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iMIRACLI SIGNED

innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts (iMIRACLI)

Total Cost €

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EC-Contrib. €

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Partnership

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Project "iMIRACLI" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

Organization address
address: WELLINGTON SQUARE UNIVERSITY OFFICES
city: OXFORD
postcode: OX1 2JD
website: www.ox.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 4˙185˙717 €
 EC max contribution 4˙185˙717 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2019
 Funding Scheme MSCA-ITN-ETN
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) coordinator 909˙517.00
2    STOCKHOLMS UNIVERSITET SE (STOCKHOLM) participant 563˙965.00
3    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 562˙553.00
4    DEUTSCHES ZENTRUM FUER LUFT - UND RAUMFAHRT EV DE (KOELN) participant 505˙576.00
5    UNIVERSITAET LEIPZIG DE (LEIPZIG) participant 505˙576.00
6    THE UNIVERSITY OF EDINBURGH UK (EDINBURGH) participant 303˙172.00
7    UNIVERSITY COLLEGE LONDON UK (LONDON) participant 303˙172.00
8    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE CH (LAUSANNE) participant 281˙276.00
9    UNIVERSITAT DE VALENCIA ES (VALENCIA) participant 250˙904.00

Map

 Project objective

Climate change is one of the most urgent problems facing mankind. Implementation of the Paris climate agreement relies on robust scientific evidence. Yet, the uncertainty of non-greenhouse gas forcing associated with aerosol-cloud interactions limits our constraints on climate sensitivity. Radically new ideas are required. While the majority of forcing estimates are model based, model uncertainties remain too large to achieve the required uncertainty reductions. The quantification of aerosol cloud climate interactions in Earth Observations is thus one of the major challenges of climate science. Progress has been hampered by the difficulty to disentangle aerosol effects on clouds and climate from their covariability with confounding factors, limitations in remote sensing, very low signal-to-noise ratios as well as computationally, due to the scale of the big (>100Tb) datasets and their heterogeneity. Such big data challenges are not unique to climate science but occur across a wide range of data science applications. Innovative techniques developed by the AI and machine learning community show huge potential but have not yet found their way into climate sciences – and climate scientists are currently not trained to capitalise on these advances. The central hypothesis of IMIRACLI is that merging machine learning and climate science will provide a breakthrough in the exploration of existing datasets, and hence advance our understanding of aerosol-cloud forcing and climate sensitivity. Its innovative training plan will match each ESR with supervisors from climate and data sciences as well as a non-academic advisor and secondment and provide them with state-of-the-art data and climate science training. Partners from the non-academic sector will be closely involved in each of the projects and provide training in a commercial context. This ETN will produce a new generation of climate data scientists, ideally trained for employment in the academic and commercial sectors.

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The information about "IMIRACLI" are provided by the European Opendata Portal: CORDIS opendata.

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