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

Project Information

E-CONTRAIL

Grant agreement ID: 101114795

DOI 10.3030/101114795

EC signature date 5 June 2023

Start date 1 June 2023

End date 30 November 2025

Funded under

• Climate, Energy and Mobility

Total cost € 997 500,00

EU contribution € 997 500,00

Coordinated by

UNIVERSIDAD CARLOS III DE MADRID
Spain

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Documents, reports (12)

Contrail tracking and aviation-induced cloudiness algorithm (M10).

D1.2Control tracking and aviation-induced cloudiness algorithm

Deep-learning-based temporal predictions. Technical report/article showing the performance of the models for temporal predictions

D3.2Deep-learning-based temporal predictions. Technical report/article showing the performance of the models for temporal predictions

Project Management Plan (Intermediate Version))

D5.1 - Project Management Plan (Intermediate Version)

Exploratory research plan (ERP)

D5.3Exploratory research plan (ERP)

Dissemination Exploitation and Communications Plan (Intermediate)

D6.1Dissemination Exploitation and Communications Plan (Intermediate)

Project management plan

D5.1Project management plan

Report on the cirrus cloud properties retrieval with MSG.

D2.1Report on the cirrus cloud properties retrieval with MSG.

Dissemination Exploitation and Communications Plan

D6.1Dissemination Exploitation and Communications Plan

Exploratory research report (ERR)

D5.5Exploratory research report

Definition of E-CONTRAIL Aviation Contrails Detection Products and Archive.

D4.1Definition of E-CONTRAIL Aviation Contrails Detection Products and Archive.

Concept outline

D5.2Concept outline

Relevant data for deep-learning models. Report summarizing the relevant data sources and their usage in the various models.

D3.1Relevant data for deep-learning models. Report summarizing the relevant data sources and their usage in the various models.

Other (1)

Solution Slides

Solution SlidesE-CONTRAIL solution is directly linked to WP4 with inputs or enablers coming from WP1, WP2, WP3. We will include all this information in the delivered document

Data sets, microdata, etc (2)

Scientific Look Up Tables of the cirrus cloud radiative forcing (NetCDF formats), +README.

D2.2Scientific Look Up Tables of the cirrus cloud radiative forcing (NetCDF formats), +README.

Data acquisition

Data Management Plan (2)

Data Management Plan (intermediate)

D6.2Data Management Plan (intermediate)

Data Management Plan

D6.2Data Management Plan (with periodic updates)