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223 results for “model ice”
Load, pressure, rubble pile geometry and video data from model-scale tests on shallow water ice-structure interaction
<p>The data is obtained from model-scale experiments on shallow water ice-structure interaction. During the conducted experiments, a ten-meter wide initially intact ice sheet was pushed against a sloping structure of the same width. As the ice failed against the structure, a grounded rubble pile accumulated in front of it. The structure consisted of ten identical one-meter-wide segments and the horizontal load on each of these segments was measured independently with load cells. These measurements are presented as load-time datasets. The horizontal load acting on the false bottom was measured with load cells and are also presented as load-time datasets. Furthermore, the ice pressure on two of the segments was measured with tactile sensors. These pressure measurements are presented as array-based pressure-time datasets. Video footage filmed from two different video angles is included in the data. In addition, the coordinates of the rubble pile geometries at the end of each experiment are published. The data includes the top and side rubble pile geometries. In total, seven experiments were conducted. The data can be used by researchers, engineers and designers who work with ice structure interaction related issues in order to, for instance, optimize the design of offshore structures, improve ice load predictions or develop future experiments and simulations. A full description of the experimental set-up and the published data is submitted to the journal Data in Brief. </p>
Research data supporting "Ephemeral Ice-Like Local Environments in Classical Rigid Models of Liquid Water"
<p>This repository contains the set of data shown in the paper <strong>"</strong><em>Ephemeral Ice-Like Local Environments in Classical Rigid Models of Liquid Water</em>", published on the Journal of Chemical Physics (DOI:10.1063/5.0088599).</p>
Postprocessed trajectory output for ice cloud microphysics - ICON and CLaMS-Ice models
<p>Postprocessed output from a trajectory module implemented in ICON v 2.3.0. The trajectories track density, temperature, pressure, specific humidity, cloud ice mass and number mixing ratios, cloud liquid mass and number mixing ratios, graupel mass and number mixing ratios, and ice sedimentation mass and number mixing ratios both into and out of the parcel. They are initiated over the Sichuan basin and allowed to flow for 51 hours westward during which the cross India into the Arabian Sea. This trajectory output is also used to run an offline microphysics box model, CLaMS-Ice. qih-Nih* files contain histograms of ice mass mixing ratio (qi) and ice crystal number concentration (Ni); het-hom-pre* files contain process tendencies from heterogeneous nucleation, homogeneous nucleation, and preexisting ice in CLaMS-Ice; qippmvNi-TRHi* files contain qi and Ni versus a range of cirrus temperatures and a range of supersaturations with respect to ice; qi_ppmv_abs* and Ni_abs* files contain probability distributions of qi and Ni differences over absolute time; and qi_ppmv_norm* and Ni_norm* files contain probability distributions of qi and Ni differences over normalized time. Suffixes in all cases indicate the cloud microphysical setup that the trajectory values were used to run with 1M = one-moment scheme, 2M = two-moment scheme, Tf = temperature fluctuation parameterization in CLaMS-Ice simulations, and noSHflux = no pseudo-mixing tendency included in CLaMS-Ice simulations.</p>
Data set of 1D model runs, CTRL and ICE runs, associated with "Underestimation of oceanic carbon uptake in the Arctic Ocean: Ice melt as predictor of the sea ice carbon pump"
<p>Dataset of one-dimensional runs for investigation on the sea ice carbon pump. Associated with Sect. 3.1 and 4.1 of manuscript "Underestimation of oceanic carbon uptake in the Arctic Ocean: Ice melt as predictor of the sea ice carbon pump".</p>
Data and code availibility for the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al.
<p>The data and codes used in the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al., published in <em>Science Advances</em> are included in this collection. Detailed descriptions of the files are given in the readme file.</p>
Glacial ice sheet extent effects on tidal mixing and the global overturning circulation - Model Output
<p>This dataset contains the output from the tide model and climate model simulations from the publication Wilmes et al. (2018) "Glacial ice sheet extent effects on tidal mixing and the global overturning circulation" submitted to Paleoceanography. The user is referred to the paper for details on the methodology.</p> <p>Dissipation files:</p> <p>Files beginning with "diss" contain tidal dissipation files calculated from the OTIS tide model output at 1/8th deg using the direct method. Files with the M2 constituent only are in .mat format and extend from 86deg S to 89deg N whereas the files containing all constituents (M2, S2, K1 and O1) are in netcdf format and extend from 90deg S to 90deg N. These files regridded and are used as the climate model tidal forcing.</p> <p>Dissipation file list:</p> <p>diss_dir_ze_1_8_rtp_21kyrBP_i6g_-I1.5_-t_8299008.nc Dissipation for LGM ICE-6G ZE ITdrag 1/8th deg<br> diss_dir_ze_1_8_rtp_21kyrBP_i5g_-I1.5_-t_8299031.nc Dissipation for LGM ICE-5G ZE ITdrag 1/8th deg<br> diss_dir_ze_1_8_rtp_00kyrBP_-I1.5_pdsal_8299034.nc Dissipation for PD ZE ITdrag 1/8th deg</p> <p>diss_dir_js_1_8_rtop_21kyrBP_i6g_-t_-I6.0_7673000.nc Dissipation for LGM ICE-6G JS ITdrag 1/8th deg<br> diss_dir_js_1_8_rtop_21kyrBP_i5g_-t_-I6.0_7672999.nc Dissipation for LGM ICE-5G JS ITdrag 1/8th deg<br> diss_dir_js_1_8_rtop_00kyrBP_-I6.0_7672998.nc Dissipation for PD JS ITdrag 1/8th deg</p> <p>diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk5_NH_lmsk_-I1.5_8299652.mat M2 dissipation for LGM ICE-5G blk1 + NH ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk5_-I1.5_8299534.mat M2 dissipation for LGM ICE-5G blk5 ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk4_-I1.5_8299533.mat M2 dissipation for LGM ICE-5G blk4 ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk3_-I1.5_8299531.mat M2 dissipation for LGM ICE-5G blk3 ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk2_-I1.5_8299530.mat M2 dissipation for LGM ICE-5G blk2 ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk1_-I1.5_8299529.mat M2 dissipation for LGM ICE-5G blk1 ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_140mSLD_i6g_lmsk_-I1.5_8299543.mat M2 dissipation for PD 140mSLD ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_140mSLD_i5g_lmsk_-I1.5_8299542.mat M2 dissipation for PD 140mSLD ICE-5G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_130mSLD_i6g_lmsk_-I1.5_8299544.mat M2 dissipation for PD 130mSLD ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_130mSLD_i5g_lmsk_-I1.5_8299541.mat M2 dissipation for PD 130mSLD ICE-5G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_i6g_lmsk_-I1.5_8299545.mat M2 dissipation for PD 120mSLD ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_i5g_lmsk_-I1.5_8299540.mat M2 dissipation for PD 120mSLD ICE-5G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_110mSLD_i6g_lmsk_-I1.5_8299546.mat M2 dissipation for PD 110mSLD ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_110mSLD_i5g_lmsk_-I1.5_8299539.mat M2 dissipation for PD 110mSLD ICE-5G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_100mSLD_i6g_lmsk_-I1.5_8299547.mat M2 dissipation for PD 100mSLD ICE-6G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_100mSLD_i5g_lmsk_-I1.5_8299538.mat M2 dissipation for PD 100mSLD ICE-5G land mask ZE ITdrag 1/8th deg<br> diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_-I1.5_8299537.mat M2 dissipation for PD 120mSLD JS ITdrag 1/8th deg</p> <p> </p> <p>Climate model output:</p> <p>UVic climate model output for all simulations in the paper has been compressed using tar and zip. Each folder contains the output yearly averages (tavg.xxx.nc) which have been used in the results section of the paper. The model input files are located in /data. The tidal input file is in /data/O_tideenrg_green.nc. Furthermore included are restart files (rest.xxx.nc), model code in /code, and the model exectuables.