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64 results for “MITgcm”
MITgcm Dataset for paper: Sensitivity analysis of a data-driven model of ocean temperature
<p>MITgcm dataset used in paper, Sensitivity analysis of a data-driven model of ocean temperature, made available here. The dataset comes from running a sector config of the MITgcm model, briefly described in the paper. This dataset is used to train the regression model described in the paper.</p> <p>Updated to include ncra_cat_tave.nc file which was accidentally missed on first version.</p>
MITgcm simulations of sea level response to freshwater injected at the surface and at depth in southern high latitudes: Model output and analysis code
<p>Model output (netcdf) and python code (included in both py and ipynb formats) to create the figures in Eisenman et al. (2024).</p> <div> <p>See https://eisenman-group.github.io for further details.</p> </div>
West Antarctic Peninsula (WAP) MITgcm-REcoMv2 outputs for 1991 (T, S, DIC, TA, DIN, Chl, air-sea CO2 flux)
<p>This dataset contains the netCDF files for the year 1991 of dissolved inorganic nitrogen (DIN), dissolved inorganic carbo (DIC), total alkalinity (TA), diatom chlorophyll concentration (DiaPhyto), small phytoplankton chlorophyll (SmPhyto), air-sea CO<sub>2</sub> fluxes (CO2flx), ocean temperature (Temp) and salinity (Salt) for the MITgcm-REcoMv2 ocean circulation and biogeochemistry model implemented for the West Antarctic Peninsula. Latitude and longitude for all variables are contained in the grid.glob.nc file.</p> <p>Files names start with the variable name, followed by the month and year. They are saved either as monthly means, as 10 day means, or 5 day means.</p> <p>The units for each variable are as follows:</p> <p>DIN: mmol/m<sup>3</sup></p> <p>DIC: mmol/m<sup>3</sup></p> <p>TA: mmol/m<sup>3</sup></p> <p>DiaPhyto: mg/m<sup>3</sup></p> <p>SmPhyto: mg/m<sup>3</sup></p> <p>CO2flx: mmol/s</p> <p>Temp: ˚C</p> <p>Results from this simulation are published in:</p> <p><strong><span>SCHULTZ, C., </span></strong><span>DONEY, S.C., ZHANG, W.G., REGAN, H.C., HOLLAND, P., MEREDITH, M., STAMMERJOHN, S.</span><strong><span> </span></strong><span>Modeling of the Influence of Sea Ice Cycle and Langmuir Circulation on the Upper Ocean Mixed Layer Depth and Freshwater distribution at the West Antarctic Peninsula. Journal of Geophysics Research Oceans, 125, 8, 2020. doi:10.1029/2020JC016109</span></p> <p><strong><span>SCHULTZ, C., </span></strong><span>DONEY, S.C., HAUCK, J., KAVANAUGH, M.T., SCHOFIELD, O.</span><strong><span> </span></strong><span>Modeling Phytoplankton Blooms and Inorganic Carbon Responses to Sea-Ice Variability in the West Antarctic Peninsula. Journal of Geophysical Research Biogeosciences, 126, 4, 2021. doi: 10.1029/2020JG006227</span></p> <p> </p>
Five day averaged sea surface salinity from MITgcm integration with climatological river discharge forcing
<p>The 5-day averaged sea surface salinity for experiment using climate river discharge, with file names like sss_clmflux_YEAR.mat for each year</p>
Five day averaged sea surface height from MITgcm integration with climatological river discharge forcing
<p>The 5-day averaged sea surface height for experiment using climate river discharge, with file names like ssh_dayflux_YEAR.mat for each year.</p>
Five day averaged sea surface salinity from MITgcm integration with daily river discharge forcing
<p>The 5-day averaged sea surface salinity (SSS) for experiment using daily river discharge, with file names like sss_dayflux_YEAR.mat for each year (1992-2017)</p>
Five day averaged sea surface height from MITgcm integration with daily river discharge forcing
<p>The 5-day averaged sea surface height (SSH) for experiment using daily discharge, with file names like ssh_dayflux_YEAR.mat for each year</p>
MITgcm model setup and output for "Impact of subglacial freshwater discharge on Pine Island Ice Shelf"
