Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS

Using causal discovery algorithms to boost subseasonal to seasonal forecast skill of Mediterranean rainfall

Project description

Algorithms for improved rainfall predictions

The Mediterranean region (MED) is a hot-spot of anthropogenic climate change. To assure effective near-term planning, decisionmakers in weather-dependent sectors depend on skilful forecasts of precipitation on sub-seasonal to seasonal (S2S) timescales. However, some fundamental challenges prevent reliable predictions beyond approximately 10 days. The EU-funded CausalBoost project will apply an innovative method to improve S2S forecasts of MED rainfall. The approach relies on a combination of innovative causal discovery algorithms from machine learning with operational forecast models. The project will identify central S2S drivers of MED rainfall, systematically assess them with prediction models and produce process-based bias corrections.

Objective

The Mediterranean region (MED) is a hotspot of anthropogenic climate change and impacts are probably already felt today; recent heatwaves and persistent droughts have led to crop failures, wild fires and water shortages, causing large economic losses. Climate models robustly project further warming and drying of the region, putting it at risk of desertification. The particular vulnerability of this water-limited region to climatic changes has created an urgent need for reliable forecasts of rainfall on subseasonal to seasonal (S2S) timescales, i.e. 2 weeks up to a season ahead. This S2S time-range is particularly crucial, as the prediction lead time is long enough to implement adaptation measures, and short enough to be of immediate relevance for decision makers. However, predictions on lead-times beyond approximately 10 days fall into the so-called “weather-climate prediction gap”, with operational forecast models only providing marginal skill. The reasons for this are a range of fundamental challenges, including a limited causal understanding of the underlying sources of predictability.
The proposed research effort aims to improve S2S forecasts of MED rainfall by taking an innovative, interdisciplinary approach that combines novel causal discovery algorithms from complex system science with operational forecast models. This will overcome current limitations of conventional statistical methods to identify relevant sources of predictability and to evaluate modelled teleconnection processes. The outcomes of this project will (i) identify key S2S drivers of MED rainfall, (ii) systematically evaluate them in forecast models, (iii) derive process-based bias corrections to (iv) boost forecast skill. My strong background in both causal inference techniques and atmospheric dynamics puts me in a unique position to lead this innovative effort and to achieve real progress in reducing the “weather-climate prediction gap” for the MED region.

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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

You need to log in or register to use this function

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

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.

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.

MSCA-IF-EF-ST - Standard EF

See all projects funded under this funding scheme

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2018

See all projects funded under this call

Coordinator

THE UNIVERSITY OF READING
Net EU contribution

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.

€ 212 933,76
Address
WHITEKNIGHTS CAMPUS WHITEKNIGHTS HOUSE
RG6 6AH Reading
United Kingdom

See on map

Region
South East (England) Berkshire, Buckinghamshire and Oxfordshire Berkshire
Activity type
Higher or Secondary Education Establishments
Links
Total cost

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.

€ 212 933,76
My booklet 0 0