An Overview of European Union-Funded Project APPLICATE
This webinar focuses on the APPLICATE project, presenting its main objectives and the multi-model experimental framework in which it relies to assess and improve the predictive capacity of the Arctic and beyond. Dr. Ortega presents a few examples of the project's seasonal prediction activities,...
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ftdatacite:10.5281/zenodo.3441917 2023-05-15T14:38:13+02:00 An Overview of European Union-Funded Project APPLICATE Ortega, Pablo 2019 https://dx.doi.org/10.5281/zenodo.3441917 https://zenodo.org/record/3441917 unknown Zenodo https://zenodo.org/communities/applicate https://dx.doi.org/10.5281/zenodo.3441916 https://zenodo.org/communities/applicate Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Text Presentation article-journal ScholarlyArticle 2019 ftdatacite https://doi.org/10.5281/zenodo.3441917 https://doi.org/10.5281/zenodo.3441916 2021-11-05T12:55:41Z This webinar focuses on the APPLICATE project, presenting its main objectives and the multi-model experimental framework in which it relies to assess and improve the predictive capacity of the Arctic and beyond. Dr. Ortega presents a few examples of the project's seasonal prediction activities, including a multi-model comparison of the predictive skill in Arctic sea ice for all the seasonal forecast systems participating to the project, a first exploration of a suite of experiments assessing the added-value of increasing both the atmospheric and oceanic resolution on seasonal prediction skill, results from empirical statistical models evaluating the optimal number of locations needed to estimate robustly the evolution of Pan-Arctic Sea Ice Volume, and an analysis of how the different forecast errors in Arctic sea ice develop in the EC-Earth and CNRM systems Conference Object Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Ortega ENVELOPE(-57.950,-57.950,-63.950,-63.950) |
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DataCite Metadata Store (German National Library of Science and Technology) |
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description |
This webinar focuses on the APPLICATE project, presenting its main objectives and the multi-model experimental framework in which it relies to assess and improve the predictive capacity of the Arctic and beyond. Dr. Ortega presents a few examples of the project's seasonal prediction activities, including a multi-model comparison of the predictive skill in Arctic sea ice for all the seasonal forecast systems participating to the project, a first exploration of a suite of experiments assessing the added-value of increasing both the atmospheric and oceanic resolution on seasonal prediction skill, results from empirical statistical models evaluating the optimal number of locations needed to estimate robustly the evolution of Pan-Arctic Sea Ice Volume, and an analysis of how the different forecast errors in Arctic sea ice develop in the EC-Earth and CNRM systems |
format |
Conference Object |
author |
Ortega, Pablo |
spellingShingle |
Ortega, Pablo An Overview of European Union-Funded Project APPLICATE |
author_facet |
Ortega, Pablo |
author_sort |
Ortega, Pablo |
title |
An Overview of European Union-Funded Project APPLICATE |
title_short |
An Overview of European Union-Funded Project APPLICATE |
title_full |
An Overview of European Union-Funded Project APPLICATE |
title_fullStr |
An Overview of European Union-Funded Project APPLICATE |
title_full_unstemmed |
An Overview of European Union-Funded Project APPLICATE |
title_sort |
overview of european union-funded project applicate |
publisher |
Zenodo |
publishDate |
2019 |
url |
https://dx.doi.org/10.5281/zenodo.3441917 https://zenodo.org/record/3441917 |
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ENVELOPE(-57.950,-57.950,-63.950,-63.950) |
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Arctic Ortega |
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Arctic Ortega |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_relation |
https://zenodo.org/communities/applicate https://dx.doi.org/10.5281/zenodo.3441916 https://zenodo.org/communities/applicate |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5281/zenodo.3441917 https://doi.org/10.5281/zenodo.3441916 |
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1766310339956178944 |