Project description
Better climate model predictions for the North Atlantic
Accurately predicting climate in the North Atlantic over an interannual-to-decadal timescale depends on models correctly simulating atmosphere and ocean processes, including the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC). The EU-funded DivPredSkill project will apply the novel idea of relating predictability to model biases via a better understanding of interactions between the NAO and AMOC and through linking findings from long, uninitialised simulations to initialised predictions, providing fresh insights for climate modelling and the prediction community. Specifically, the research fellow will identify model differences in the simulated NAO-AMOC relationship, assess the role of mean state biases for model differences, and link these findings with North Atlantic forecast skill.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences earth and related environmental sciences atmospheric sciences climatology climatic changes north atlantic oscillation
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
RG6 6AH Reading
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.