Project description
A new pathway to climate risk assessment
How big is the risk of a climate-related physical event that may cause damage or loss? While risk assessment and adaptation responses are a priority, the methods need improvement. To date, the assessment of climate hazards, risk and resilience has usually been based on static models which lose the appreciation of the temporal and spatial dynamics and complex feedback responses. The implementation of novel approaches and models is not always easy. Barriers include the availability, cost and reliability of input data sets, computational times and costs, and the lack of consideration of the combined effect of multiple hazards. With the support of the Marie Skłodowska-Curie Actions, the EXPEDITE project will test machine learning and data science techniques to remove these barriers.
Objective
Despite the urgent need for adopting multi-hazard risk approaches and for the implementation of resilience-enhancing measures in
the EU and at the global scale, several challenges for effective implementation of risk assessment and adaptation responses remain.
In particular, the assessment of climate hazards, risk and resilience is often based on static models which lose the appreciation of the
temporal and spatial dynamics and complex feedback responses within the system. As a consequence, the information provided
often fails to inform decision-makers and other end-users with the correct data to be actioned through timely responses to emerging
risks. Barriers to development and implementation of novel approaches and models include the availability, cost and reliability of
input datasets; the computational times and costs; the lack of consideration of the combined effect of multiple hazards; the spatial
and temporal changes in the exposure of assets and services; and the complex adaptive responses of government, society and the
environment to emerging risks. EXPEDITE aims at exploring new pathways to reduce and remove these barriers by exploring, testing
and deploying machine learning and data science techniques and by developing and testing a climate service prototype, tailored to
end-users. These may include institutional clients (such as Regions) the private sector or individual consumers. The research project,
which will last 24 months, will be mainly conducted at CMCC@Ca’Foscari in Venice (Italy) under the supervision of Prof. Andrea
Critto, with targeted secondments for advanced training in machine learning and data science at MALGA, University of Genoa and
for climate service design and prototyping at GECOsistema srl, a specialised R&D consulting lab. A targeted dissemination and
communication plan will allow EXPEDITE to share the research activities, outcomes and outputs with researchers, policymakers, the
private sector and the general public.
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.
- engineering and technology environmental engineering ecosystem-based management climate change adaptation
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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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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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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) HORIZON-MSCA-2021-PF-01
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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.
30123 VENEZIA
Italy
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.