</p> <p>Climate mode output list:</p> <p>preind_tidal_ze_00kyr_rtop_-1.5_8299034_dir.tgz Output from PIC<br> lgm_tidal_ze_21kyr_i6g_rtop_-1.5_8299008_dir_tau_lgm.tgz Output from LGM_i6gT_lgmW<br> lgm_tidal_ze_21kyr_i6g_rtop_-1.5_8299008_dir.tgz Output from LGM_i6gT_pdW<br> lgm_tidal_ze_21kyr_i5g_rtop_-1.5_8299031_dir_tau_lgm.tgz Output from LGM_i5gT_lgmW<br> lgm_tidal_ze_21kyr_i5g_rtop_-1.5_8299031_dir.tgz Output from LGM_i5gT_pdW<br> lgm_tidal_ze_00kyr_rtop_-1.5_8299034_dir_tau_lgm.tgz Output from LGM_pdT_lgmW<br> lgm_tidal_ze_00kyr_rtop_-1.5_8299034_dir.tgz Output from LGM_pdT_pdW</p> <p>preind_tidal_js_1_2_rtp_00kyrBP_-I1.0_7881173.tgz Output from PIC_1_2_rtp82<br> preind_js_1_2_SandS8.2_00kyrBP_82SNcb_-I1.0_8317333_dir.tgz Output from PIC_1_2_SS82<br> lgm_tidal_js_1_2_SandS8.2_00kyrBP_120mSLD_82SNcb_-t_-I1.0_8317331_dir.tgz Output from LGM_1_2_SS82_sldT<br> lgm_tidal_js_1_2_SandS8.2_00kyrBP_82SNcb_-I1.0_8317333_dir.tgz Output from LGM_1_2_SS82_pdT<br> lgm_tidal_js_1_2_rtop_00kyrBP_120mSLD_82SN_-t_-I1.0_8315693.tgz Output from LGM_1_2_rtp82_sldT<br> lgm_tidal_js_1_2_rtop_00kyrBP_82SN_pdsal_-I1.0_8315702.tgz Output from LGM_1_2_rtp82_pdT<br> <br> </p> <p> </p> <p> </p>
Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"
<div> <div> <div>This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the paper titled "Unraveling Secondary Ice Production in Winter Orographic Clouds through a Synergy of In-Situ Observations, Remote Sensing, and Modeling." The in-situ and remote sensing measurements were conducted at Mount Helmos in Peloponnese as part of the CALISHTO campaign (https://calishto.panacea-ri.gr/).</div> </div> </div> <div>Preprint accessible at: https://doi.org/10.21203/rs.3.rs-3502790/v1</div>
Model output: CICE6-WIM Antarctic sea ice data (2010--2019)
<p>CICE6 model with waves-in-ice module (WIM) output analysed with k-means clustering to identify the Antarctic marginal ice zone. Daily data at a 1-degree horizontal resolution of the variables used to inform k-means and the physical processes which drive the Antarctic marginal ice zone are included. The model was spun-up over 2005–2009 and outputs were analysed over 2010–2019.</p> <p> </p> <p>For further details, see </p> <p>Day, N. S., Bennetts. L. G., O'Farrell, S. P., Alberello, A., & Montiel, F. (2023) Analysis of the Antarctic Marginal Ice Zone Based on Unsupervised Classification of Standalone Sea Ice Model Data.</p> <p> </p> <p>Data files:</p> <ul> <li><code>iceh_{year}.nc</code>: gridded NetCDF files containing the training variables for k-mean clustering and the fitted clusters.</li> <li><code>forcing_variables_2010_2019.csv</code>: flat file containing variables of CICE6-WIM forcing and sea ice dynamics.</li> <li><code>fsd_processes_2010_2019.csv</code>: flat file containing each term of the prognostic floe size distribution model in CICE6.</li> </ul> <p> </p> <p>Scripts:</p> <ul> <li><code>ice_in</code>: CICE namelist</li> <li>Waves-in-Ice Module: <ul> <li><code>ice_floe.F90</code>: Appends the WIM to CICE6</li> <li><code>m_prams_waveice.F90</code>: wave-ice parameters</li> <li><code>m_waveattn.F90</code>: wave attenuation from sea ice</li> <li><code>m_fzero.F90</code>: useful mathematical functions and solvers</li> <li><code>m_waveice.F90</code>: wave-ice physics</li> </ul> </li> </ul> <p>To implement the WIM into CICE6, subroutines within ice_floe.F90 should be called prior calling the floe size distribution subroutines in ice_step_mod.F90. For further details/assistance in implementing the WIM please contact Noah Day (<code>noah.day@adelaide.edu.au</code>).</p>
S-chains adsorbed onto amorphous water ice models
<p>This Supporting Material contains:</p> <ul> <li>The fractional coordinates of DFT optimized adsorption complexes for crystalline and amorphous periodic ice models in <a href="https://www.moldraw.unito.it/_sgg/m1m1s43_1.htm">.mol</a> format, editable with <a href="http://www.moldraw.unito.it/">MOLDRAW</a>, using <a href="http://www.crystal.unito.it/">CRYSTAL17</a> computer code;</li> <li>The images of Raman and IR spectra computed for gas phase and adsorbed S-chains. </li> <li>The frequencies and their intensities computed for each species in gas phase, adsorbed in the cavity region and on the flat region. </li> </ul>
Modeling the impacts of Antarctic Sea Ice Decline: Responses of Atmospheric Dynamics
Open the record for dataset details and reuse information.
Graph neural network emulator for modeling of ice dynamics and calving in the Helheim Glacier, Greenland
<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 Helheim Glacier, Greenland.</p> <ul> <li>ISSM_DGL_Helheim.py: Python file for training GNN models</li> <li>ISSM_CNN_Helheim.py: Python file for training convolutional neural network (CNN) models</li> <li>*.mat: Datasets of the ISSM transient simulation results</li> </ul>
Model data for probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under high ice-shelf basal melt conditions
<p>Model data for probabilistic projections of the Amery Ice Shelf catchment, <br>Antarctica, under high ice-shelf basal melt conditions<br>======================================================================</p> <p>This archive contains ice-sheet model output and statistical models <br>used in the manuscript:<br>"Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under<br>high ice-shelf basal melt conditions" by:<br>Sanket Jantre, Matthew Hoffman, Nathan M. Urban, Trevor Hillebrand, Mauro<br>Perego, Stephen Price, John D. Jakeman</p> <p>OVERVIEW<br>--------</p> <p>Statistical models and corresponding datasets are archived in the file<br>Amery_UQ_Study_Statistical_Models.zip. That file contains a README that<br>describes its contents.<br>Contact for statistical models:<br>Sanket Jantre, Brookhaven National Laboratory, sjantre@bnl.gov</p> <p>The remaining files in this archive contain output from ice-sheet model <br>simulations using the MPAS-Albany Land Ice (MALI) model <br>(Hoffman et al. 2018, https://github.com/MALI-Dev/E3SM)<br>applied to a regional domain of the Amery Ice Shelf catchment<br>of Antarctica with mesh resolution varying from 4 to 20 km.<br>The contents of these files are described below.