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49 results for “Antarctic Ice Sheet”
Simulations of Miocene Antarctic ice-sheet variability under increased precipitation and sub-shelf melt, using the ice-sheet model IMAU-ICE
<p>To demonstrate the viability of a precipitation regime change leading to a fundamentally different volume-to-area ratio of the Antarctic ice sheet, we deploy the 3D thermodynamical ice sheet/shelf model IMAU-ICE v1.1.1. In the standard set-up (<a href="https://doi.org/10.5194/cp-2023-12">Stap et al., 2021a</a>, <a href="https://doi.pangaea.de/10.1594/PANGAEA.939114">2021b</a>), climate forcing follows from pre-run warm and cold snapshot climate simulations. The applied climate forcing is transiently calculated based on the prescribed CO<sub>2</sub> concentration and the modelled ice sheet size, through a matrix interpolation method. Equilibrium experiments are performed at various CO<sub>2</sub> levels between preindustrial and 3x preindustrial CO<sub>2</sub> values, with insolation at present-day levels and initiated from an ice-free Miocene Antarctic topography (dataset <a href="https://doi.pangaea.de/10.1594/PANGAEA.923109">Hochmuth et al., 2020</a>). Here, we perform additional sensitivity experiments, in which we apply a fixed precipitation increase and extreme sub-shelf melt rates. The precipitation anomaly is calculated as 25% of the warm snapshot precipitation fields, sub-shelf melt rates are set to 400 m/yr.</p> <p> </p>
The commitment to global sea level rise over the next 500 years: exploring the threat of the Antarctic Ice Sheet to coastal infrastructure
<p>Within Australia alone, more than A$226 billion of coastal infrastructure is vulnerable to the anticipated rise in sea level by the end of the century. The IPCC Fifth Assessment Report concludes that the likely increase in global mean sea level during the 21st century ranges from 26-55 centimetres (under the low-end RCP2.6 climate scenario) to 45-82 centimetres (under the high-end RCP8.5 climate scenario). However, these projections do not take into account the potential for collapse of the marine-based sectors of the Antarctic Ice Sheet.</p> <p>Recent evidence has indicated that the IPCC projections may be under-estimates, with sea level increases of up to 2.5 metres possible by the end of the 21st century. Modelling studies have also demonstrated the potential for the Antarctic Ice Sheet to undergo irreversible collapse during the coming centuries, leading to dramatic increases in global sea level on time scales relevant to critical coastal infrastructure such as refineries and airports. The most extreme prediction is that Antarctica could contribute 15.65±2.00 metres to global sea level by the year 2500.</p> <p>Here, we combine climate modelling and ice sheet modelling to explore the evolution of the Antarctic Ice Sheet over the next 500 years under a range of climate scenarios. We run the models many times to take into account gaps in our understanding of ice sheet dynamics. This allows us to generate robust projections of the Antarctic contribution to global sea level from the present to the year 2500, complete with quantified confidence intervals. We conclude that the sea level contribution during the 21st century will be modest, consistent with the IPCC Fifth Assessment Report, but that melting of the Antarctic Ice Sheet will accelerate thereafter. By the year 2500, we predict that the Antarctic contribution to global sea level will be at least 5 metres.</p>
Additional steady-state simulations of Miocene Antarctic ice-sheet variability using 3D thermodynamical ice-sheet model IMAU-ICE
<div> </div> <div> <div> <div>We supplement our previous dataset (<a href="https://doi.pangaea.de/10.1594/PANGAEA.939114">doi:10.1594/PANGAEA.939114</a>), with six additional steady-state simulations of the Miocene Antarctic ice sheet using the reference Miocene settings.</div> <div> </div> <div>IMAU-ICE was run using a 40x40km grid covering the Antarctic continent. Initial conditions were obtained from reconstructions of the Antarctic bathymetry and bedrock topography pertaining to 23 to 24 million years (Myr) ago (dataset <a href="https://doi.pangaea.de/10.1594/PANGAEA.923109" target="_self">doi:10.1594/PANGAEA.923109</a>). The simulations were forced by climate input data obtained from GENESIS simulations with varying CO2 levels (280 to 840 ppm) and Antarctic ice sheet cover (no ice to a large East-Antarctic ice sheet), and with present-day insolation. We utilized a matrix interpolation method to construct the time-varying climate forcing, based on the prescribed CO2 levels and ice cover simulated by IMAU-ICE.</div> <div> </div> <div>For each simulation, we provide the run script, 1D output variables including CO2 level and the sea level contribution of the Antarctic ice sheet, and 3D output variables including ice thickness, bedrock and surface height, surface mass balance, basal mass balance, ice velocities, and ice temperatures. For more information, please contact L.B. Stap at l.b.stap@uu.nl.</div> </div> </div>
