Data

MOM and ROMS model output from Antarctic bottom layer temperature advection experiments v1.0

Also known as: MOM_ROMS_UVT
ARC Centre of Excellence for Climate System Science
ARC Centre of Excellence for Climate Extremes Data Manager (Managed by) ARC Centre of Excellence for Climate System Science Data Manager (Managed by) David Webb (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25914/5becb179a75cd&rft.title=MOM and ROMS model output from Antarctic bottom layer temperature advection experiments v1.0&rft.identifier=10.25914/5becb179a75cd&rft.publisher=ARC Centre of Excellence for Climate System Science&rft.description=This dataset contains ocean temperatures and velocity anomalies from idealized wind perturbation experiments resembling a shift towards a positive Southern Annular Mode. Data is provided for two global ocean sea-ice models using the Modular Ocean Model (MOM) at 1/4° horizontal resolution (MOM025; 50 vertical levels) and 1/10° horizontal resolution (MOM01; 75 vertical levels). It also contains velocity anomalies from the same wind perturbation experiment in a single-layer shallow water model using the Regional Ocean Modelling System (ROMS) at 1/4° horizontal resolution. The ROMS zonal and meridional velocity fields, U and V, cover a one-year period with a 0.5 day temporal resolution. Barotropic U and V fields for MOM025 are given at a 5 daily temporal resolution (over a one-year period) and a subset of the MOM01 U and V fields are given at a 6 hourly temporal resolution. Temperature fields, T, are calculated from the average of the annual (MOM01) and seasonal (MOM025) 10 member ensembles from the respective model mean-states.&rft.creator=ARC Centre of Excellence for Climate System Science&rft.date=2018&rft.relation=in press&rft.coverage=-180,-90 180,-90 180,90 -180,90 -180,-90&rft_rights=Access to this dataset is free, the users are free to download this dataset and share it with others and adapt it as long as they credit the dataset owners, provide a link to the license, and if changes were made, indicate it clearly and distribute their contributions under the same license as the original, commercial use is not permitted.&rft_rights=Creative Commons - Attribution - Non Commercial - No Derivatives 4.0 International http://creativecommons.org/licenses/by-nc-sa/4.0/&rft_subject=Physical Oceanography&rft_subject=EARTH SCIENCES&rft_subject=OCEANOGRAPHY&rft_subject=Antarctic warming&rft_subject=Coastal ocean processes&rft.type=dataset&rft.language=English Access the data

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CC-BY-NC-SA

Creative Commons - Attribution - Non Commercial - No Derivatives 4.0 International
http://creativecommons.org/licenses/by-nc-sa/4.0/

Access to this dataset is free, the users are free to download this dataset and share it with others and adapt it as long as they credit the dataset owners, provide a link to the license, and if changes were made, indicate it clearly and distribute their contributions under the same license as the original, commercial use is not permitted.

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Full description

This dataset contains ocean temperatures and velocity anomalies from idealized wind perturbation experiments resembling a shift towards a positive Southern Annular Mode. Data is provided for two global ocean sea-ice models using the Modular Ocean Model (MOM) at 1/4° horizontal resolution (MOM025; 50 vertical levels) and 1/10° horizontal resolution (MOM01; 75 vertical levels). It also contains velocity anomalies from the same wind perturbation experiment in a single-layer shallow water model using the Regional Ocean Modelling System (ROMS) at 1/4° horizontal resolution. The ROMS zonal and meridional velocity fields, U and V, cover a one-year period with a 0.5 day temporal resolution. Barotropic U and V fields for MOM025 are given at a 5 daily temporal resolution (over a one-year period) and a subset of the MOM01 U and V fields are given at a 6 hourly temporal resolution. Temperature fields, T, are calculated from the average of the annual (MOM01) and seasonal (MOM025) 10 member ensembles from the respective model mean-states.

Created: 2018-10-01

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