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223 results for “model ice”
Code for GMD publication - Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018
<p>In this repository, we include the source codes for WRF microphysics parameterization used in the GMD publication "Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018."</p> <p>The four 2-moment bulk microphysical parameterization codes, WDM6, WDM7, Thompson, and Morrison, are divided into 3 WDM, Thompson, and Morrison codes, and each code has been modified so that detailed microphysical processes can be checked in wrfout.</p> <p>The WDM6 and WDM7 schemes include numerical errors for ice microphysical parameterization (Kim and lim, 2021) and for cloud evaporation and melting processes (Lei et al., 2020).</p> <p>Namelist files shows the namelist.input for each case.</p> <p> </p> <p> </p>
Sea Ice Rheology Experiment (SIREx) - Model output data
<p>Sea-ice model output analyzed in the Sea Ice Rheology Experiment (SIREx) Part I and Part II. </p> <p>There is one netCDF file per model, per year (1997 and/or 2008). Each netCDF file contains daily output (as means or instantaneous values -- as indicated in the name) for January-February-March of the given year. Please see below for more information on what is included and how to cite. </p> <p> </p> <p><strong>1. Naming convention of the files</strong></p> <p>"Model simulation label" + _ + "year" + _ + "daily_means" OR "instant" </p> <p> </p> <p><strong>2. Variables included</strong></p> <ul> <li><em>U,V</em> : sea-ice velocity in the x,y directions (in m/s);</li> <li><em>A</em>: ice concentration per grid cell (0 -- 1);</li> <li><em>h</em>: mean ice thickness per grid cell (in m);</li> <li>Grid spacing information: centered on u-points (<em>DXU, DYU</em>), v-points (<em>DXV, DYV</em>), or t-points (<em>DXT, DYT</em>) (in m); </li> <li>Grid point coordinates: for u-points (<em>ULON, ULAT</em>), v-points (<em>VLON, VLA</em>T), or t-points (<em>TLON, TLAT</em>) (in degrees); </li> <li><em>maskT</em>: land mask at t-points (0/1 = ocean/land);</li> <li><em>time</em>: time axis (in days since 1901-01-01 00:00:00).</li> </ul> <p> </p> <p><strong>3. Recommended citation usage</strong></p> <p>If <em>all</em> simulations included in the current archive are used in a future study, we ask to cite this archive and the SIREx papers (Bouchat et al., 2022, Hutter et al., 2022 ). If only <em>selected </em>simulations are used, we ask to cite both this archive and the reference paper(s) applying to the selected simulation(s) (as stated indicated in Table 1 of the SIREx papers).</p>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>7_experiments.zip contains modified model code and output data of each experiment in this study.</li> <li>off-line test.zip contains off-line test code and output data.</li> <li>plot_scripts.zip are the NCL scripts used for figures in the paper.</li> </ul>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>Figs&Table are the NCL scripts used for figures and table in the paper.</li> <li>Model_Results contains output data of each experiment in this study.</li> <li>Mods_Scripts contains modified model code.</li> <li>Offline_Code contains off-line test code.</li> </ul>
MITgcm model setup and output for "What determines the shape of the Pine-Island-like ice shelf?"
