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Artificial Neural Networks for the Prediction of Contrails and Aviation Induced Cloudiness

Project description

Estimating non-CO2 environmental damage from aviation

Aviation is known to have a negative impact on the climate due to harmful emissions. However, recent studies and research have uncovered additional effects, particularly concerning the role of contrails and anthropogenic cirrus in cooling the atmosphere and causing cloudiness. Unfortunately, research on this topic has been limited due to the complexity of various variables involved. The EU-funded E-CONTRAIL project aims to conduct a comprehensive study on contrails and aviation-induced cloudiness leveraging state-of-the-art satellite imaginary, exploring their potential impact on the environment. Additionally, the project seeks to develop an artificial neural network capable of predicting non-CO2 aviation damage to the environment. To achieve this goal, the researchers will draw upon extensive knowledge in deep learning and climate science to minimise uncertainties.

Objective

Contrails and aviation-induced cloudiness effects on climate change show large uncertainties since they are subject to meteorological, regional, and seasonal variations. Indeed, under some specific circumstances, aircraft can generate anthropogenic cirrus with cooling. Thus, the need for research into contrails and aviation-induced cloudiness and its associated uncertainties to be considered in aviation climate mitigation actions becomes unquestionable.

We will blend cutting-edge AI techniques (deep learning) and climate science with application to the aviation domain, aiming at closing (at least partially) de existing gap in terms of understanding aviation-induced climate impact.

The overall purpose of E-CONTRAIL project is to develop artificial neural networks (leveraging remote sensing detection methods) for the prediction of the climate impact derived from contrails and aviation-induced cloudiness, contributing, thus, to a better understanding of the non-CO2 impact of aviation on global warming and reducing their associated uncertainties as essential steps towards green aviation.

Specifically, the objectives of E-CONTRAIL are:

O-1 to develop remote sensing algorithms for the detection of contrails and aviation-induced cloudiness.

O-2 to quantify the radiative forcing of ice clouds based on remote sensing and radiative transfer methods.

O-3 to use of deep learning architectures to generate AI models capable of predicting the radiative forcing of contrails based on data-archive numerical weather forecasts and historical traffic

O-4 to assess the climate impact and develop a visualization tool in a dashboard

Upon successful achievement of the objectives described above, we ambition to provide aviation stakeholders with an early and accurate (thus, reducing the associated uncertainty) prediction of those volumes of airspace with the conditions for large global warming impact due to contrails and aviation-induced cloudiness.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-JU-RIA - HORIZON JU Research and Innovation Actions

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Call for proposal

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

(opens in new window) HORIZON-SESAR-2022-DES-ER-01

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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.

€ 291 875,00
Address
CALLE MADRID 126
28903 Getafe (Madrid)
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Higher or Secondary Education Establishments
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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.

€ 291 875,00

Participants (3)

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