====== ASPECT: Adaptation-oriented Seamless Predictions of European ClimaTe ======



|Project number|101081460|
|Project name|Adaptation-oriented Seamless Predictions of European ClimaTe|
|Project acronym|ASPECT|
|Call|HORIZON-CL5-2022-D1-02|
|Topic|HORIZON-CL5-2022-D1-02-04|
|Type of action|HORIZON-RIA|
|Service|CINEA/C/01|
|Project start date|1 January 2023|
|Project end date|31 December 2026|
|Project duration|48 months|
|Project email address|hello.aspect@bsc.es|
|Project website|https://www.aspect-project.eu/|

==== ASPECT in a nutshell====
**ASPECT** aims for the setup and demonstration of a seamless climate information (SCI) system with a time horizon up to 30yr, accompanied by underpinning research and utilisation of climate information for sectoral applications ('middle- ground level'1). The goal is to improve existing climate prediction systems and merge their outputs across timescales together with climate projections to unify a SCI as a standard for sectoral decision-making.
The focus will be on European climate information but we will also look more widely where there is a policy interest (e.g., disaster preparedness) and in regions of European interest. We will maintain a strong link into an exploit learning from the WCRP lighthouse activities on explaining and predicting earth system change.

To provide a bandwidth diversity of information the SCI system will be based on multi-model climate forecasts, and will build on learning from projects such as EUCP. It will align with new activities on Digital Twins within Europe, including DestinE. The SCI will combine physical science aspects with those from other disciplines to ensure the information is robust, reliable and relevant for a range of user driven decision cases. 

The information package will incorporate baseline forecasts and projections (plus uncertainty), but also new frontiers will be explored (e.g., extremes which are of socioeconomic high-level interest). To be successful the research will encompass: Understanding and attribution of various processes along the timescales (such as exploring signal-to-noise ratio) and their impact on predictability, new ways of initialisation of the prediction systems, merging predictions with projections, provision of regional SCI for Europe by downscaling (statistical methods, AI) and HighRes models (including convection-permitting models) and innovative post-processing method enhancing the skill and robustness of the climate forecasts.

//**In case you would like to get in touch with the project team, please contact us via hello.aspect@bsc.es.**//

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====Consortium====

The ASPECT consortium consists of eight partners and three UK associated partners representing world-class expertise covering a range of physical science, social science and IT disciplines including climate prediction, climate projection, impacts and applications, communication, user engagement and co-development, climate service design and delivery, and data management. Many of the partners have worked together in several other projects, and have led consortia under previous Framework Programmes, including the recent Horizon 2020 EUCP project on which ASPECT builds.

^ Role                ^ Short Name   ^ Legal name and entity website                                                                      ^ Country  ^
| Coordinator         | BSC          | [[https://www.bsc.es/|BARCELONA SUPERCOMPUTING CENTER-CENTRO NACIONAL DE SUPERCOMPUTACION]]        | ES       |
| Beneficiary         | MPG MPI-M    | [[https://mpimet.mpg.de/en/homepage|MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV]]  | DE       |
| Beneficiary         | ECMWF        | [[https://www.ecmwf.int/|EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS]]                      | UK       |
| Beneficiary         | CMCC         | [[https://www.cmcc.it/|FONDAZIONE CENTRO EURO-MEDITERRANEOSUI CAMBIAMENTI CLIMATICI]]              | IT       |
| Beneficiary         | UZagreb      | [[https://www.pmf.unizg.hr/en|FACULTY OF SCIENCE UNIVERSITY OF ZAGREB]]                            | HR       |
| Beneficiary         | SMHI         | [[https://www.smhi.se/en/q/Stockholm/2673730|SVERIGES METEOROLOGISKA OCH HYDROLOGISKA INSTITUT]]   | SE       |
| Beneficiary         | RHMZ         | [[https://www.hidmet.gov.rs/index_eng.php|REPUBLICKI HIDROMETEOROLOSKI ZAVODSRBIJE]]               | RS       |
| Beneficiary         | CODORNIU SA  | [[https://www.codorniu.com/en|CODORNIU SA]]                                                        | ES       |
| Associated Partner  | UNIVLEEDS    | [[https://www.leeds.ac.uk/|UNIVERSITY OF LEEDS]]                                                   | UK       |
| Associated Partner  | MET OFFICE   | [[https://www.metoffice.gov.uk/|MET OFFICE]]                                                       | UK       |
| Associated Partner  | UOXF         | [[https://www.ox.ac.uk/|THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD]]         | UK       |