<br>Contact for MALI simulations:<br>Matthew Hoffman, Los Alamos National Laboratory, mhoffman@lanl.gov</p> <p>ENSEMBLES<br>---------</p> <p>The ensembles consist of all or a subset of 200 model runs with values for 6<br>parameters sampled from a Sobol' sequence over a specified range.</p> <p>Parameters and Sampled Ranges:<br>1. Ice stiffness scaling factor, Cφ: (0.8, 1.2)<br>2. Basal friction scaling factor, Cμ: (0.8, 1.2)<br>3. Basal slip exponent, q: (0.1, 0.333)<br>4. Calving yield stress, σmax: (80, 180) kPa<br>5. Ice-shelf melt coefficient, γ0: (9620, 471000) m yr−1<br>6. Ice-shelf basal melt rate, m: (12, 58) Gt yr−1</p> <p>SCENARIOS<br>---------</p> <p>The archive contains output from 4 scenarios described in the manuscript:</p> <p>Historical relaxation (RELX): For each ensemble member, we conducted a 50 year<br>relaxation from the initial condition using historical climate forcing to<br>integrate out fast transient behavior. For surface mass balance, we applied a<br>1995–2017 climatological average from RACMO2.3p1 (Van Wessem et al., 2014; van<br>den Broeke, 2019). The ocean thermal forcing was the observation-based<br>climatology compiled for ISMIP6-Antarctica, which uses data from 1995–2018<br>(Jourdain et al., 2020; Nowicki et al., 2020). The 50 year relaxation duration<br>was chosen as the most rapid adjustments occur in the first few decades of<br>integration, while the long term adjustment to a fully steady state takes<br>thousands of years. Relaxation to full steady state would require<br>substantially more computing resources than our entire set of ensembles and<br>also leads to the complication of different runs having potentially very<br>different initial states. Future improvements to model initialization that<br>account for surface elevation change (Perego et al., 2014) may reduce model<br>drift and adjust this requirement. The final model state in each run at the<br>end of RELX was given the nominal date of January 1, 2015, and all three<br>projection ensembles were branched from these states.</p> <p>Control projection (CTRL): The CTRL projection ensemble were an extension of<br>the RELX configurations, continuing the same surface mass balance and ocean<br>thermal forcing from January 1, 2015, to January 1, 2300. This ensemble was<br>used to assess model drift relative to the forced response of the climate<br>scenarios. </p> <p>SSP1-2.6 projection (SSP1): Our SSP1 projection used annual surface mass<br>balance and ocean thermal forcing derived from a UKESM SSP1-2.6 climate<br>scenario (expAE10 from Seroussi et al., 2024). Surface mass balance and ocean<br>thermal forcing were applied as anomalies relative to the climatological mean<br>forcings in RELX/CTRL to avoid issues related to climate model bias and abrupt<br>changes in forcing. This ensemble was also run from January 1, 2015, to<br>January 1, 2300.</p> <p>SSP5-8.5 projection (SSP5) Our SSP5 projection used the UKESM SSP5-8.5<br>projection forcings (expAE05 from Seroussi et al., 2024), again applied as<br>anomalies and from 2015 to 2300.</p> <p><br>OUTPUT<br>------</p> <p>Each ensemble directory contains at the base level:<br>* branch_ensemble.cfg - configuration file for the ensemble_generator test<br> case (https://mpas-dev.github.io/compass/latest/users_guide/landice/test_groups/ensemble_generator.html) <br> of COMPASS (Configuration Of Model for Prediction Across Scales Setups, https://github.com/MPAS-Dev/compass)<br> used to set up the ensemble.<br>* mesh_vars.nc - netCDF file containing the mesh variables. This file is the<br> same for all ensembles. These fields need to be appended to an output file to<br> visualize in, e.g., Paraview. This can be done with the command:<br> ncks -A mesh_vars.nc output.nc</p> <p>Each ensemble contains subdirectories for each run numbered 000-199. Each run<br>directory contains the files:<br>* globalStats.nc - scalar metrics at every time step<br>* output.nc - spatial fields at 10 year intervals<br>* run_info.cfg - summary of parameter values</p> <p>Notes:<br>* The SSP1 and SSP5 ensembles contain a subset of the full 200 runs<br> because some runs were filtered out as being unnecessary during model<br> calibration (see manuscript).<br>* The RELX ensemble is run for 50 years with an arbitrary start year of 2000.<br> The CTRL, SSP1, and SSP5 ensembles are started in 2015 from the final state<br> of the corresponding RELX run (nominally 2050). Because spatial data has<br> been saved in this archive at 10 year intervals, the first output for the<br> three projection ensembles is 2020. To get the initial condition for the<br> projection ensembles, use the 2050 state from RELX for the corresponding<br> model run.<br>* Spatial field output at 1 year intervals, as well as run input, log, and<br> restart files are available from the corresponding contact. The complete<br> run data is about 2 TB.</p> <p><br>CITATION<br>--------<br>If you find these data useful, please cite the DOI for this <br>archive (10.5281/zenodo.11166628), as well as our manuscript<br>submitted to The Cryosphere.</p> <p>This archive is approved by Los Alamos National Laboratory<br>for public release under LA-UR-24-24969; distribution is unlimited.</p> <p> </p> <p>REFERENCES<br>----------</p> <p>Hoffman, M. J., Perego, M., Price, S. F., Lipscomb, W. H., Zhang, T.,<br>Jacobsen, D., Tezaur, I., Salinger, A. G., Tuminaro, R., and Bertagna, L.:<br>MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth<br>system modeling using Voronoi grids, Geoscientific Model Development, 11,<br>3747–3780, 2018.</p> <p>Jourdain, N. C., Asay-Davis, X., Hattermann, T., Straneo, F., Seroussi, H.,<br>Little, C. M., and Nowicki, S.: A protocol for calculating basal melt rates in<br>the ISMIP6 Antarctic ice sheet projections, The Cryosphere, 14, 3111–3134,<br>https://doi.org/10.5194/tc-14-3111-2020, 2020.</p> <p>Nowicki, S., Goelzer, H., Seroussi, H., Payne, A. J., Lipscomb, W. H.,<br>Abe-Ouchi, A., Agosta, C., Alexander, P., Asay-Davis, X. S., Barthel, A.,<br>Bracegirdle, T. J., Cullather, R., Felikson, D., Fettweis, X., Gregory, J. M.,<br>Hattermann, T., Jourdain, N. C., Kuipers Munneke, P., Larour, E., Little, C.<br>M., Morlighem, M., Nias, I., Shepherd, A., Simon, E., Slater, D., Smith, R.<br>S., Straneo, F., Trusel, L. D., van den Broeke, M. R., and van de Wal, R.:<br>Experimental protocol for sea level projections from ISMIP6 stand-alone ice<br>sheet models, The Cryosphere, 14, 2331–2368,<br>https://doi.org/10.5194/tc-14-2331-2020, 2020.</p> <p>Perego, M., Price, S., and Stadler, G.: Optimal Initial Conditions for<br>Coupling Ice Sheet Models to Earth System Models, Journal of Geophysical<br>Research: Earth Surface, 119, 1894–1917, https://doi.org/10.1002/2014JF003181,<br>2014.</p> <p>Seroussi, H., et al. 2024. ISMIP6 Projections 2300 Antarctica Protocol.<br>https://theghub.org/groups/ismip6/wiki/ISMIP6-Projections2300-Antarctica. </p> <p>van den Broeke, M.: RACMO2.3p1 annual surface mass balance Antarctica<br>(1979-2014), PANGAEA - Data Publisher for Earth & Environmental Science,<br>https://doi.org/10.1594/PANGAEA.896940, 2019.</p> <p>van Wessem, J., Reijmer, C., Morlighem, M., Mouginot, J., Rignot, E., Medley,<br>B., Joughin, I., Wouters, B., Depoorter, M., Bamber, J., Lenaerts, J., Van De<br>Berg, W., Van Den Broeke, M., and Van Meijgaard, E.: Improved Representation<br>of East Antarctic Surface Mass Balance in a Regional Atmospheric Climate<br>Model, Journal of Glaciology, 60, 761–770,<br>https://doi.org/10.3189/2014JoG14J051, 2014.</p>
