.5281/zenodo.3769155
https://zenodo.org/record/3769155
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Summary:Climate prediction is the challenge to forecast climatic conditions months to decades into the future with a skill and regional detail that is of practical use. Will, for example, Arctic sea ice cover increase the next winter? Will Scandinavian hydroclimate be particularly beneficial for hydropower production? Will Southern European summers be excessively warm through the 2020s? To what extent such conditions are predictable in nature and to what extent predictability can be realised in operational climate forecast systems and translated to useful stakeholder information, i.e., the climate equivalent to weather forecasting, remain unknown. It is commonly understood that predictability resides with the more inert components of the climate system and particularly—as is the focus of Blue-Action—with ocean circulation. Blue-Action has substantiated this premise by exploring observations, climate models, and reanalyses (model simulations tightly constrained by available observations). Successful avenues of research and progress made in Blue-Action include mapping out the dominant timescales of European interannual-to-decadal climate variability, the identification of consistent and predictable variability in Atlantic-to-Arctic ocean circulation, the link of ocean variability to fluctuating climate over land and sea ice extent, and making actual climate forecasts toward 2020. : The Blue-Action project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 727852