<p>Here, it contains the results of the regional PIG simulation. Model grid is lat-lon similar to Nakayama et al., 2019 roughly 200 m in the region. See Nakayama et al., submitted to GRL for detail. </p> <p>For complete model output (10*Qsg and 50*Qsg cases), please access NASA data (Registration is required).<br> https://ecco.jpl.nasa.gov/drive/files/ECCO2/High_res_PIG/PIG_only_200m </p> <p>Contents can be downloaded easily using wget (see link below). <br> https://ecco-group.org/docs/wget_download_multiple_files_and_directories.pdf</p> <p><strong>(Contents)</strong><br> code.zip (code to run this simulation)<br> input.zip (input file required for this simulation)<br> latlon_run23.zip (CTRL)<br> latlon_run24.zip (Qsg case)<br> latlon_run25.zip (2*Qsg case)<br> <br> <strong>(How to build and run)</strong><br> mkdir build<br> ./../../tools/genmake2 -of ../../../tools/build_options/linux_amd64_ifort+mpi_ice_nas -mpi -mods ../code/<br> make depend<br> make -j 16<br> cd ..</p> <p>mkdir test<br> cd test<br> ln -sf ../input/* .<br> ln -sf /nobackup/hzhang1/forcing/era_xx_it50/ .<br> cp ../build/mitgcm_uv .<br> qsub latlon_run23.sh</p>
Arctic cubed sphere configuration of MITgcm with 2-km resolution
<p>This repository includes a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm,<a href="https://doi.org/10.1029/96JC02775">Marshall et al., 1997</a>; <a href="http://mitgcm.org/public/docs.html">MITgcm Group, 2017</a>) with a horizontal resolution of 2 km, which is described in <a href="https://doi.org/10.5194/tc-14-93-2020">Hutter & Losch (2020)</a>. It is based on a regional Arctic configuration (<a href="https://doi.org/10.1175/JPO-D-11-040.1">Nguyen et al., 2012</a>) of the MITgcm, which represents the Northern face of a global cubed sphere configuration. The number of vertical layers is reduced to 16, with the first 5 layers covering the uppermost 120 m to decrease the computational cost associated with the ocean model component. The Refined Topography dataset 2 (RTopo-2) (<a href="https://doi.org/10.1594/PANGAEA.856844">Schaffer and Timmermann, 2016</a>) is used as bathymetry for the entire model domain. The lateral boundary conditions are taken from the globally optimized ECCO-2 simulations (Menemenlis et al., 2008). The configuration is designed to use the 3-hourly Japanese 55-year Reanalysis (JRA-55, <a href="https://doi.org/10.2151/jmsj.2015-001">Kobayashi et al., 2015</a>) with a spatial resolution of 0.5625° for surface boundary conditions. The ocean temperature and salinity are initialized on 1 January, 1992, from the World Ocean Atlas 2005 (Locarnini et al., 2006; Antonov et al., 2006). The initial conditions for sea ice are taken from the Polar Science Center (<a href="http://doi.org/10.1029/2001JC001041">Zhang et al., 2003</a>). Ocean and sea ice parameterizations and parameters are directly taken from <a href="https://doi.org/10.1029/2010JC006573">Nguyen et al. (2011)</a>, with the ice strength P=2.264×104Nm−2. The configuration uses the classical discrimination of two ice classes: thin and thick ice (<a href="https://doi.org/10.1175/1520-0485(1979)009%3C0815:ADTSIM%3E2.0.CO;2">Hibler, 1979</a>). The momentum equations are solved by an iterative method and line successive relaxation (LSR) of the linearized equations following <a href="https://doi.org/10.1029/96JC03744">Zhang and Hibler (1997)</a>. In each time step (<span class="math-tex">\(\Delta\)</span>t=120 s), 10 nonlinear steps are made and the linear problem is iterated until an accuracy of 10e−5 is reached or 500 iterations are performed. With this configuration, simulations were run from 1 January 1992 to 31 December 2012. We also provide pickup files to restart the simulation in 2012.</p> <p>To reference this configuration please use the citation of this repository and reference to the paper describing the configuration:</p> <p>Hutter, N. and Losch, M.: Feature-based comparison of sea ice deformation in lead-permitting sea ice simulations, The Cryosphere, 14, 93–113, <a href="https://doi.org/10.5194/tc-14-93-2020">https://doi.org/10.5194/tc-14-93-2020</a>, 2020.</p>
Sermilik Fjord, MITgcm simulations, Sanchez et al.
<p>Two numerical models of Sermilik Fjord analyzed by <a href="https://doi.org/10.1029/2023JC020492">Sanchez et al. (2024, <em>J. Geophys. Res. Oceans</em>)</a>.</p> <p>For file size reasons, this archive contains a subset of the full model output. Here, outputs are daily and only contain the part of the domain north of 65.4°N (i.e., the part containing the fjord).</p> <p>As is self-evident from the file names, each file contains one month of output, starting with March 2015 and ending with December 2017.</p> <p>As in Sanchez et al., the two simulations are named</p> <ul> <li>NG: no glacier and no subglacial discharge plume</li> <li>WG: with glacier and subglacial discharge plume</li> </ul>
MITgcm simulations to study ENSO in warmer climates
Open the record for dataset details and reuse information.