Investigating similarities and differences of the penultimate and last glacial terminations with a coupled ice sheet - climate model
<p>This archive provides the iLOVECLIM-GRISLI outputs as part of the manuscript "Investigating similarities and differences of the penultimate and last glacial terminations with a coupled ice sheet - climate model". Contact: aurelien.quiquet@lsce.ipsl.fr</p>
Scripts for "Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model"
<p>The scripts used to generate the main figures and results of the work entitled ''Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model'' by Michalezyk et al., submitted for publication in JAMES - AGU in 2024.</p> <p>If you have any questions, please contact Nicolas MICHALEZYK : nicolas.michalezyk@locean.ipsl.fr</p>
Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model
<p>This archive provides the GRISLI ice sheet model and iLOVECLIM model outputs as part of the manuscript "Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model".<br><br></p> <p>Contact: louise.abot@locean.ipsl.fr</p>
Model output: NEMO-CICE with an emergent sea ice floe size distribution
<p>NEMO-CICE model output from experiments with and without an emergent sea ice floe size distribution.</p> <p>See README for further details</p>
CICE6 simulations: Quality Control for Community Based Sea Ice Model Development
<p>CICE6 simulations: Quality Control for Community Based Sea Ice Model Development<br> -----------------------------------------------------------------------------------</p> <p>Data from the CICE6 simulations by Elizabeth C. Hunke at Los Alamos National Laboratory described in the manuscript:</p> <p>Roberts, Hunke, Allard, Bailey, Craig, Lemieux and Turner (2018): Quality Control for Community Based Sea Ice Model Development.</p> <p>It was produced using the CICE sea ice model version 6.0.0.alpha with the baseline namelist:</p> <p>&setup_nml<br> days_per_year = 365<br> use_leap_years = .false.<br> year_init = 1990<br> istep0 = 0<br> dt = 3600.0<br> npt = 43800<br> ndtd = 1<br> runtype = 'continue'<br> ice_ic = '/usr/projects/climate/eclare/DATA/Consortium/CICE_data/ic/gx1/iced_gx1_v5.nc'<br> restart = .true.<br> restart_ext = .false.<br> use_restart_time = .true.<br> restart_format = 'nc'<br> lcdf64 = .false.<br> restart_dir = './restart/'<br> restart_file = 'iced'<br> pointer_file = './ice.restart_file'<br> dumpfreq = 'm'<br> dumpfreq_n = 1<br> dump_last = .false.<br> bfbflag = .false.<br> diagfreq = 24<br> diag_type = 'stdout'<br> diag_file = 'ice_diag.d'<br> print_global = .true.<br> print_points = .true.<br> latpnt(1) = 90.<br> lonpnt(1) = 0.<br> latpnt(2) = -65.<br> lonpnt(2) = -45.<br> dbug = .false.<br> histfreq = 'm','d','x','x','x'<br> histfreq_n = 1 , 1 , 1 , 1 , 1<br> hist_avg = .true.<br> history_dir = './history/'<br> history_file = 'iceh'<br> write_ic = .true.<br> incond_dir = './history/'<br> incond_file = 'iceh_ic'<br> /</p> <p>&grid_nml<br> grid_format = 'bin'<br> grid_type = 'displaced_pole'<br> grid_file = '/usr/projects/climate/eclare/DATA/Consortium/CICE_data/grid/gx1/grid_gx1.bin'<br> kmt_file = '/usr/projects/climate/eclare/DATA/Consortium/CICE_data/grid/gx1/kmt_gx1.bin'<br> gridcpl_file = 'unknown_gridcpl_file'<br> kcatbound = 0<br> /</p> <p>&domain_nml<br> nprocs = 32<br> processor_shape = 'slenderX2'<br> distribution_type = 'cartesian'<br> distribution_wght = 'latitude'<br> ew_boundary_type = 'cyclic'<br> ns_boundary_type = 'open'<br> maskhalo_dyn = .false.<br> maskhalo_remap = .false.<br> maskhalo_bound = .false.<br> /</p> <p>&tracer_nml<br> tr_iage = .true.<br> restart_age = .false.<br> tr_FY = .true.<br> restart_FY = .false.<br> tr_lvl = .true.<br> restart_lvl = .false.<br> tr_pond_cesm = .false.<br> restart_pond_cesm = .false.<br> tr_pond_topo = .false.<br> restart_pond_topo = .false.<br> tr_pond_lvl = .true.<br> restart_pond_lvl = .false.<br> tr_aero = .false.<br> restart_aero = .false.<br> /</p> <p>&thermo_nml<br> kitd = 1<br> ktherm = 2<br> conduct = 'bubbly'<br> a_rapid_mode = 0.5e-3<br> Rac_rapid_mode = 10.0<br> aspect_rapid_mode = 1.0<br> dSdt_slow_mode = -5.0e-8<br> phi_c_slow_mode = 0.05<br> phi_i_mushy = 0.85<br> /</p> <p>&dynamics_nml<br> kdyn = 1<br> ndte = 120<br> revised_evp = .false.<br> advection = 'remap'<br> kstrength = 1<br> krdg_partic = 1<br> krdg_redist = 1<br> mu_rdg = 3<br> Cf = 17.<br> Ktens = 0.<br> e_ratio = 2.<br> basalstress = .false.<br> /</p> <p>&shortwave_nml<br> shortwave = 'dEdd'<br> albedo_type = 'default'<br> albicev = 0.78<br> albicei = 0.36<br> albsnowv = 0.98<br> albsnowi = 0.70 <br> ahmax = 0.3<br> R_ice = 0.<br> R_pnd = 0.<br> R_snw = 1.5<br> dT_mlt = 1.5<br> rsnw_mlt = 1500.<br> kalg = 0.6<br> /</p> <p>&ponds_nml<br> hp1 = 0.01<br> hs0 = 0.<br> hs1 = 0.03<br> dpscale = 1.e-3<br> frzpnd = 'hlid'<br> rfracmin = 0.15<br> rfracmax = 1.<br> pndaspect = 0.8<br> /</p> <p>&zbgc_nml<br> tr_brine = .false.<br> restart_hbrine = .false.<br> tr_zaero = .false.<br> modal_aero = .false.<br> skl_bgc = .false.<br> z_tracers = .false.<br> dEdd_algae = .false.<br> solve_zbgc = .false.<br> bgc_flux_type = 'Jin2006'<br> restore_bgc = .false.<br> restart_bgc = .false.<br> scale_bgc = .false.<br> solve_zsal = .false.<br> restart_zsal = .false.<br> bgc_data_dir = '/uknown_bgc_data_dir'<br> sil_data_type = 'default'<br> nit_data_type = 'default'<br> fe_data_type = 'default'<br> tr_bgc_Nit = .true.<br> tr_bgc_C = .true.<br> tr_bgc_chl = .false.<br> tr_bgc_Am = .true.<br> tr_bgc_Sil = .true.<br> tr_bgc_DMS = .false.<br> tr_bgc_PON = .true.<br> tr_bgc_hum = .true.<br> tr_bgc_DON = .false.<br> tr_bgc_Fe = .true. <br> grid_o = 0.006<br> grid_o_t = 0.006<br> l_sk = 0.024<br> grid_oS = 0.0<br> l_skS = 0.028<br> phi_snow = -0.3<br> initbio_frac = 0.8<br> frazil_scav = 0.8 <br> ratio_Si2N_diatoms = 1.8 <br> ratio_Si2N_sp = 0.0<br> ratio_Si2N_phaeo = 0.0<br> ratio_S2N_diatoms = 0.03 <br> ratio_S2N_sp = 0.03 <br> ratio_S2N_phaeo = 0.03<br> ratio_Fe2C_diatoms = 0.0033<br> ratio_Fe2C_sp = 0.0033<br> ratio_Fe2C_phaeo = 0.1<br> ratio_Fe2N_diatoms = 0.023 <br> ratio_Fe2N_sp = 0.023<br> ratio_Fe2N_phaeo = 0.7<br> ratio_Fe2DON = 0.023<br> ratio_Fe2DOC_s = 0.1<br> ratio_Fe2DOC_l = 0.033<br> fr_resp = 0.05<br> tau_min = 5200.0<br> tau_max = 173000.0<br> algal_vel = 0.0000000111<br> R_dFe2dust = 0.035<br> dustFe_sol = 0.005<br> chlabs_diatoms = 0.03<br> chlabs_sp = 0.01<br> chlabs_phaeo = 0.05<br> alpha2max_low_diatoms = 0.8<br> alpha2max_low_sp = 0.67<br> alpha2max_low_phaeo = 0.67<br> beta2max_diatoms = 0.018<br> beta2max_sp = 0.0025<br> beta2max_phaeo = 0.01<br> mu_max_diatoms = 1.44<br> mu_max_sp = 0.851<br> mu_max_phaeo = 0.851<br> grow_Tdep_diatoms = 0.06<br> grow_Tdep_sp = 0.06<br> grow_Tdep_phaeo = 0.06<br> fr_graze_diatoms = 0.0<br> fr_graze_sp = 0.1<br> fr_graze_phaeo = 0.1<br> mort_pre_diatoms = 0.007<br> mort_pre_sp = 0.007<br> mort_pre_phaeo = 0.007<br> mort_Tdep_diatoms = 0.03<br> mort_Tdep_sp = 0.03<br> mort_Tdep_phaeo = 0.03<br> k_exude_diatoms = 0.0<br> k_exude_sp = 0.0<br> k_exude_phaeo = 0.0<br> K_Nit_diatoms = 1.0<br> K_Nit_sp = 1.0<br> K_Nit_phaeo = 1.0<br> K_Am_diatoms = 0.3<br> K_Am_sp = 0.3<br> K_Am_phaeo = 0.3<br> K_Sil_diatoms = 4.0<br> K_Sil_sp = 0.0<br> K_Sil_phaeo = 0.0<br> K_Fe_diatoms = 1.0<br> K_Fe_sp = 0.2<br> K_Fe_phaeo = 0.1<br> f_don_protein = 0.6<br> kn_bac_protein = 0.03<br> f_don_Am_protein = 0.25<br> f_doc_s = 0.4<br> f_doc_l = 0.4<br> f_exude_s = 1.0<br> f_exude_l = 1.0<br> k_bac_s = 0.03<br> k_bac_l = 0.03<br> T_max = 0.0<br> fsal = 1.0<br> op_dep_min = 0.1<br> fr_graze_s = 0.5<br> fr_graze_e = 0.5<br> fr_mort2min = 0.5<br> fr_dFe = 0.3<br> k_nitrif = 0.0<br> t_iron_conv = 3065.0<br> max_loss = 0.9<br> max_dfe_doc1 = 0.2<br> fr_resp_s = 0.75<br> y_sk_DMS = 0.5<br> t_sk_conv = 3.0<br> t_sk_ox = 10.0<br> algaltype_diatoms = 0.0<br> algaltype_sp = 0.5<br> algaltype_phaeo = 0.5<br> nitratetype = -1.0<br> ammoniumtype = 1.0<br> silicatetype = -1.0<br> dmspptype = 0.5<br> dmspdtype = -1.0<br> humtype = 1.0<br> doctype_s = 0.5<br> doctype_l = 0.5<br> dontype_protein = 0.5<br> fedtype_1 = 0.5<br> feptype_1 = 0.5<br> zaerotype_bc1 = 1.0<br> zaerotype_bc2 = 1.0<br> zaerotype_dust1 = 1.0<br> zaerotype_dust2 = 1.0<br> zaerotype_dust3 = 1.0<br> zaerotype_dust4 = 1.0<br> ratio_C2N_diatoms = 7.0<br> ratio_C2N_sp = 7.0<br> ratio_C2N_phaeo = 7.0<br> ratio_chl2N_diatoms= 2.1<br> ratio_chl2N_sp = 1.1<br> ratio_chl2N_phaeo = 0.84<br> F_abs_chl_diatoms = 2.0<br> F_abs_chl_sp = 4.0<br> F_abs_chl_phaeo = 5.0<br> ratio_C2N_proteins = 7.0<br> /</p> <p>&forcing_nml<br> formdrag = .false.<br> atmbndy = 'default'<br> fyear_init = 1990<br> ycycle = 20<br> atm_data_format = 'bin'<br> atm_data_type = 'LYq'<br> atm_data_dir = '/usr/projects/climate/eclare/DATA/Consortium/CICE_data/forcing/gx1/COREII'<br> calc_strair = .true.<br> highfreq = .false.<br> natmiter = 5<br> calc_Tsfc = .true.<br> precip_units = 'mm_per_sec'<br> ustar_min = 0.0005<br> fbot_xfer_type = 'constant'<br> update_ocn_f = .false.<br> l_mpond_fresh = .false.<br> tfrz_option = 'mushy'<br> oceanmixed_ice = .true.<br> ocn_data_format = 'nc'<br> sss_data_type = 'ncar'<br> sst_data_type = 'ncar'<br> ocn_data_dir = '/usr/projects/climate/eclare/DATA/gx1v3/gx1v3/forcing/'<br> oceanmixed_file = 'oceanmixed_ice_depth.nc'<br> restore_sst = .false.<br> trestore = 90<br> restore_ice = .false.<br> /</p> <p>&icefields_nml<br> f_tmask = .true.<br> f_blkmask = .true.<br> f_tarea = .true.<br> f_uarea = .true.<br> f_dxt = .false.<br> f_dyt = .false.<br> f_dxu = .false.<br> f_dyu = .false.<br> f_HTN = .false.<br> f_HTE = .false.<br> f_ANGLE = .true.<br> f_ANGLET = .true.<br> f_NCAT = .true.<br> f_VGRDi = .false.<br> f_VGRDs = .false.<br> f_VGRDb = .false.<br> f_VGRDa = .true.<br> f_bounds = .false.<br> f_aice = 'm' <br> f_hi = 'm'<br> f_hs = 'm' <br> f_Tsfc = 'm' <br> f_sice = 'm' <br> f_uvel = 'm' <br> f_vvel = 'm' <br> f_uatm = 'm' <br> f_vatm = 'm' <br> f_fswdn = 'm' <br> f_flwdn = 'm'<br> f_snowfrac = 'x'<br> f_snow = 'x' <br> f_snow_ai = 'm' <br> f_rain = 'x' <br> f_rain_ai = 'm' <br> f_sst = 'm' <br> f_sss = 'm' <br> f_uocn = 'm' <br> f_vocn = 'm' <br> f_frzmlt = 'm'<br> f_fswfac = 'm'<br> f_fswint_ai = 'm'<br> f_fswabs = 'x' <br> f_fswabs_ai = 'm' <br> f_albsni = 'm' <br> f_alvdr = 'x'<br> f_alidr = 'x'<br> f_alvdf = 'x'<br> f_alidf = 'x'<br> f_alvdr_ai = 'x'<br> f_alidr_ai = 'x'<br> f_alvdf_ai = 'x'<br> f_alidf_ai = 'x'<br> f_albice = 'x'<br> f_albsno = 'x'<br> f_albpnd = 'x'<br> f_coszen = 'x'<br> f_flat = 'x' <br> f_flat_ai = 'm' <br> f_fsens = 'x' <br> f_fsens_ai = 'm' <br> f_fswup = 'x' <br> f_flwup = 'x' <br> f_flwup_ai = 'm' <br> f_evap = 'x' <br> f_evap_ai = 'm' <br> f_Tair = 'm' <br> f_Tref = 'x' <br> f_Qref = 'x'<br> f_congel = 'm' <br> f_frazil = 'm' <br> f_snoice = 'm' <br> f_dsnow = 'x' <br> f_melts = 'm'<br> f_meltt = 'm'<br> f_meltb = 'm'<br> f_meltl = 'm'<br> f_fresh = 'x'<br> f_fresh_ai = 'm'<br> f_fsalt = 'x'<br> f_fsalt_ai = 'm'<br> f_fbot = 'm'<br> f_fhocn = 'x' <br> f_fhocn_ai = 'm' <br> f_fswthru = 'x' <br> f_fswthru_ai = 'm' <br> f_fsurf_ai = 'x'<br> f_fcondtop_ai = 'x'<br> f_fmeltt_ai = 'x' <br> f_strairx = 'm' <br> f_strairy = 'm' <br> f_strtltx = 'x' <br> f_strtlty = 'x' <br> f_strcorx = 'x' <br> f_strcory = 'x' <br> f_strocnx = 'x' <br> f_strocny = 'x' <br> f_strintx = 'x' <br> f_strinty = 'x'<br> f_taubx = 'x'<br> f_tauby = 'x'<br> f_strength = 'm'<br> f_divu = 'm'<br> f_shear = 'm'<br> f_sig1 = 'm' <br> f_sig2 = 'm' <br> f_dvidtt = 'm' <br> f_dvidtd = 'm' <br> f_daidtt = 'm'<br> f_daidtd = 'm' <br> f_dagedtt = 'm'<br> f_dagedtd = 'm' <br> f_mlt_onset = 'm'<br> f_frz_onset = 'm'<br> f_hisnap = 'd'<br> f_aisnap = 'd'<br> f_trsig = 'm'<br> f_icepresent = 'm'<br> f_iage = 'm'<br> f_FY = 'x'<br> f_aicen = 'x'<br> f_vicen = 'x'<br> f_vsnon = 'x'<br> f_snowfracn = 'x'<br> f_keffn_top = 'x'<br> f_Tinz = 'x'<br> f_Sinz = 'x'<br> f_Tsnz = 'x'<br> f_fsurfn_ai = 'x'<br> f_fcondtopn_ai = 'x'<br> f_fmelttn_ai = 'x'<br> f_flatn_ai = 'x'<br> f_fsensn_ai = 'x'<br> /</p> <p>&icefields_mechred_nml<br> f_alvl = 'm'<br> f_vlvl = 'm'<br> f_ardg = 'm'<br> f_vrdg = 'm'<br> f_dardg1dt = 'x'<br> f_dardg2dt = 'x'<br> f_dvirdgdt = 'x'<br> f_opening = 'x'<br> f_ardgn = 'x'<br> f_vrdgn = 'x'<br> f_dardg1ndt = 'x'<br> f_dardg2ndt = 'x'<br> f_dvirdgndt = 'x'<br> f_krdgn = 'x'<br> f_aparticn = 'x'<br> f_aredistn = 'x'<br> f_vredistn = 'x'<br> f_araftn = 'x'<br> f_vraftn = 'x'<br> /</p> <p>&icefields_pond_nml<br> f_apondn = 'x'<br> f_apeffn = 'x'<br> f_hpondn = 'x'<br> f_apond = 'm'<br> f_hpond = 'm'<br> f_ipond = 'm'<br> f_apeff = 'm'<br> f_apond_ai = 'm'<br> f_hpond_ai = 'm'<br> f_ipond_ai = 'm'<br> f_apeff_ai = 'm'<br> /</p> <p>&icefields_bgc_nml<br> f_faero_atm = 'x'<br> f_faero_ocn = 'x'<br> f_aero = 'x' <br> f_fbio = 'm'<br> f_fbio_ai = 'm'<br> f_zaero = 'x'<br> f_bgc_S = 'm'<br> f_bgc_N = 'm'<br> f_bgc_C = 'x'<br> f_bgc_DOC = 'm'<br> f_bgc_DIC = 'x'<br> f_bgc_chl = 'x'<br> f_bgc_Nit = 'm'<br> f_bgc_Am = 'm'<br> f_bgc_Sil = 'm'<br> f_bgc_DMSPp = 'x'<br> f_bgc_DMSPd = 'x'<br> f_bgc_DMS = 'x'<br> f_bgc_DON = 'x' <br> f_bgc_Fe = 'm' <br> f_bgc_hum = 'm' <br> f_bgc_PON = 'm'<br> f_bgc_ml = 'm'<br> f_upNO = 'm'<br> f_upNH = 'm'<br> f_bTin = 'm'<br> f_bphi = 'm' <br> f_iDi = 'm'<br> f_iki = 'm'<br> f_fbri = 'm' <br> f_hbri = 'm'<br> f_zfswin = 'm'<br> f_bionet = 'm'<br> f_biosnow = 'm'<br> f_grownet = 'm'<br> f_PPnet = 'm'<br> f_algalpeak = 'm'<br> f_zbgc_frac = 'm'<br> /</p> <p>&icefields_drag_nml<br> f_drag = 'x'<br> f_Cdn_atm = 'x'<br> f_Cdn_ocn = 'x'<br> /</p>
RASM simulations: Quality Control for Community Based Sea Ice Model Development
