Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations

This repository contains the estimate of the atmospherically-forced contribution to sea level variability described in Close et al, 2020, and derived from the Ssalto/Duacs altimeter products produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (http://www.mari...

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Main Authors: Close, Sally, Penduff, Thierry, Speich, Sabrina, Molines, Jean-Marc
Format: Dataset
Language:unknown
Published: Zenodo 2020
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.3707930
https://zenodo.org/record/3707930
id ftdatacite:10.5281/zenodo.3707930
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic ocean
sea level anomaly
altimetry
spellingShingle ocean
sea level anomaly
altimetry
Close, Sally
Penduff, Thierry
Speich, Sabrina
Molines, Jean-Marc
Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
topic_facet ocean
sea level anomaly
altimetry
description This repository contains the estimate of the atmospherically-forced contribution to sea level variability described in Close et al, 2020, and derived from the Ssalto/Duacs altimeter products produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (http://www.marine.copernicus.eu). The files contain successive 5-day averages of sea level anomaly, with the same global coverage and 0.25° grid as the Ssalto/Duacs altimeter products. The estimate is created using a spatial bandpass filter, with cutoff scales of ~1.5° and 10.5°. Zeros in the mask file indicate regions in which it has not been possible to evaluate the quality of the estimate. The cutoff scales applied to the altimetry data were determined through analysis of output from the OceaniC Chaos – ImPacts, strUcture, predicTability (Penduff et al, 2014) experiment, comprising a 50-member ensemble of ocean-sea ice model hindcasts with 0.25° horizontal resolution (Bessières et al., 2017). The spatiotemporal coherence between the model-based estimates of the atmospherically-forced (ensemble mean) and total simulated sea surface height signals was analysed, and found to exhibit distinct partitioning between the atmospherically-forced and intrinsic contributions in a spatial (but not temporal) sense, thus suggesting that meaningful estimation of the two components can be achieved based on simple spatial filtering. Verification of the method using the model data indicates good accuracy, with a global mean correlation of 0.9 between the estimate based on spatial filtering and the ensemble mean sea surface height. Full details of the methodology and verification may be found in Close et al, 2020. ---- References : Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091–1106, doi: 10.5194/gmd-10-1091-2017. Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314 Penduff, T., Barnier, B. , Terray, L., Bessières, L., Sérazin, G., Grégorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19. : This work is a contribution to the AtlantOS project, and has received funding from the European Union Horizon 2020 research and innovation program under grant agreement No 633211. This is also a contribution to the PIRATE project funded by CNES through the Ocean Surface Topography Science Team (OST-ST), and to the GLO-HR project funded by the Copernicus Marine Environment Monitoring Service (CMEMS); CMEMS is implemented by Mercator Ocean International in the framework of a delegation agreement with the European Union. This work was also supported by the French national programme LEFE/INSU. The ensemble simulation used in the study was performed as part of the OCCIPUT project, funded by the ANR through contract ANR-13-BS06-0007–01. We acknowledge that the results of this research have been achieved using the PRACE Research Infrastructure resource CURIE based in France at TGCC; some of the computations were performed at TGCC under allocations granted by GENCI. : {"references": ["Bessi\u00e8res, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and S\u00e9razin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091\u20131106, doi: 10.5194/gmd-10-1091-2017.", "Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314", "Penduff, T., Barnier, B. , Terray, L., Bessi\u00e8res, L., S\u00e9razin, G., Gr\u00e9gorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19."]}
format Dataset
author Close, Sally
Penduff, Thierry
Speich, Sabrina
Molines, Jean-Marc
author_facet Close, Sally
Penduff, Thierry
Speich, Sabrina
Molines, Jean-Marc
author_sort Close, Sally
title Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
title_short Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
title_full Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
title_fullStr Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
title_full_unstemmed Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
title_sort estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations
publisher Zenodo
publishDate 2020
url https://dx.doi.org/10.5281/zenodo.3707930
https://zenodo.org/record/3707930
long_lat ENVELOPE(-64.231,-64.231,-65.619,-65.619)