<p><strong>(Contents)</strong><br> Here it contains<br> <br> jim_run3 = CTRL (Similar to Jordan et al., 2018 but with smaller ocean)</p> <p>melt/run/ = IOCTRL, M(all)V(dyn)U(dyn)</p> <p>melt2/ = M( changing, see below ) V( dyn ) U( 0 )<br> melt2/run/ = M(all)V(dyn)U(0)<br> melt2/run2/ = M(20)V(dyn)U(0)<br> melt2/run3/ = M(GL10)V(dyn)U(0)<br> melt2/run4/ = M(GL20)V(dyn)U(0)</p> <p><br> melt3/ = M ( changing, see below ) V( changing ) U( 0 )<br> melt3/run5/ = M(all)V(2000)U(0)<br> melt3/run10/ = M(20)V(2000)U(0)</p> <p>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%<br> Input melt data for running ice only experiments<br> #data.streamice#<br> meltCTRL.bin = M(all) ... melt rate data of CTRL for every time steps <br> meltCTRL2.bin = M(GL10)<br> meltCTRL3.bin = M(20 m/a)<br> meltCTRL4.bin = M(GL20)</p> <p>Input velocity data for running ice only experiments <br> melt3/<br> uvel_ext4.bin = U(0 m/a)<br> vvel_ext5.bin = V(2000 m/a)</p> <p><strong>(How to compile and run)</strong><br> mkdir build<br> cd build/<br> module load intel/2021.2.0<br> module load impi/2021.2.0<br> export LANG=en_US.UTF-8<br> export LC_ALL=en_US.utf8<br> ../../../tools/genmake2 -of ../../../tools/build_options/linux_amd64_ifort+mpi_ice_nas_tokyo3 -mpi -mods ../code/<br> make depend<br> export LANG=en_US.UTF-8<br> export LC_ALL=en_US.utf8<br> make -j 16</p> <p> mkdir ../run<br> cd ../run/<br> cp ../build/mitgcmuv .<br> cp ../input/* .<br> pjsub job*.pbs<br> <br> <strong>Other important links</strong><br> https://github.com/hgu784/MITgcm_67s<br> <br> For more info please send an email to Yoshihiro.Nakayama@lowtem.hokudai.ac.jp</p>
Data for "Uncovering basal friction in northwest Greenland using an ice flow model and observations of the past decade"
<p>Data for the main figures for "Uncovering basal friction in northwest Greenland using an ice flow model and observations of the past decade"</p>
Data for figures in Model predictions of wave overwash extent into the marginal ice zone
<p>The data required to reproduce the figures in 'Model predictions of wave overwash extent into the marginal ice zone'.</p> <p>The data includes:</p> <ul> <li>Coefficient values produced by coupled floe-wave motions, required to determine overwash of a single floe and thus the overwash extent model.</li> <li>The data for the transects used to predict overwash in Figure 11 (Agulhas II), includes wave conditions and the ice concentration along the transect (other floe field properties remains constant).</li> </ul> <p>The code is uploaded at - </p> <pre>https://doi.org/10.5281/zenodo.7059554</pre>
Model data - Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions
<p>Model data for JGR paper : Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions</p>
Dataset for "Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model" by Kim et al., 2022 in Geophysical Research Letters
<p>Kiel Climate Model pre-industrial simulation data used in the Geophysical Research Letters publication titled “Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model” by Kim et al., 2022</p>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The code, scripts, and data used in the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>All Figures&Table and their corresponding NCL scripts are under the directory of Figs&Table. </li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The code, data, and NCL scripts used for the figures and table in the Appendix are under the directory of Appendix.</li> </ul>
geography/topography and ice sheet models
<p>geography/topography: topo.txt</p> <p>ice sheet: ice thickness distribution for every 25 m change in ESL (e.g. 0500.txt for 500 m change in ESL)</p> <p>5 minute grid</p>
Data for "Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison"
<p>All data recorded for reflectance and e-folding depth measurements associated with "Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison"</p>
Model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"
<p>This folder contains the model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"</p> <p>The code for plotting the figures is the notebook Plot_figures.ipynb</p> <p>Fig1/simulation_output/ : Model output necessary for plotting the first figure </p> <p>The last timestep of each simulation is provided. There is one file for 1D variables (ice volume, ice volume above flotation), and one file for 2D variables (ice sheet thickness for instance).</p> <ul> <li><span>melt_insoPI_output/ : melt branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>growth_insoPI_output/ : growth branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>melt_insoMAX_output/ : melt branch, maximum insolation. Results for different CO2 levels</span></li> <li><span>growth_insoMIN_output/ : growth branch, minimum insolation. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig1/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p>Fig2/simulation_output/ : Model output necessary for plotting the second figure </p> <p>The last timestep of each simulation is provided. </p> <ul> <li><span>melt_insoPI_enhancedmelt_albfb/ : melt branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_albfb/ : growth branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>melt_insoPI_enhancedmelt_fixedalb/ : melt branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_fixedalb/: growth branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig2/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p><span>Fig3/simulation_output/ : Model output necessary for plotting the third figure </span></p> <ul> <li><span>1xCO2_nocoupling/ : simulation with pre-industrial CO2 levels and insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_nocoupling/ : simulation with 8xpiCO2 (pre-industrial CO2) levels, pre-industrial insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_transient_albfb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model </span></li> <li><span>8xCO2_transient_fixedalb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model excluding the albedo-melt feedback</span></li> </ul> <p> </p>
Data for Modeling Snow on Sea Ice using Physics Guided Machine Learning
Open the record for dataset details and reuse information.
