Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations

This data set contains the interannual variability fields for the sea level (ssh_var_inter_1993_2015_annuel.tar.gz) and its steric (hsterica_var_inter_1993_2015_annuel.tar.gz) and manometric (obp_var_inter_1993_2015_annuel.tar.gz) components over 1993-2015 from the OCCIPUT ensemble simulations. It i...

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Main Authors: Carret, Alice, Llovel, William, Penduff, Thierry, Molines, Jean-Marc
Format: Dataset
Language:unknown
Published: Zenodo 2021
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.5564398
https://zenodo.org/record/5564398
id ftdatacite:10.5281/zenodo.5564398
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description This data set contains the interannual variability fields for the sea level (ssh_var_inter_1993_2015_annuel.tar.gz) and its steric (hsterica_var_inter_1993_2015_annuel.tar.gz) and manometric (obp_var_inter_1993_2015_annuel.tar.gz) components over 1993-2015 from the OCCIPUT ensemble simulations. It is used in the paper « Atmospherically forced and chaotic interannual variability of regional sea level and its components over 1993-2015 » published in Journal of Geophysical Research - Oceans. This dataset has been computed from the OceaniC Chaos – ImPacts, strUcture, predicTability (OCCIPUT) global ocean/sea-ice ensemble simulation. It is composed of 50 members with a horizontal resolution of 1/4° and 75 geopotential levels (Bessières et al., 2017, Penduff et al., 2014). The numerical configuration is based on the version 3.5 of the NEMO model (Madec, 2008). The 50 members were started on January 1st 1960 from a common 21-year spinup. A small stochastic perturbation is applied to the equation of state of sea water (as in Brankart, 2013) within each member during 1960, then switched off during the rest of the simulation. This 1-year perturbation generates an ensemble spread which grows and saturates after a few months up to a few years depending on the region. The 50 members are driven through bulk formulae during the whole 1960-2015 simulation by the same realistic 6-hourly atmospheric forcing (Drakkar Forcing Set DFS5.2, Dussin et al., 2016) derived from ERA interim atmospheric reanalysis. For each member, the simulated sea surface height (SSH) over 1993-2015 is considered. As NEMO is a Boussinesq model, it conserves volume instead of mass. Therefore, the steric effect is missing into the global mean sea level change (Greatbatch 1994). To overcome this issue, we remove the global mean estimate for the sea level time series at each grid point. Then the sea level anomalies obtained are averaged per year and a linear trend is removed from each member. The same processes are applied to the steric and manometric sea level time series. Here is an example of the file header dimensions: member = UNLIMITED // (50 currently) time = 23 y = 1021 x = 1442 variables: float ssh(member, time, y, x) ssh:long_name = "sea level interannual variability" ssh:standard_name = "sea_level interannual variability" ssh:units = "m" ssh:FillValue = "nan" float nav_lat(member, y, x) nav_lat:axis = "Y" nav_lat:long_name = "Latitude" nav_lat:standard_name = "latitude" nav_lat:units = "degrees_north" float nav_lon(member, y, x) nav_lon:axis = "Y" nav_lon:long_name = "Longitude" nav_lon:standard_name = "longitude" nav_lon:units = "degrees_east" float time(time) time:long_name = "time" time:standard_name = "time" time:units = "years since 1992" nav_lat and nav_lon represent the latitude and longitude of the NEMO model whereas var represents the interannual variability time series. : {"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, 1091-1106, doi:10.5194/gmd-10-1091-2017", "Brankart, J.-M. (2013). Impact of uncertainties in the horizontal density gradient upon low resolution global ocean modelling. Ocean Modelling, 66, 64\u201376. https://doi.org/10.1016/j.ocemod.2013.02.004", "Dussin, R., Barnier, B., Brodeau, L., Molines, J. M. (2016). The making of Drakkar forcing set DFS5. DRAKKAR/MyOcean report 01-04-16, IGE, Grenoble, France", "Greatbatch, R. J. , 1994: A note on the representation of steric sea level in models that conserve volume rather than mass, J. Geophys. Res., 99(C6), 12767\u201312771.", "Madec, G. (2008). NEMO Ocean Engine. Note du Pole de mod\u00e9lisation. Institut Pierre-. Simon Laplace (IPSL)Madec, G. (2016). NEMO ocean engine. Institut Pierre-Simon Laplace (IPSL). Retrieved from https://www.nemo-ocean.eu/doc", "Penduff, T., Barnier, B., Terray, L., Bessi\u00e8res, L., S\u00e9razin, G., Gregorio, S., Brankart, J., Moine, M., Molines, J., and Brasseur, P.: Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges,\u00a0 Special\u00a0 Issue\u00a0 on\u00a0 High\u00a0 Resolution\u00a0 Ocean\u00a0 Climate Modelling, 19, 2014"]}
format Dataset
author Carret, Alice
Llovel, William
Penduff, Thierry
Molines, Jean-Marc
spellingShingle Carret, Alice
Llovel, William
Penduff, Thierry
Molines, Jean-Marc
Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
author_facet Carret, Alice
Llovel, William
Penduff, Thierry
Molines, Jean-Marc
author_sort Carret, Alice
title Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
title_short Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
title_full Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
title_fullStr Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
title_full_unstemmed Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations
title_sort atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the occiput ensemble simulations
publisher Zenodo
publishDate 2021
url https://dx.doi.org/10.5281/zenodo.5564398
https://zenodo.org/record/5564398
long_lat ENVELOPE(141.467,141.467,-66.782,-66.782)
ENVELOPE(-64.231,-64.231,-65.619,-65.619)
geographic Laplace
Leroux
geographic_facet Laplace
Leroux
genre Sea ice
genre_facet Sea ice
op_relation https://dx.doi.org/10.5281/zenodo.5564399
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.5564398
https://doi.org/10.5281/zenodo.5564399
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spelling ftdatacite:10.5281/zenodo.5564398 2023-05-15T18:19:02+02:00 Atmospherically-forced and chaotic interannual variability of the sea level and its components over 1993-2015 from the OCCIPUT ensemble simulations Carret, Alice Llovel, William Penduff, Thierry Molines, Jean-Marc 2021 https://dx.doi.org/10.5281/zenodo.5564398 https://zenodo.org/record/5564398 unknown Zenodo https://dx.doi.org/10.5281/zenodo.5564399 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 dataset Dataset 2021 ftdatacite https://doi.org/10.5281/zenodo.5564398 https://doi.org/10.5281/zenodo.5564399 2021-11-05T12:55:41Z This data set contains the interannual variability fields for the sea level (ssh_var_inter_1993_2015_annuel.tar.gz) and its steric (hsterica_var_inter_1993_2015_annuel.tar.gz) and manometric (obp_var_inter_1993_2015_annuel.tar.gz) components over 1993-2015 from the OCCIPUT ensemble simulations. It is used in the paper « Atmospherically forced and chaotic interannual variability of regional sea level and its components over 1993-2015 » published in Journal of Geophysical Research - Oceans. This dataset has been computed from the OceaniC Chaos – ImPacts, strUcture, predicTability (OCCIPUT) global ocean/sea-ice ensemble simulation. It is composed of 50 members with a horizontal resolution of 1/4° and 75 geopotential levels (Bessières et al., 2017, Penduff et al., 2014). The numerical configuration is based on the version 3.5 of the NEMO model (Madec, 2008). The 50 members were started on January 1st 1960 from a common 21-year spinup. A small stochastic perturbation is applied to the equation of state of sea water (as in Brankart, 2013) within each member during 1960, then switched off during the rest of the simulation. This 1-year perturbation generates an ensemble spread which grows and saturates after a few months up to a few years depending on the region. The 50 members are driven through bulk formulae during the whole 1960-2015 simulation by the same realistic 6-hourly atmospheric forcing (Drakkar Forcing Set DFS5.2, Dussin et al., 2016) derived from ERA interim atmospheric reanalysis. For each member, the simulated sea surface height (SSH) over 1993-2015 is considered. As NEMO is a Boussinesq model, it conserves volume instead of mass. Therefore, the steric effect is missing into the global mean sea level change (Greatbatch 1994). To overcome this issue, we remove the global mean estimate for the sea level time series at each grid point. Then the sea level anomalies obtained are averaged per year and a linear trend is removed from each member. The same processes are applied to the steric and manometric sea level time series. Here is an example of the file header dimensions: member = UNLIMITED // (50 currently) time = 23 y = 1021 x = 1442 variables: float ssh(member, time, y, x) ssh:long_name = "sea level interannual variability" ssh:standard_name = "sea_level interannual variability" ssh:units = "m" ssh:FillValue = "nan" float nav_lat(member, y, x) nav_lat:axis = "Y" nav_lat:long_name = "Latitude" nav_lat:standard_name = "latitude" nav_lat:units = "degrees_north" float nav_lon(member, y, x) nav_lon:axis = "Y" nav_lon:long_name = "Longitude" nav_lon:standard_name = "longitude" nav_lon:units = "degrees_east" float time(time) time:long_name = "time" time:standard_name = "time" time:units = "years since 1992" nav_lat and nav_lon represent the latitude and longitude of the NEMO model whereas var represents the interannual variability time series. : {"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, 1091-1106, doi:10.5194/gmd-10-1091-2017", "Brankart, J.-M. (2013). Impact of uncertainties in the horizontal density gradient upon low resolution global ocean modelling. Ocean Modelling, 66, 64\u201376. https://doi.org/10.1016/j.ocemod.2013.02.004", "Dussin, R., Barnier, B., Brodeau, L., Molines, J. M. (2016). The making of Drakkar forcing set DFS5. DRAKKAR/MyOcean report 01-04-16, IGE, Grenoble, France", "Greatbatch, R. J. , 1994: A note on the representation of steric sea level in models that conserve volume rather than mass, J. Geophys. Res., 99(C6), 12767\u201312771.", "Madec, G. (2008). NEMO Ocean Engine. Note du Pole de mod\u00e9lisation. Institut Pierre-. Simon Laplace (IPSL)Madec, G. (2016). NEMO ocean engine. Institut Pierre-Simon Laplace (IPSL). Retrieved from https://www.nemo-ocean.eu/doc", "Penduff, T., Barnier, B., Terray, L., Bessi\u00e8res, L., S\u00e9razin, G., Gregorio, S., Brankart, J., Moine, M., Molines, J., and Brasseur, P.: Ensembles of eddying ocean simulations for climate, CLIVAR Exchanges,\u00a0 Special\u00a0 Issue\u00a0 on\u00a0 High\u00a0 Resolution\u00a0 Ocean\u00a0 Climate Modelling, 19, 2014"]} Dataset Sea ice DataCite Metadata Store (German National Library of Science and Technology) Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) Leroux ENVELOPE(-64.231,-64.231,-65.619,-65.619)