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

Physics-informed nEuRal networks for SEVERe wEather event prediction

Project description

A new way to compute the behaviour of storms

The prediction of severe weather events like heavy rain and windstorms is important because it gives communities time to better prepare in advance. It’s also critical information for the air transport industry since delays and actions to take may be anticipated. The EU-funded PERSEVERE project is exploring the use of neural networks, specifically physics‐informed neural networks (PINNs) that combine data-driven machine learning and physical models, to predict the fluid status of the atmosphere in regions affecting air traffic. PERSEVERE will also explore the development of dedicated generative adversarial networks to enhance and complement the outcome of PINNs by boosting the precision of the prediction and embedding additional variables such as temperature and air humidity.

Objective

The novel development of Physics-Informed Neural Networks (PINNs), which incorporate the constraints given by physics laws into the training process, as excellent means of computing fluidic fields and their characteristics such as velocity and pressure has open the gates to numerous applications. One of them is the data enhancement of experiments, since PINNs can reconstruct by means of applying the Navier-Stokes equations as loss function the full fluid domain in areas where experiments are limited by technology. On the other hand, the development of Generative Adversarial Networks (GANs) as robust networks with excellent precision but excessive computational costs leaves the door open to further investigate new applications where PINNs and GANs can be combined to amplify their strengths and reduce their weak points. One of those applications regards the forecast of severe weather conditions, where PINNs are useful to compute the fluidic behavior of storms approaching a certain location, whereas GANs can incorporate many additional parameters, such as wind speed, humidity, temperature and electric content, which may be essential to determine if in the following 48h a certain location is going to suffer from severe weather conditions.
The estimation and forecast of storms is essential to the air transport industry, since the losses incurred due to delays and deviations of air traffic caused by the presence of storms have been reported to be over $38.5 billion in USA. The development of a computational architecture which is able to determine if severe weather events are going to take place within the next 48h is therefore of crucial importance. There exists no model nor application in which the combined strengths of PINNs and GANs have been put into practice, one to rapidly estimate the fluidic behaviour of a moving storm, the second to calculate the properties of the field with high precision.

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.

You need to log in or register to use this function

Keywords

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.

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.

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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) HORIZON-MSCA-2021-PF-01

See all projects funded under this call

Coordinator

UNIVERSIDAD CARLOS III DE MADRID
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.

€ 165 312,96
Address
CALLE MADRID 126
28903 Getafe (Madrid)
Spain

See on map

Region
Comunidad de Madrid Comunidad de Madrid Madrid
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.

No data

Partners (1)

My booklet 0 0