<p>RASM simulations: Quality Control for Community Based Sea Ice Model Development<br> -----------------------------------------------------------------------------------</p> <p>Data from the Regional Arctic System Model (RASM) simulations by Andrew F. Roberts at Naval Postgraduate School, described in the manuscript:</p> <p>Roberts, Hunke, Allard, Bailey, Craig, Lemieux and Turner (2018): Quality Control for Community Based Sea Ice Model Development.</p> <p>It was produced using RASM with CICE sea ice model version 5.2 with the namelist:</p> <p>&setup_nml<br> bfbflag = .false. <br> diagfreq = 24 <br> hist_avg = .true. <br> histfreq = 'h','x','x','x','x'<br> histfreq_n = 1,0,0,0,0<br> ice_ic = '/work4/projects/apcraig_dir/RACM/inputdata/ccsm4_init/R1008Gcaaa01a_loop2/1979-09-01/R1008Gcaaa01a_loop2.cice.r.1979-09-01-00000.nc'<br> latpnt = 90.0,-65.0 <br> lcdf64 = .true. <br> lonpnt = 0.0,-45.0 <br> ndtd = 1 <br> pointer_file = './rpointer.ice'<br> print_global = .true. <br> print_points = .false. <br> restart_ext = .false. <br> restart_format = 'pio'<br> year_init = 1 <br> /<br> &grid_nml<br> grid_file = '/work4/projects/apcraig_dir/RACM/inputdata/ice/cice/ar9v3_20101118.grid'<br> grid_format = 'bin'<br> grid_type = 'regional'<br> gridcpl_file = '/work4/projects/apcraig_dir/RACM/inputdata/ice/cice/domain.ocn.ar9v4.100920.nc'<br> kcatbound = 0 <br> kmt_file = '/work4/projects/apcraig_dir/RACM/inputdata/ice/cice/ar9v3_20110106.kmt'<br> /<br> &tracer_nml<br> restart_aero = .false. <br> restart_age = .false. <br> restart_fy = .false. <br> restart_lvl = .false. <br> restart_pond_cesm = .false. <br> restart_pond_lvl = .false. <br> restart_pond_topo = .false. <br> tr_aero = .false.<br> tr_fy = .true. <br> tr_iage = .true. <br> tr_lvl = .true. <br> tr_pond_cesm = .false. <br> tr_pond_lvl = .true. <br> tr_pond_topo = .false. <br> /<br> &thermo_nml<br> a_rapid_mode = 0.5e-03 <br> aspect_rapid_mode = 1.0 <br> conduct = 'bubbly'<br> dsdt_slow_mode = -1.5e-07 <br> kitd = 1 <br> ktherm = 2 <br> phi_c_slow_mode = 0.05 <br> phi_i_mushy = 0.85 <br> rac_rapid_mode = 10 <br> /<br> &dynamics_nml<br> advection = 'remap'<br> cf = 21.3<br> kdyn = 2 (EAP) or kdyn = 2 (EVP)<br> krdg_partic = 1<br> krdg_redist = 1<br> kstrength = 1 <br> mu_rdg = 3.0<br> ndte = 600 <br> revised_evp = .false. <br> /<br> &shortwave_nml<br> ahmax = 0.3 <br> albedo_type = 'default'<br> albicei = 0.45<br> albicev = 0.75<br> albsnowi = 0.73<br> albsnowv = 0.98<br> dt_mlt = 1.00 <br> kalg = 0.0 <br> r_ice = 0.0 <br> r_pnd = 0.0 <br> r_snw = 0.50 <br> rsnw_mlt = 1000. <br> shortwave = 'dEdd'<br> /<br> &ponds_nml<br> dpscale = 1.0e-3 <br> frzpnd = 'hlid'<br> hp1 = 0.01 <br> hs0 = 0.03 <br> hs1 = 0.03 <br> pndaspect = 0.8 <br> rfracmax = 0.85 <br> rfracmin = 0.15 <br> /<br> &forcing_nml<br> fbot_xfer_type = 'constant'<br> formdrag = .false.<br> highfreq = .true.<br> l_mpond_fresh = .false.<br> natmiter = 25 <br> tfrz_option = 'mushy'<br> /<br> &domain_nml<br> distribution_type = 'roundrobin'<br> ew_boundary_type = 'cyclic'<br> maskhalo_bound = .true.<br> maskhalo_dyn = .true.<br> maskhalo_remap = .true.<br> ns_boundary_type = 'open'<br> processor_shape = 'null'<br> /<br> &zbgc_nml<br> bgc_data_dir = 'unknown_bgc_data_dir'<br> bgc_flux_type = 'Jin2006'<br> nit_data_type = 'unknown'<br> phi_snow = 0.5 <br> restart_bgc = .false. <br> restart_hbrine = .false. <br> restore_bgc = .false. <br> sil_data_type = 'unknown'<br> skl_bgc = .false. <br> tr_bgc_am_sk = .false. <br> tr_bgc_c_sk = .false. <br> tr_bgc_chl_sk = .false. <br> tr_bgc_dms_sk = .false. <br> tr_bgc_dmspd_sk = .false. <br> tr_bgc_dmspp_sk = .false. <br> tr_bgc_sil_sk = .false. <br> tr_brine = .false. <br> /<br> &icefields_bgc_nml<br> f_aero = 'mxxxx'<br> f_aeron = 'xxxxx'<br> f_bgc_am_ml = 'xxxxx'<br> f_bgc_am_sk = 'xxxxx'<br> f_bgc_c = 'xxxxx'<br> f_bgc_c_sk = 'xxxxx'<br> f_bgc_chl = 'xxxxx'<br> f_bgc_chl_sk = 'xxxxx'<br> f_bgc_dms = 'xxxxx'<br> f_bgc_dms_ml = 'xxxxx'<br> f_bgc_dms_sk = 'xxxxx'<br> f_bgc_dmsp_ml = 'xxxxx'<br> f_bgc_dmspd = 'xxxxx'<br> f_bgc_dmspd_sk = 'xxxxx'<br> f_bgc_dmspp = 'xxxxx'<br> f_bgc_dmspp_sk = 'xxxxx'<br> f_bgc_n = 'xxxxx'<br> f_bgc_n_sk = 'xxxxx'<br> f_bgc_nh = 'xxxxx'<br> f_bgc_nit_ml = 'xxxxx'<br> f_bgc_nit_sk = 'xxxxx'<br> f_bgc_no = 'xxxxx'<br> f_bgc_s = 'xxxxx'<br> f_bgc_sil = 'xxxxx'<br> f_bgc_sil_ml = 'xxxxx'<br> f_bgc_sil_sk = 'xxxxx'<br> f_bphi = 'xxxxx'<br> f_btin = 'xxxxx'<br> f_faero_atm = 'mxxxx'<br> f_faero_ocn = 'mxxxx'<br> f_fbri = 'xxxxx'<br> f_fn = 'xxxxx'<br> f_fn_ai = 'xxxxx'<br> f_fnh = 'xxxxx'<br> f_fnh_ai = 'xxxxx'<br> f_fno = 'xxxxx'<br> f_fno_ai = 'xxxxx'<br> f_fsil = 'xxxxx'<br> f_fsil_ai = 'xxxxx'<br> f_grownet = 'xxxxx'<br> f_hbri = 'xxxxx'<br> f_ppnet = 'xxxxx'<br> /<br> &icefields_drag_nml<br> f_cdn_atm = 'hxxxx'<br> f_cdn_ocn = 'hxxxx'<br> f_drag = 'hxxxx'<br> /<br> &icefields_mechred_nml<br> f_alvl = 'hxxxx'<br> f_aparticn = 'xxxxx'<br> f_araftn = 'xxxxx'<br> f_ardg = 'hxxxx'<br> f_ardgn = 'hxxxx'<br> f_aredistn = 'xxxxx'<br> f_dardg1dt = 'xxxxx'<br> f_dardg1ndt = 'xxxxx'<br> f_dardg2dt = 'xxxxx'<br> f_dardg2ndt = 'xxxxx'<br> f_dvirdgdt = 'xxxxx'<br> f_dvirdgndt = 'xxxxx'<br> f_krdgn = 'xxxxx'<br> f_opening = 'hxxxx'<br> f_vlvl = 'hxxxx'<br> f_vraftn = 'xxxxx'<br> f_vrdg = 'hxxxx'<br> f_vrdgn = 'hxxxx'<br> f_vredistn = 'xxxxx'<br> /<br> &icefields_pond_nml<br> f_apeff = 'hxxxx'<br> f_apeff_ai = 'hxxxx'<br> f_apeffn = 'hxxxx'<br> f_apond = 'hxxxx'<br> f_apond_ai = 'hxxxx'<br> f_apondn = 'hxxxx'<br> f_hpond = 'hxxxx'<br> f_hpond_ai = 'hxxxx'<br> f_hpondn = 'hxxxx'<br> f_ipond = 'hxxxx'<br> f_ipond_ai = 'hxxxx'<br> /<br> &icefields_nml<br> f_a11 = 'hxxxx'<br> f_a12 = 'hxxxx'<br> f_aice = 'hxxxx'<br> f_aicen = 'hxxxx'<br> f_aisnap = 'hxxxx'<br> f_albice = 'hxxxx'<br> f_albpnd = 'hxxxx'<br> f_albsni = 'hxxxx'<br> f_albsno = 'hxxxx'<br> f_alidf = 'hxxxx'<br> f_alidr = 'hxxxx'<br> f_alvdf = 'hxxxx'<br> f_alvdr = 'hxxxx'<br> f_angle = .true.<br> f_anglet = .true.<br> f_blkmask = .true.<br> f_bounds = .false.<br> f_congel = 'hxxxx'<br> f_coszen = 'hxxxx'<br> f_daidtd = 'hxxxx'<br> f_daidtt = 'hxxxx'<br> f_divu = 'hxxxx'<br> f_dsnow = 'hxxxx'<br> f_dvidtd = 'hxxxx'<br> f_dvidtt = 'hxxxx'<br> f_dxt = .false.<br> f_dxu = .false.<br> f_dyt = .false.<br> f_dyu = .false.<br> f_e11 = 'xxxxx'<br> f_e12 = 'xxxxx'<br> f_e22 = 'xxxxx'<br> f_evap = 'hxxxx'<br> f_evap_ai = 'hxxxx'<br> f_fcondtop_ai = 'hxxxx'<br> f_fcondtopn_ai = 'hxxxx'<br> f_fhocn = 'hxxxx'<br> f_fhocn_ai = 'hxxxx'<br> f_flat = 'hxxxx'<br> f_flat_ai = 'hxxxx'<br> f_flatn_ai = 'hxxxx'<br> f_flwdn = 'hxxxx'<br> f_flwup = 'hxxxx'<br> f_flwup_ai = 'hxxxx'<br> f_fmeltt_ai = 'hxxxx'<br> f_fmelttn_ai = 'hxxxx'<br> f_frazil = 'hxxxx'<br> f_fresh = 'hxxxx'<br> f_fresh_ai = 'hxxxx'<br> f_frz_onset = 'hxxxx'<br> f_frzmlt = 'hxxxx'<br> f_fsalt = 'hxxxx'<br> f_fsalt_ai = 'hxxxx'<br> f_fsens = 'hxxxx'<br> f_fsens_ai = 'hxxxx'<br> f_fsensn_ai = 'hxxxx'<br> f_fsurf_ai = 'hxxxx'<br> f_fsurfn_ai = 'hxxxx'<br> f_fswabs = 'hxxxx'<br> f_fswabs_ai = 'hxxxx'<br> f_fswdn = 'hxxxx'<br> f_fswfac = 'hxxxx'<br> f_fswint_ai = 'xxxxx'<br> f_fswthru = 'hxxxx'<br> f_fswthru_ai = 'hxxxx'<br> f_fy = 'hxxxx'<br> f_hi = 'hxxxx'<br> f_hisnap = 'xxxxx'<br> f_hs = 'hxxxx'<br> f_hte = .false.<br> f_htn = .false.<br> f_iage = 'hxxxx'<br> f_icepresent = 'hxxxx'<br> f_keffn_top = 'xxxxx'<br> f_meltb = 'hxxxx'<br> f_meltl = 'hxxxx'<br> f_melts = 'hxxxx'<br> f_meltt = 'hxxxx'<br> f_mlt_onset = 'hxxxx'<br> f_ncat = .true.<br> f_qref = 'hxxxx'<br> f_rain = 'hxxxx'<br> f_rain_ai = 'hxxxx'<br> f_s11 = 'hxxxx'<br> f_s12 = 'hxxxx'<br> f_s22 = 'hxxxx'<br> f_shear = 'hxxxx'<br> f_sice = 'hxxxx'<br> f_sig1 = 'hxxxx'<br> f_sig2 = 'hxxxx'<br> f_sinz = 'xxxxx'<br> f_snoice = 'hxxxx'<br> f_snow = 'hxxxx'<br> f_snow_ai = 'hxxxx'<br> f_sss = 'hxxxx'<br> f_sst = 'hxxxx'<br> f_strairx = 'hxxxx'<br> f_strairy = 'hxxxx'<br> f_strcorx = 'hxxxx'<br> f_strcory = 'hxxxx'<br> f_strength = 'hxxxx'<br> f_strintx = 'hxxxx'<br> f_strinty = 'hxxxx'<br> f_strocnx = 'hxxxx'<br> f_strocny = 'hxxxx'<br> f_strtltx = 'hxxxx'<br> f_strtlty = 'hxxxx'<br> f_tair = 'hxxxx'<br> f_tarea = .true.<br> f_tinz = 'xxxxx'<br> f_tmask = .true.<br> f_tref = 'hxxxx'<br> f_trsig = 'hxxxx'<br> f_tsfc = 'hxxxx'<br> f_tsnz = 'xxxxx'<br> f_uarea = .true.<br> f_uatm = 'hxxxx'<br> f_uocn = 'hxxxx'<br> f_uvel = 'hxxxx'<br> f_vatm = 'hxxxx'<br> f_vgrdb = .true.<br> f_vgrdi = .true.<br> f_vgrds = .true.<br> f_vicen = 'hxxxx'<br> f_vocn = 'hxxxx'<br> f_vsnon = 'hxxxx'<br> f_vvel = 'hxxxx'<br> f_yieldstress11 = 'hxxxx'<br> f_yieldstress12 = 'hxxxx'<br> f_yieldstress22 = 'hxxxx'<br> /<br> &ice_prescribed_nml<br> prescribed_ice = .false.<br> /</p>