Dataset for "Mass loss of the Antarctic ice sheet until the year 3000 under a sustained late-21st-century climate"
<p>Dataset for the paper "Mass loss of the Antarctic ice sheet until the year 3000 under a sustained late-21st-century climate" (Journal of Glaciology, <a href="https://doi.org/10.1017/jog.2021.124">https://doi.org/10.1017/jog.2021.124</a>).</p> <p>Please see the README for details.</p> <p>V2: New version with ISMIP6-type variables and compressed netCDF files.<br> V1: Initial upload.</p> <p>* * * * * * *</p> <p>The following script may be used to download the entire content of the archive on a Unix/Linux system:</p> <p>#!/bin/bash<br> # --- download_all.sh ---<br> wget https://zenodo.org/record/6215117/files/_README.pdf<br> wget https://zenodo.org/record/6215117/files/run_specs_headers.zip<br> for aexp in hist ctrl_proj_long \<br> exp05_long exp06_long exp07_long exp08_long exp09_long exp10_long \<br> exp12_long exp13_long \<br> expA5_long expA6_long expA7_long expA8_long \<br> expB6_long expB7_long expB8_long expB9_long expB10_long; do<br> wget https://zenodo.org/record/6215117/files/${aexp}.zip<br> done<br> for aexp in abuc_long abuciso_long \<br> abuk_long abukiso_long \<br> abum_long abumiso_long; do<br> wget https://zenodo.org/record/6215117/files/${aexp}.zip<br> done</p> <p>* * * * * * *</p> <p>Users should cite the original publication when using all or parts of these data.<br> </p>
IODP Expedition 382: Supplementary Tables for "Episodes of early Pleistocene West Antarctic Ice Sheet retreat recorded by Iceberg Alley sediments"
<p>IODP Expedition 382: Supplementary Tables for "Episodes of early Pleistocene West Antarctic Ice Sheet retreat recorded by Iceberg Alley sediments"</p> <p>Includes SEM QEMSCAN® and <sup>40</sup>Ar/<sup>39</sup>Ar data for International Ocean Discovery Program (IODP) Expedition 382 Site U1538. Also includes a movie of a 3D-volume realization of an iceberg-rafted sedimentary layer from this site based on non-destructive X-ray microtomography imaging.</p> <p> </p> <p><strong>Data Set Captions:</strong></p> <p> </p> <p><strong>Data Set S1. </strong>Modal mineralogy data based on QEMSCAN® analyses, which infer minerals from chemistry. The mineral name assignations for each chemistry-based category stated in this table are aided by visual (microscope-based) inspection of the raw sieved samples.</p> <p><strong>Data Set S2. </strong>Mineral association data based on QEMSCAN® analyses. Please read data in columns, mineral against mineral (down then across left). These data define what touches what in the sample and is displayed as a percentage. Association refers to adjacency. Two minerals are “associated” if a pixel of one of the minerals occurs adjacent to a pixel of the other mineral. iExplorer software used scans the measured particles horizontally, from left to right, counting the associations that occur in the images (so the more pixels/closer the x-ray spacing the more accurate the data). Each column is independent. That is, it is split into a percentage of what touches what, so it is not expected that any two minerals’ data are reciprocal. The background category primarily reflects the free boundaries of ‘grains’ rather than liberated grains/particles. While it may provide an indicator of liberation, it does not represent liberation since it does not describe ‘particles’ which are made up of mineral grains. Inclusions and composite particles are therefore not described. Please consider the modal mineralogy (Tab. S1) when examining these mineral association data.</p> <p><strong>Data Set S3. </strong>Lithotyping data based on QEMSCAN® analyses. Particles have been digitally filtered using a set of lithotype rules (also displayed in this data set). These rules are based on the mineral grains in the particles themselves and use their area percent within each particle and their size in microns. The lithotype names stated here are largely assigned based on the dominant mineral grain in each category.</p> <p><strong>Data Set S4. </strong>40Ar/39Ar ages of individual sand-sized hornblende and mica. See main text for method used to generate these ages.</p> <p><strong>Data Set S5.</strong> Ties to place Hole U1538A NGR data on Dove Basin Stack (Reilly et al., 2021) depths.