geographic Leroux
geographic_facet Leroux
genre Sea ice
genre_facet Sea ice
op_relation https://dx.doi.org/10.1016/j.pocean.2020.102314
https://dx.doi.org/10.5281/zenodo.3707929
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.3707930
https://doi.org/10.1016/j.pocean.2020.102314
https://doi.org/10.5281/zenodo.3707929
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spelling ftdatacite:10.5281/zenodo.3707930 2023-05-15T18:19:03+02:00 Estimate of the atmospherically-forced contribution to sea surface height variability based on altimetric observations Close, Sally Penduff, Thierry Speich, Sabrina Molines, Jean-Marc 2020 https://dx.doi.org/10.5281/zenodo.3707930 https://zenodo.org/record/3707930 unknown Zenodo https://dx.doi.org/10.1016/j.pocean.2020.102314 https://dx.doi.org/10.5281/zenodo.3707929 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 ocean sea level anomaly altimetry dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.3707930 https://doi.org/10.1016/j.pocean.2020.102314 https://doi.org/10.5281/zenodo.3707929 2021-11-05T12:55:41Z This repository contains the estimate of the atmospherically-forced contribution to sea level variability described in Close et al, 2020, and derived from the Ssalto/Duacs altimeter products produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (http://www.marine.copernicus.eu). The files contain successive 5-day averages of sea level anomaly, with the same global coverage and 0.25° grid as the Ssalto/Duacs altimeter products. The estimate is created using a spatial bandpass filter, with cutoff scales of ~1.5° and 10.5°. Zeros in the mask file indicate regions in which it has not been possible to evaluate the quality of the estimate. The cutoff scales applied to the altimetry data were determined through analysis of output from the OceaniC Chaos – ImPacts, strUcture, predicTability (Penduff et al, 2014) experiment, comprising a 50-member ensemble of ocean-sea ice model hindcasts with 0.25° horizontal resolution (Bessières et al., 2017). The spatiotemporal coherence between the model-based estimates of the atmospherically-forced (ensemble mean) and total simulated sea surface height signals was analysed, and found to exhibit distinct partitioning between the atmospherically-forced and intrinsic contributions in a spatial (but not temporal) sense, thus suggesting that meaningful estimation of the two components can be achieved based on simple spatial filtering. Verification of the method using the model data indicates good accuracy, with a global mean correlation of 0.9 between the estimate based on spatial filtering and the ensemble mean sea surface height. Full details of the methodology and verification may be found in Close et al, 2020. ---- References : Bessières, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and Sérazin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091–1106, doi: 10.5194/gmd-10-1091-2017. Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314 Penduff, T., Barnier, B. , Terray, L., Bessières, L., Sérazin, G., Grégorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19. : This work is a contribution to the AtlantOS project, and has received funding from the European Union Horizon 2020 research and innovation program under grant agreement No 633211. This is also a contribution to the PIRATE project funded by CNES through the Ocean Surface Topography Science Team (OST-ST), and to the GLO-HR project funded by the Copernicus Marine Environment Monitoring Service (CMEMS); CMEMS is implemented by Mercator Ocean International in the framework of a delegation agreement with the European Union. This work was also supported by the French national programme LEFE/INSU. The ensemble simulation used in the study was performed as part of the OCCIPUT project, funded by the ANR through contract ANR-13-BS06-0007–01. We acknowledge that the results of this research have been achieved using the PRACE Research Infrastructure resource CURIE based in France at TGCC; some of the computations were performed at TGCC under allocations granted by GENCI. : {"references": ["Bessi\u00e8res, L., Leroux, S., Brankart, J.-M., Molines, J.-M., Moine, M.-P., Bouttier, P.-A., Penduff, T., Terray, L., Barnier, B., and S\u00e9razin, G., 2017. Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution, Geosci. Model Dev., 10, 1091\u20131106, doi: 10.5194/gmd-10-1091-2017.", "Close, S., Penduff, T., Speich, S. and Molines J.-M., 2020. A means of estimating the intrinsic and atmospherically-forced contributions to sea surface height variability applied to altimetric observations. Progr. Oceanogr. doi: 10.1016/j.pocean.2020.102314", "Penduff, T., Barnier, B. , Terray, L., Bessi\u00e8res, L., S\u00e9razin, G., Gr\u00e9gorio, S., Brankart, J., Moine, M., Molines, J., Brasseur, P., 2014. Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges, Special Issue on High Resolution Ocean Climate Modelling, 19."]} Dataset Sea ice DataCite Metadata Store (German National Library of Science and Technology) Leroux ENVELOPE(-64.231,-64.231,-65.619,-65.619)