Scherrenberg et al. (2024) supplement (Climate of the past): Ice-sheet model code, and output of Northern Hemisphere ice-sheet evolution of the past 800 kyr
<p>Supplement to Scherrenberg et al. (2024), article in Climate of the Past.</p> <p>This data-set contains ice-sheet model (IMAU-ICE) code (see IMAU_ICE_Code.zip; see https://github.com/IMAU-paleo/IMAU-ICE/tree/main for the most recent version of the model), the model output and configuration files (see Data_output.zip), and scripts to create figures (see Scripts_and_Figures.zip).</p> <p>Please note that additional input fields are required to run IMAU-ICE and to produce the figures. See Scherrenberg et al., (2024) for more information or contact the corresponding author.</p> <p>Citation: M.D.W. Scherrenberg, C.J. Berends, R.S.W. van de Wal: Late Pleistocene glacial terminations accelerated by proglacial lakes, climate of the past, special issue "icy landscapes of the past", 2024</p>
Transient ice flow/damage model
<p>This archive contains the code and model outputs used to produce the manuscript "A tran-<br> sient coupled ice ow-damage model to simulate iceberg calving from tidewater outlet glaciers"<br> submitted to the Journal of Advances of the Modeling of the Earth System</p>
Snow particle number, aerosol concentration and 10 meter windspeed data from MOSAiC, N-ICE, Weddel Sea expeditions and chemistry transport model data (p-TOMCAT) .
<p>The folder contains data for the MOSAiC, N-ICE and Weddell sea expedition for Snow particle counter measurements. Coarse aerosol measurements from the MOSAiC expedition are also included. Simulation data from a chemistry transport model (p-TOMCAT) is also available. This version includes both .mat and .nc files</p>
Simulation output of the reference setup in "The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses"
<p>This supplementary material for "The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses" contains the simulation output of the 20 reference runs. Additional data is available upon request from the corresponding author.</p>
Graph neural network emulator for modeling of ice dynamics and calving in the Pine Island Glacier, Antarctica
<p>These files include the following codes and datasets for developing graph neural network (GNN) emulators for the Ice-sheet and Sea-level System Model (ISSM) for modeling ice sheet dynamics and calving in the Pine Island Glacier, Antarctica</p> <ul> <li>ISSM_DGL_PIG2.py: Python file for training GNN models (*single.py: code for single GPU environment)</li> <li>ISSM_CNN_PIG.py: Python file for training convolutional neural network (CNN) models</li> <li>*.mat: Datasets of the ISSM transient simulation results (graphs for GNNs)</li> <li>*.pkl: Datasets of the ISSM transient simulation results (grids for CNNs)</li> </ul>
Active Regions of Secondary Ice Production in a Modeled Tropical Mesoscale Convective System
<p>The animations of the modeled tropical mesoscale convective system (MCS). The red regions indicate the cloud regions with the secondary ice production rate dNice/dt >10<sup>5</sup> m<sup>-3</sup> s<sup>-1</sup>. The numerical simulation of the MCS was performed with the help of the Environment and Climate Change Canada's (ECCC) Global Environmental Multiscale (GEM) model.</p> <p>For details see Korolev, A., Z. Qu, J. Milbrandt, I. Heckman, M. Cholette, M. Wolde, C. Nguyen, G. M. McFarquhar, P. Lawson, and A. M. Fridlind: High ice water content in tropical mesoscale convective systems (a conceptual model). Atmos. Chem. Phys., 2024.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.