GOFS simulations: Quality Control for Community Based Sea Ice Model Development
<p>GOFS simulations: Quality Control for Community Based Sea Ice Model Development<br> -----------------------------------------------------------------------------------</p> <p>Data from the Global Ocean Forecast System (GOFS 3.1) from the Naval Research Laboratory, curated by Richard Allard, and described in the manuscript:</p> <p>Roberts, Hunke, Allard, Bailey, Craig, Lemieux and Turner (2018): Quality Control for Community Based Sea Ice Model Development.</p> <p>It was produced using GOFS with CICE sea ice model version 4.0 with the namelist:</p> <p>&setup_nml<br> days_per_year= 366<br> , year_init = 1901<br> , istep0 = 0<br> , dt = 225.0<br> , npt = -1 <br> , ndyn_dt = 1<br> , inserthr = 0<br> , runtype = 'continue'<br> , ice_ic = 'default'<br> , restart = .true.<br> , restart_dir = './'<br> , restart_file = 'cice.restart'<br> , pointer_file = './cice.restart_file'<br> , histfreq = 'h'<br> , histfreq_n = 12<br> , dumpfreq = '5'<br> , dumpfreq_n = 1<br> , diagfreq = 8<br> , diag_type = 'stdout'<br> , diag_file = 'ice.diag.d'<br> , print_global = .true.<br> , print_points = .true.<br> , latpnt(1) = 72.011<br> , lonpnt(1) = -149.987<br> , latpnt(2) = 90.<br> , lonpnt(2) = 0.<br> , dbug = .false.<br> , incond_dir = <br> , incond_file = './cice'<br> /<br> &grid_nml<br> grid_format = 'bin'<br> , grid_type = 'hycom'<br> , grid_file = 'regional.cice.r'<br> , kmt_file = 'kmt'<br> , kcatbound = 0 <br> /<br> &domain_nml<br> nprocs = 1800<br> , processor_shape = 'slenderX4'<br> , distribution_type = 'cartesian'<br> , distribution_wght = 'latitude'<br> , ew_boundary_type = 'cyclic'<br> , ns_boundary_type = 'tripole'<br> /<br> &tracer_nml<br> tr_iage = .false.<br> , restart_age = .false.<br> , tr_pond = .false.<br> , restart_pond = .false.<br> /<br> &ice_nml<br> kitd = 1<br> , kdyn = 1<br> , ndte = 120<br> , kstrength = 1<br> , krdg_partic = 1<br> , krdg_redist = 1<br> , advection = 'remap'<br> , heat_capacity = .true.<br> , shortwave = 'default'<br> , albedo_type = 'default'<br> , albicev = 0.78<br> , albicei = 0.36<br> , albsnowv = 0.98<br> , albsnowi = 0.70 <br> , R_ice = 0.0<br> , R_pnd = 0.0<br> , R_snw = 0.0<br> , atmbndy = 'default'<br> , fyear_init = 1911 <br> , ycycle = 1 <br> , atm_data_format = 'bin'<br> , atm_data_type= 'cfsr'<br> , atm_data_dir = './cice.'<br> , calc_strair = .true.<br> , calc_Tsfc = .true.<br> , precip_units = 'mm_per_month'<br> , Tfrzpt = 'linear_S'<br> , update_ocn_f = .false.<br> , oceanmixed_ice = .true.<br> , ocn_data_format = 'bin'<br> , sss_data_type= 'cfsr'<br> , sst_data_type= 'cfsr'<br> , ocn_data_dir = 'COUPLED'<br> , oceanmixed_file= 'pop_frc.gx1v3.051202.nc'<br> , restore_sst = .true.<br> , insert_ssmi = .true.<br> , insert_sih = .false.<br> , trestore = 1 <br> , atm_netrad = .false.<br> , albnetrad = 0.00<br> /<br> &icefields_nml<br> f_tmask = .false.<br> , f_tarea = .false.<br> , f_uarea = .false.<br> , f_dxt = .false.<br> , f_dyt = .false.<br> , f_dxu = .false.<br> , f_dyu = .false.<br> , f_HTN = .false.<br> , f_HTE = .false.<br> , f_ANGLE = .false.<br> , f_ANGLET = .false.<br> , f_bounds = .false.<br> , f_hi = .true.<br> , f_hs = .true. <br> , f_Tsfc = .true. <br> , f_aice = .true. <br> , f_uvel = .true. <br> , f_vvel = .true. <br> , f_fswdn = .true. <br> , f_flwdn = .true.<br> , f_snow = .true. <br> , f_snow_ai = .true. <br> , f_rain = .false. <br> , f_rain_ai = .true. <br> , f_sst = .true. <br> , f_sss = .true. <br> , f_uocn = .true. <br> , f_vocn = .true. <br> , f_frzmlt = .true.<br> , f_fswabs = .true. <br> , f_fswabs_ai = .true. <br> , f_albsni = .true. <br> , f_alvdr = .false.<br> , f_alidr = .false.<br> , f_flat = .false. <br> , f_flat_ai = .true. <br> , f_fsens = .false. <br> , f_fsens_ai = .true. <br> , f_flwup = .false. <br> , f_flwup_ai = .true. <br> , f_evap = .false. <br> , f_evap_ai = .true. <br> , f_Tair = .true. <br> , f_Tref = .false. <br> , f_Qref = .false.<br> , f_congel = .true. <br> , f_frazil = .true. <br> , f_snoice = .true. <br> , f_meltt = .true.<br> , f_meltb = .true.<br> , f_meltl = .true.<br> , f_fresh = .false.<br> , f_fresh_ai = .true.<br> , f_fsalt = .false.<br> , f_fsalt_ai = .true.<br> , f_fhocn = .false. <br> , f_fhocn_ai = .true. <br> , f_fswthru = .false. <br> , f_fswthru_ai= .true. <br> , f_fsurf_ai = .false.<br> , f_fcondtop_ai= .false.<br> , f_fmeltt_ai = .false. <br> , f_strairx = .true. <br> , f_strairy = .true. <br> , f_strtltx = .false. <br> , f_strtlty = .false. <br> , f_strcorx = .true. <br> , f_strcory = .true. <br> , f_strocnx = .true. <br> , f_strocny = .true. <br> , f_strintx = .false. <br> , f_strinty = .false.<br> , f_strength = .true.<br> , f_divu = .true.<br> , f_shear = .false.<br> , f_sig1 = .false. <br> , f_sig2 = .false. <br> , f_dvidtt = .false. <br> , f_dvidtd = .false. <br> , f_daidtt = .false.<br> , f_daidtd = .false. <br> , f_mlt_onset = .false.<br> , f_frz_onset = .false.<br> , f_dardg1dt = .false.<br> , f_dardg2dt = .false.<br> , f_dvirdgdt = .false.<br> , f_opening = .true.<br> , f_hisnap = .false.<br> , f_aisnap = .false.<br> , f_trsig = .false.<br> , f_icepresent= .false.<br> , f_iage = .false.<br> , f_aicen = .false.<br> , f_vicen = .false.<br> , f_fsurfn_ai = .false.<br> , f_fcondtopn_ai = .false.<br> , f_fmelttn_ai = .false.<br> , f_flatn_ai = .false.<br> /</p> <p> </p> <p> </p>
ECCC simulations: Quality Control for Community Based Sea Ice Model Development
<p>ECCC simulations: Quality Control for Community Based Sea Ice Model Development<br> -----------------------------------------------------------------------------------</p> <p>Data from the Environment and Climate Change Canada (ECCC) simulation by Jean-François Lemieux at Environment and Climate Change Canada, described in the manuscript:</p> <p>Roberts, Hunke, Allard, Bailey, Craig, Lemieux and Turner (2018): Quality Control for Community Based Sea Ice Model Development.</p> <p>It was produced using ECCC with CICE sea ice model version 4.0 with the namelist:</p> <p>&setup_nml<br> days_per_year = 365<br> , year_init = 2001100100<br> , istep0 = 0<br> , dt = 600<br> , npt = 2880<br> , ndyn_dt = 1<br> , runtype = 'continue'<br> , ice_ic = 'default'<br> , restart = .true.<br> , restart_dir = 'not_used_at_cmc'<br> , restart_file = 'not_used_at_cmc'<br> , pointer_file = './ice.restart_file'<br> , dumpfreq = 's'<br> , dumpfreq_n = 2880<br> , diagfreq = 144<br> , diag_type = 'file'<br> , diag_file = 'ice_stdout'<br> , print_global = .false.<br> , print_points = .false.<br> , latpnt(1) = 90.<br> , lonpnt(1) = 0.<br> , latpnt(2) = -65.<br> , lonpnt(2) = -45.<br> , dbug = .false.<br> , histfreq = 's' <br> , histfreq_n = 144<br> , hist_avg = .false.<br> , history_dir = './history/'<br> , history_file = 'iceh'<br> , history_format = 'nc'<br> , write_ic = .false.