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Downscaling of CMIP6 Climate Projections using Machine Learning Tools to fill the Gaps of the Worldwide CORDEX RCM Simulations
Details
Location:Austria, Azores, Belgium, Bulgaria, Canary Islands, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden
Category:Consulting services
Status:Open
Sectors:Environment & NRM, Information & Communication Technology
Languages:English
Contracting authority: European Centre for Medium-Range Weather Forecasts
Quick summary
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Objectives: The tender aims to provide new high-resolution regional climate data using Machine Learning (ML) techniques, which will downscale CMIP6 Global Climate Models. This project will fill the gaps of the existing and future CORDEX (RCM: Regional Climate Model) data, thus forming a more comprehensive set of regional climate datasets. The objective is to enhance the climate projection uncertainty space coverage and offer guidance and documentation to users for utilizing the new data alongside CORDEX datasets.
Eligibility criteria: Eligible organizations must be located within the European Economic Area, specifically within a European Union Member State or a Copernicus Participating State. The executing service must be carried out at the Contractor's premises within these locat...
Description
Title: C3S2_384 Downscaling of CMIP6 Climate Projections using Machine Learning Tools to fill the Gaps of the Worldwide CORDEX RCM Simulations Internal identifier: C3S2_384
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