Coastal freshening enhances eddy-driven heat transfer toward the Antarctic margins

• Main Authors: Si, Yidongfang, Stewart, Andrew L., Eisenman, Ian
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Zenodo 2022
• Subjects: Antarctic; The Antarctic; Antarc*
• Online Access: https://dx.doi.org/10.5281/zenodo.5915019; https://zenodo.org/record/5915019

This release contains: MITgcm_ASF-code.zip: the Matlab scripts used to generate, run, and analyze the MITgcm simulations, and the scripts for making figures for the manuscript “Coastal freshening enhances eddy-driven heat transfer toward the Antarctic margins”. products_new.zip: the products calculated from MITgcm diagnostics. exps_configuration.zip: the configurations of the MITgcm simulations. data_WOA18_etopo.zip: the Matlab scripts to process hydrographic data (World Ocean Atlas 2018) and ocean bathymetric data (ETOPO1), and the corresponding products. The source code of the Massachusetts Institute of Technology General Circulation Model (MITgcm) is available at: http://mitgcm.org. All the raw data of the model output are available at: https://doi.org/10.15144/S47P49. Guidelines on reproducing MITgcm_ASF simulations: Start each simulation with a 20-year spin-up integration. Before running each simulation, you need to substitute &OBCS_PARM04 with &OBCS_PARM05 in the file input/ data.obcs , and substitute &EXF_NML_05 with &EXF_NML_OBCS in the file input/ data.exf . For very fresh continental shelves (e.g., shelf salinity = 33 psu), you need to start the simulation with a very small time step (e.g., 60s) for two months, and then transition to a larger time step. Initialize the production run from the corresponding spin-up run, using the Matlab script initialize.m in the folder MITgcm_ASF-csi/newexp. When using the LAYERS package, you need to substitute numperlist = 1 with numperlist = 2 in the file code/ DIAGNOSTICS_SIZE.h before running the simulations. Feel free to contact Yidongfang Si via [e-mail] if you have any questions. : This work is supported by the National Science Foundation, under award numbers OCE-1751386 and OPP-2023244, as well as awards OCE-2048590 and OPP-1643445. This work used the Extreme Science and Engineering Discovery Environment XSEDE, which is supported by the National Science Foundation grant number ACI-1548562. This work also used the Hoffman2 Cluster, which is supported by the IDRE Research Technology Group at UCLA. We thank the MITgcm team for their contribution to numerical modeling and for making their code available. Y. Si acknowledges the scholarship provided by China Scholarship Council that supports her study at UCLA.