Inputs to an Arctic configuration based on MITgcm and model results
<p>This dataset contains input files for model runs used in Leng et al, JGR, 2020, "Origin and Fate of the Chukchi Slope Current Using a Numerical Model and In-situ Data". The model used in this study is an Arctic configuration based on the Massachusetts Institute of Technology general circulation model (MITgcm). Original source code is the MITgcm_c66m. The simulation covers six years from January 2010 to December 2015. Some representative output is also included.</p> <p>code: contains subroutines modified from the original MITgcm codes to accommodate the Arctic configuration and tracer setup.</p> <p>data: representative data to form the figures in the paper.</p> <p>forcing_2010: surface forcing for 2010 from JRA-55.</p> <p>forcing_2011: surface forcing for 2011 from JRA-55.</p> <p>forcing_2012: surface forcing for 2012 from JRA-55.</p> <p>forcing_2013: surface forcing for 2013 from JRA-55.</p> <p>forcing_2014: surface forcing for 2014 from JRA-55.</p> <p>forcing_2015: surface forcing for 2015 from JRA-55.</p> <p>input: contains input parameters and initial/boundary conditions.</p> <p>script: contains scripts to compile the executable code, need to be modified for local computer libraries, etc.</p>
Inputs to an idealized numerical model based on MITgcm and model results
<p>This dataset contains input files for model runs used in Leng et al. 2021, "Temporal Evolution of a Geostrophic Current under Sea Ice: Analytical and Numerical Solutions" (to be submitted to JPO). The model used in this study is an idealized channel configuration based on the Massachusetts Institute of Technology general circulation model (MITgcm). Original source code is the MITgcm_c66m. Some representative output is also included.</p> <p>code: contains code configuration.</p> <p>input: contains parameters, initial conditions, forcing, etc.</p> <p>output: contains model output.</p>
MITgcm model setup and output for "Modeling ocean circulation in the Bellingshausen Sea"
<p>MITgcm model setup and output for "Modeling ocean circulation in the Bellingshausen Sea".</p> <p>Here, it contains the results of the Amundsen and the Bellingshausen Sea from 1992 to 2020. </p> <p><Changes from run260 to this model><br> This is improved version of run260 with 70 vertical layers. <br> To adjust melt rate of the George VI ices shelf, we change the values of heat transfer coefficient γT similar to run260.</p> <p>This experiment was conducted in two separate sessions due to changes in timestep (150 -> 120).<br> We can refer to input/data.diagnostics for the details of the model output name.<br> Outputs are the monthly mean.</p> <p><br> <strong>(Contents)</strong></p> <p>ABSmodel_1992_2009_code.tar.gz (code to run this simulation between 1992 and 2009)</p> <p>ABSmodel_2010_2020_code.tar.gz (code to run this simulation between 2010 and 2020)</p> <p>ABSmodel_1992_2009_input.tar.gz (input file required for this simulation between 1992 and 2009)</p> <p>ABSmodel_2010_2020_input.tar.gz (input file required for this simulation between 1992 and 2009)</p> <p>ABSmodel_1992_2009_results.tar.gz</p> <p>ABSmodel_2010_2020_results.tar.gz</p> <p>(due to size limit of 50GB, please check https://ecco.jpl.nasa.gov/drive/files/ECCO2/LLC1080_REG_AMS/Hyogo_et_al_2022 for complete model output. Complete datasets can also be obtained by rerunning the simulation.)</p> <p><strong>(How to build and run)</strong><br> mkdir build<br> ./../../tools/genmake2 -of ../../../tools/build_options/linux_amd64_ifort+mpi_ice_nas_tokyo3 -mpi -mods ../code/<br> make depend<br> make -j 16<br> cd ..</p> <p>mkdir test<br> cd test<br> ln -sf ../input/* .<br> ln -sf /forcing/era_xx/ .<br> cp ../build/mitgcmuv .<br> qsub run_omp_high_t1.pbs</p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-2)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/. <br><br></p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-3)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/. </p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-5)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/. <br><br></p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-8)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/ (recommended). </p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-7)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/ (recommended). </p>
SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" (Part 2-1)
<p>SOSE output analyzed in "Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean" submitted to GMD. Complete theta data is 174GB. Thus, this dataset is separated into smaller files. These data can be accessed by accessing Zenode links (see below) or downloading from http://sose.ucsd.edu/ (recommended). <br><br>#2 https://zenodo.org/records/13117976<br>#3 https://zenodo.org/records/13118797<br>#4 https://zenodo.org/records/13118949<br>#5 https://zenodo.org/records/13119899<br>#6 https://zenodo.org/records/13119952<br>#7 https://zenodo.org/records/13121012<br>#8 https://zenodo.org/records/13121700<br>#9 https://zenodo.org/records/13123458</p> <p> </p>
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