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DivPredSkill

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Climate model diversity in the North Atlantic and its impact on prediction skill...

Climate model diversity in the North Atlantic and its impact on prediction skill on interannual to decadal timescales Europe is vulnerable to climate extremes and climate change, making predictions valuable to political and economic stakeholders. The European winter climate depends a lot on sea level pressure differences between Iceland and the A... ver más

18/07/2023

THE UNIVERSITY OF...

213K€

Presupuesto del proyecto: 213K€

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THE UNIVERSITY OF READING No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-07-18

MSCA-IF-2020: Individual Fellowships

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Duración del proyecto: 27 meses Fecha Inicio: 2021-04-08
Fecha Fin: 2023-07-18

Líder del proyecto

THE UNIVERSITY OF READING No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 213K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Europe is vulnerable to climate extremes and climate change, making predictions valuable to political and economic stakeholders. The European winter climate depends a lot on sea level pressure differences between Iceland and the Azores, described by the North Atlantic Oscillation (NAO). Thus, many modelling centres working on predictions, focus on improving NAO predictions. Recent studies find the NAO could be highly predictable, much higher than suggested by individual models - calling for a better process understanding to improve models and predictions. The major source of our ability to make predictions for years and beyond are slow ocean processes, e.g. linked to the Atlantic Meridional Overturning Circulation (AMOC). Both, AMOC and NAO are considered key for North Atlantic decadal variability and predictability. They interact, especially via the NAO driving AMOC, but also vice versa. Consequently, prediction skill is reduced by uncertainties in the NAO-AMOC relationship, but also by severe mean state biases common among models. As of yet, not much effort has been made to understand skill difference across models - motivating the proposed research: The overarching research objective is to understand the causes for inter-model differences in interannual-to-decadal prediction skill - with a focus on the role of the model-dependent NAO-AMOC relationship and mean state biases. Specific objectives are to: (i) identify model differences in the NAO-AMOC interaction and their effect on differences of the potential to predict the North Atlantic; (ii) assess the role of mean state biases for model differences; (iii) link these findings with North Atlantic forecast skill. The proposed research comprises: the novel idea to relate predictability to model biases via NAO-AMOC interaction; and the innovative approach to link findings from long, uninitialised simulations to initialised predictions, enabling new insights valuable to the climate modelling and prediction community.

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