DOI: 10.5281/zenodo.6904145
title: Heat transport across the Antarctic Slope Front controlled by cross-slope salinity gradients

description: <pre><strong>Please see the latest version: https://doi.org/10.5281/zenodo.7651177</strong> </pre> This release contains updates on analysis code and products. MITgcm_ASF-heat-ver2/newexp/: the Matlab scripts used to generate and run the MITgcm simulations MITgcm_ASF-heat-ver2/analysis/cross_slope/ and MITgcm_ASF-heat-ver2/analysis/plots/: the Matlab scripts used to analyze model output and make plots. exps_configuration.zip: the configurations of the MITgcm simulations. products_new-ver2.zip: the products calculated from MITgcm diagnostics, including 7-year means of all the model outputs, overturning streamfunctions, neutral density, shoreward heat transport, kinetic energy, temporal decomposition, etc. ThicknessFlux_FreshShelf.zip: products of isopycnal thickness flux, used to calculate the decomposition of eddy/tidal heat advection/diffusion, for the "fresh-shelf" simulation. ThicknessFlux_ref.zip: as above, but for the reference simulation. ThicknessFlux_DenseShelf.zip: as above, but for the "dense-shelf" simulation. 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. To reproduce MITgcm_ASF simulations: Start each simulation with a 20-year spin-up integration. Before running each simulation, you need to substitute <em>&OBCS_PARM04</em> with <em>&OBCS_PARM05 </em>in the file <em>input/data.obcs</em>, and substitute <em>&EXF_NML_05 </em>with <em>&EXF_NML_OBCS</em> <em> </em>in the file <em>input/data.exf</em>. For simulations with very fresh shelf waters (e.g., shelf salinity = 33 psu), you need to spin up the simulation with a very small time step (e.g., 60s) for ~ two months, and then use a larger time step. Initialize the production run from the corresponding spin-up run, using the Matlab script <em>initialize.m</em> in the folder<em> MITgcm_ASF-heat-ver2/newexp/. </em>When using the LAYERS package, you need to substitute<em> numperlist = 1</em> with <em>numperlist = 2 </em>in the file<em> code/DIAGNOSTICS_SIZE.h</em> before running the simulations. Notes on calculationg the overturning streamfunction and its mean/eddy/tidal decomposition using the MITgcm LAYERS package: avg_t: Calculate time averages. It has been modified since the vertical number of layers can be different from Nr. calc_Overturning_pt, usscar_plot_overturning_pt: calculate and plot eddy/mean/isopycnal overturning streamfunction using potential temperature layer fluxes. calc_Overturning_rho, usscar_plot_overturning_rho: calculate and plot eddy/mean/isopycnal overturning streamfunction using potential density layer fluxes. calc_Overturning_pt_Aocean, usscar_pt_overturning_rho_Aocean (recommended if your bathymetry is not flat): calculate and plot eddy/mean/isopycnal overturning streamfunction using <em>potential temperature</em> layer fluxes. For each latitude, use the total ocean area below a certain level to interpolate the streamfunction from pt space to z space. calc_Overturning_rho_Aocean, usscar_plot_overturning_rho_Aocean (recommended if your bathymetry is not flat): calculate and plot eddy/mean/isopycnal overturning streamfunction using <em>potential density</em> layer fluxes. For each latitude, use the total ocean area below a certain level to interpolate the streamfunction from potential density space to z space. calc_decomposition_OT, plot_OT_rho_Aocean_TidalEddyMean: decompose the isopycnal overturning streamfunction into tidal/eddy/mean components, using potential density layer fluxes. Feel free to contact Yidongfang Si via ysi@g.ucla.edu if you have any questions.
description: 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 China Scholarship Council.