<br> , incond_dir = './history/'<br> , incond_file = 'iceh_ic'<br> /</p> <p>&grid_nml<br> grid_format = 'cmc'<br> , grid_type = 'cmc'<br> , grid_file = 'not_used_at_cmc'<br> , kmt_file = 'not_used_at_cmc'<br> , kcatbound = 2<br> /</p> <p>&domain_nml<br> nprocs = 72<br> , processor_shape = 'square-pop'<br> , distribution_type = 'cartesian'<br> , distribution_wght = 'block'<br> , ew_boundary_type = 'closed'<br> , ns_boundary_type = 'closed'<br> /</p> <p>&tracer_nml<br> tr_iage = .false.<br> , restart_age = .false.<br> , tr_pond = .false.<br> , restart_pond = .false.<br> /</p> <p>&ice_nml<br> kitd = 1<br> , kdyn = 1<br> , ndte = 900<br> , kstrength = 0<br> , Pstar = 27.5e3<br> , floediam = 300.0<br> , hfrazilmin = 0.05 <br> , iceruf = 0.0004<br> , krdg_partic = 1<br> , krdg_redist = 1<br> , advection = 'remap'<br> , heat_capacity = .true.<br> , shortwave = 'default'<br> , albedo_type = 'default'<br> , albicev = 0.85<br> , albicei = 0.40<br> , albsnowv = 0.98<br> , albsnowi = 0.70 <br> , R_ice = 0.<br> , R_pnd = 0.<br> , R_snw = 0.<br> , atmbndy = 'default'<br> , fyear_init = 1000<br> , ycycle = 1<br> , atm_data_format = 'not_used_at_cmc'<br> , atm_data_type = 'cmc'<br> , atm_data_dir = 'not_used_at_cmc'<br> , calc_strair = .true.<br> , calc_Tsfc = .true.<br> , precip_units = 'mks'<br> , Tfrzpt = 'nonlin'<br> , update_ocn_f = .true.<br> , oceanmixed_ice = .false.<br> , oceanmixed_frc = .false.<br> , ocn_data_format = 'not_used_at_cmc'<br> , sss_data_type = 'cmcint'<br> , sst_data_type = 'cmcint'<br> , ocn_data_dir = 'not_used_at_cmc'<br> , oceanmixed_file = 'not_used_at_cmc'<br> , restore_sst = .false.<br> , trestore = 0<br> , dirassm_ice = .false.<br> , restore_ice = .false.<br> , restore_nul = .false.<br> , l_thermo = .true.<br> , l_dynmcs = .true.<br> , z0io = 0.0165<br> , l_dragio_r = .false.<br> , l_basalstress = .true.<br> , k1 = 8.0<br> , k2 = 15.0<br> , u0 = 5e-5<br> , CC = 20.0<br> , Ktens = 0.05<br> , e_ratio = 1.4<br> /</p> <p>&namcmc_nml<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! CMC grid parameters (cmc_ln_gemgrid = T ==> grtyp=Z, else grtyp=X)<br> ! The buffer zone is not output <br> ! cmc_ln_bdyopn=T ==> open boundaries including buffer zone<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> cmc_ln_gemgrid = .false.<br> , cmc_ln_nemogrid = .true.<br> , cmc_nbuff_zone = 0<br> , cmc_ln_bdyopn = .false.<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! CMC atmospheric forcing parameters<br> cmc_dt_frcd = -9<br> , cmc_dt_prec = -9<br> , cmc_ln_intrp = .true.<br> , cmc_dateo = '20011001.000000' <br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! Input varables ! Long name (doc only) ! nomvar ! Constant (C) or Field (F) !<br> ! ...! Value (if C) ! Binary (B) or Integer (I) (if F) !<br> ! ...! ip1_1 ! ip1_2 ! scaling ! offset !<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! Grid ...<br> cmc_ulat = 'u-Lat(deg)','ULAT','F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_ulon = 'u-Lon(deg)','ULON','F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_tlat = 't-Lat(deg)','TLAT','F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_tlon = 't-Lon(deg)','TLON','F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_kmt = 'Mask (0-1)','KMT', 'F',-999.0,'I',-1 ,-1 , 1., 0.<br> cmc_hte = 'HTE (m) ','HTE' ,'F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_htn = 'HTN (m) ','HTN' ,'F',-999.0,'B',-1 ,-1 , 1., 0.<br> ! Ice-ocean state ...<br> cmc_ln_gslcat = .false.<br> cmc_ln_wmocat = .false.<br> cmc_ln_avgcat = .true.<br> cmc_ln_itdspr = .true.<br> cmc_gl = 'GL de CMC ','GL' ,'F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_i8 = 'I8 de CMC ','I8' ,'F',-999.0,'B',-1 ,-1 , 1., 0.<br> cmc_uice0 = 'U ice Vel.','null','C', 0.0,' ',-999999999,-999999999, -999., -999.<br> cmc_vice0 = 'V ice Vel.','null','C', 0.0,' ',-999999999,-999999999, -999., -999.<br> ! Ocean forcing ...<br> cmc_ln_frcsss = .false.<br> cmc_ln_frcsst = .false.<br> cmc_ln_frcuvo = .false.<br> ! Atm forcing ... (for ice I. C. internal temp override by restart)<br> cmc_tair = 'Air temp ','TT', 'C', 273.15,' ',999999999,999999999, 999., 999.<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! Mixed layer parameters<br> cmc_frzeps = 0.0005<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> ! Output parameters (cmc_ofmt='F' or 'H', Forecast or Hindcast style)<br> cmc_ofmt = 'H'<br> cmc_npako = -32<br> cmc_ln_stdrsti = .true.<br> cmc_ln_stdrsto = .true.<br> cmc_npakri = -64<br> cmc_npakro = -64<br> cmc_etiket = 'CREG_HCST'<br> !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!<br> /</p> <p>&icefields_nml<br> f_tmask = .false.<br> , f_tarea = .false.<br> , f_uarea = .false.<br> , f_dxt = .false.<br> , f_dyt = .false.<br> , f_dxu = .false.<br> , f_dyu = .false.<br> , f_HTN = .false.<br> , f_HTE = .false.<br> , f_ANGLE = .false.<br> , f_ANGLET = .false.<br> , f_bounds = .false.<br> , f_hi = .true.<br> , f_hs = .false. <br> , f_Tsfc = .false. <br> , f_aice = .true. <br> , f_uvel = .false. <br> , f_vvel = .false. <br> , f_fswdn = .false. <br> , f_flwdn = .false.<br> , f_snow = .false. <br> , f_snow_ai = .false. <br> , f_rain = .false. <br> , f_rain_ai = .false. <br> , f_sst = .false. <br> , f_sss = .false. <br> , f_uocn = .false. <br> , f_vocn = .false. <br> , f_frzmlt = .false.<br> , f_fswfac = .false.<br> , f_fswabs = .false. <br> , f_fswabs_ai = .false. <br> , f_albsni = .false. <br> , f_alvdr = .false.<br> , f_alidr = .false.<br> , f_albice = .false.<br> , f_albsno = .false.<br> , f_albpnd = .false.<br> , f_coszen = .false.<br> , f_flat = .false. <br> , f_flat_ai = .false. <br> , f_fsens = .false. <br> , f_fsens_ai = .false. <br> , f_flwup = .false. <br> , f_flwup_ai = .false. <br> , f_evap = .false. <br> , f_evap_ai = .false. <br> , f_Tair = .false. <br> , f_Tref = .false. <br> , f_Qref = .false.<br> , f_congel = .false. <br> , f_frazil = .false. <br> , f_snoice = .false. <br> , f_meltt = .false.<br> , f_meltb = .false.<br> , f_meltl = .false.<br> , f_fresh = .false.<br> , f_fresh_ai = .false.<br> , f_fsalt = .false.<br> , f_fsalt_ai = .false.<br> , f_fhocn = .false. <br> , f_fhocn_ai = .false. <br> , f_fswthru = .false. <br> , f_fswthru_ai = .false. <br> , f_fsurf_ai = .false.<br> , f_fcondtop_ai = .false.<br> , f_fmeltt_ai = .false. <br> , f_strairx = .false. <br> , f_strairy = .false. <br> , f_strtltx = .false. <br> , f_strtlty = .false. <br> , f_strcorx = .false. <br> , f_strcory = .false. <br> , f_strocnx = .false. <br> , f_strocny = .false. <br> , f_strintx = .false. <br> , f_strinty = .false.<br> , f_strength = .false.<br> , f_divu = .false.<br> , f_shear = .false.<br> , f_sig1 = .false. <br> , f_sig2 = .false. <br> , f_sigI = .false. <br> , f_dvidtt = .false. <br> , f_dvidtd = .false. <br> , f_daidtt = .false.<br> , f_daidtd = .false. <br> , f_mlt_onset = .false.<br> , f_frz_onset = .false.<br> , f_dardg1dt = .false.<br> , f_dardg2dt = .false.<br> , f_dvirdgdt = .false.<br> , f_opening = .false.<br> , f_hisnap = .false.<br> , f_aisnap = .false.<br> , f_trsig = .false.<br> , f_icepresent = .false.<br> , f_iage = .false.<br> , f_aicen = .false.<br> , f_vicen = .false.<br> , f_fsurfn_ai = .false.<br> , f_fcondtopn_ai = .false.<br> , f_fmelttn_ai = .false.<br> , f_flatn_ai = .false.<br> , f_apondn = .false.<br> , f_tau_bu = .false.<br> , f_tau_bv = .false.<br> /</p> <p> </p>
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