CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in...

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Main Authors: Agustin Sanchez-Arcilla, Joanna Staneva, Luigi Cavaleri, Merete Badger, Jean Bidlot, Jacob T. Sorensen, Lars B. Hansen, Adrien Martin, Andy Saulter, Manuel Espino, Mario M. Miglietta, Marc Mestres, Davide Bonaldo, Paolo Pezzutto, Johannes Schulz-Stellenfleth, Anne Wiese, Xiaoli Larsen, Sandro Carniel, Rodolfo Bolaños, Saleh Abdalla, Alessandro Tiesi
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Marine Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2021.604741/full
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spelling doaj-f80be96ebef343e3ae7f38c2fea513bb2021-03-24T06:39:50ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452021-03-01810.3389/fmars.2021.604741604741CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for ApplicationsAgustin Sanchez-Arcilla0Joanna Staneva1Luigi Cavaleri2Merete Badger3Jean Bidlot4Jacob T. Sorensen5Lars B. Hansen6Adrien Martin7Andy Saulter8Manuel Espino9Mario M. Miglietta10Marc Mestres11Davide Bonaldo12Paolo Pezzutto13Johannes Schulz-Stellenfleth14Anne Wiese15Xiaoli Larsen16Sandro Carniel17Rodolfo Bolaños18Saleh Abdalla19Alessandro Tiesi20Universitat Politecnica de Catalunya, BarcelonaTech (UPC), Barcelona, SpainInstitute of Coastal Systems, Helmholtz Centre for Materials and Coastal Research (HZG), Geesthacht, GermanyInstitute of Marine Science, National Research Council (CNR), Venezia, ItalyTechnical University of Denmark (DTU), Lyngby, DenmarkEuropean Centre for Medium-Range Weather Forecasts, Reading, United KingdomDanish Hydrologic Institute, Copenhagen, DenmarkDanish Hydraulic Institute (DHI) – DHI GRAS, Hørsholm, DenmarkNational Oceanography Centre, University of Southampton, Southampton, United KingdomMet Office, Exeter, United KingdomUniversitat Politecnica de Catalunya, BarcelonaTech (UPC), Barcelona, Spain0Institute of Atmospheric Sciences and Climate (CNR-ISAC), Bologna, ItalyUniversitat Politecnica de Catalunya, BarcelonaTech (UPC), Barcelona, SpainInstitute of Marine Science, National Research Council (CNR), Venezia, ItalyInstitute of Marine Science, National Research Council (CNR), Venezia, ItalyInstitute of Coastal Systems, Helmholtz Centre for Materials and Coastal Research (HZG), Geesthacht, GermanyInstitute of Coastal Systems, Helmholtz Centre for Materials and Coastal Research (HZG), Geesthacht, GermanyTechnical University of Denmark (DTU), Lyngby, DenmarkInstitute of Marine Science, National Research Council (CNR), Venezia, Italy1DHI, Hørsholm, DenmarkEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom0Institute of Atmospheric Sciences and Climate (CNR-ISAC), Bologna, ItalyRecent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions.https://www.frontiersin.org/articles/10.3389/fmars.2021.604741/fulloceanographycoastal and regionalcoupled modelssentinel datadownscalingcoastal ocean applications
collection DOAJ
language English
format Article
sources DOAJ
author Agustin Sanchez-Arcilla
Joanna Staneva
Luigi Cavaleri
Merete Badger
Jean Bidlot
Jacob T. Sorensen
Lars B. Hansen
Adrien Martin
Andy Saulter
Manuel Espino
Mario M. Miglietta
Marc Mestres
Davide Bonaldo
Paolo Pezzutto
Johannes Schulz-Stellenfleth
Anne Wiese
Xiaoli Larsen
Sandro Carniel
Rodolfo Bolaños
Saleh Abdalla
Alessandro Tiesi
spellingShingle Agustin Sanchez-Arcilla
Joanna Staneva
Luigi Cavaleri
Merete Badger
Jean Bidlot
Jacob T. Sorensen
Lars B. Hansen
Adrien Martin
Andy Saulter
Manuel Espino
Mario M. Miglietta
Marc Mestres
Davide Bonaldo
Paolo Pezzutto
Johannes Schulz-Stellenfleth
Anne Wiese
Xiaoli Larsen
Sandro Carniel
Rodolfo Bolaños
Saleh Abdalla
Alessandro Tiesi
CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
Frontiers in Marine Science
oceanography
coastal and regional
coupled models
sentinel data
downscaling
coastal ocean applications
author_facet Agustin Sanchez-Arcilla
Joanna Staneva
Luigi Cavaleri
Merete Badger
Jean Bidlot
Jacob T. Sorensen
Lars B. Hansen
Adrien Martin
Andy Saulter
Manuel Espino
Mario M. Miglietta
Marc Mestres
Davide Bonaldo
Paolo Pezzutto
Johannes Schulz-Stellenfleth
Anne Wiese
Xiaoli Larsen
Sandro Carniel
Rodolfo Bolaños
Saleh Abdalla
Alessandro Tiesi
author_sort Agustin Sanchez-Arcilla
title CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
title_short CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
title_full CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
title_fullStr CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
title_full_unstemmed CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications
title_sort cmems-based coastal analyses: conditioning, coupling and limits for applications
publisher Frontiers Media S.A.
series Frontiers in Marine Science
issn 2296-7745
publishDate 2021-03-01
description Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions.
topic oceanography
coastal and regional
coupled models
sentinel data
downscaling
coastal ocean applications
url https://www.frontiersin.org/articles/10.3389/fmars.2021.604741/full
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