</p> <p><strong>Movie S1. </strong>3D-volume realization based on non-destructive X-ray microtomography imaging of a centimeter-scale iceberg-rafted debris-rich layer in Hole U1538A-36X-3W. 3D images were generated using a helical scanning trajectory that allows for long scan sequences and fast acquisition time. Based on the sample geometry, a voxel (pixel) resolution of ~14-μm was achieved. The 7000+ projection images were reconstructed to produce a 3D volume of image intensities (where higher values indicate greater x-ray attenuation). Avizo software was used for 3D segmentation and volume rendering to visualize gravel and sand to create this animation. The different colors assigned to each clast were chosen arbitrary.</p>
Model Output and Figure Scripts for: "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records"
<p>New climate model output and figure scripts for the paper "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records".</p>
Antarctic ice sheet daily surface melt detection from ASCAT (2007-2022)
<p>Antarctic ice sheet-wide surface melt detection using enhanced resolution ASCAT C-band radar scatterometer data. Data are daily temporal resolution spanning 2007-2022 and gridded at 4.45 km. Melt detection approach follows Trusel et al., (2012) with updates to threshold and masking procedures. These data were used as a binary melt presence/absence estimate and a predictor in a machine learning-based estimation of Antarctic Peninsula surface meltwater production (https://zenodo.org/record/7995543). </p> <p>Please reach out to Luke Trusel with any questions!</p>
Dataset for "Future projections for the Antarctic ice sheet until the year 2300 with a climate-index method"
<p>Dataset for the paper "Future projections for the Antarctic ice sheet until the year 2300 with a climate-index method" (Journal of Glaciology, <a href="https://doi.org/10.1017/jog.2023.41">doi: 10.1017/jog.2023.41</a>).</p> <p>Please see the README for details.</p> <p>V1.1: Run-specs header files for SICOPOLIS added. README updated.<br>V1: Initial upload.</p> <p>* * * * * * *</p> <p>Users should cite the original publication when using all or parts of these data.</p>
Antarctic Ice Sheet grounding line discharge from 1996 to 2024
<p>This dataset provides estimates of grounding line discharge from the Antarctic Ice Sheet and all of it's drainage basins, as described in the following pre-print (under review):</p> <p>Davison, B. J., Hogg, A. E., Slater, T., Rigby, R., and Hansen, N.: Antarctic Ice Sheet grounding line discharge from 1996–2024, Earth Syst. Sci. Data, 17, 3259–3281, https://doi.org/10.5194/essd-17-3259-2025, 2025.</p> <p>Check the README/UserGuide for summaries of what each .zip file includes</p> <p> </p> <p><strong>Update notes</strong></p> <ul> <li>Updated through November 2024</li> <li>Added BedMap3 </li> </ul> <p> </p> <p>Any questions, comments or suggestions, send them to: b.j.davison@sheffield.ac.uk</p> <h3> </h3> <p> </p>
Data set: "Higher Antarctic ice sheet accumulation and surface melt rates revealed at 2 km resolution"
<p>This data set includes the materials required to reproduce the figures and tables presented in the study: "Higher Antarctic ice sheet accumulation and surface melt rates revealed at 2 km resolution". The data consist of:</p><p> </p><p><strong>ASCII files:</strong></p><ol><li><strong>SMB-ANT-Sectors-1979-2021-RACMO2.3p2-ERA5-2km.txt</strong>: time series of Antarctic sector-integrated annual SMB<strong> (Gt per year)</strong> from ERA5-forced RACMO2.3p2 at 27 km, statistically downscaled to 2 km resolution (1979-2021).</li><li><strong>Melt-ANT-Sectors-1979-2021-RACMO2.3p2-ERA5-2km.txt:</strong> time series of Antarctic sector-integrated annual surface melt (Gt per year) from ERA5-forced RACMO2.3p2 at 27 km, statistically downscaled to 2 km resolution (1979-2021).</li><li><strong>Melt-ANT-Sectors-1950-2014-RACMO2.3p2-CESM2-HIST-2km.txt:</strong> time series of Antarctic sector-integrated annual surface melt from CESM2-forced RACMO2.3p2 historical reconstruction (HIST), statistically downscaled to 2 km resolution (1950-2014).</li><li><strong>Melt-ANT-Sectors-2015-2099-RACMO2.3p2-CESM2-SSP126-2km.txt:</strong> time series of Antarctic sector-integrated annual surface melt from CESM2-forced RACMO2.3p2 SSP1-2.6 projection (SSP126), statistically downscaled to 2 km resolution (2015-2099).</li><li><strong>Melt-ANT-Sectors-2015-2099-RACMO2.3p2-CESM2-SSP245-2km.txt:</strong> time series of Antarctic sector-integrated annual surface melt from CESM2-forced RACMO2.3p2 SSP2-4.5 projection (SSP245), statistically downscaled to 2 km resolution (2015-2099).</li><li><strong>Melt-ANT-Sectors-2015-2099-RACMO2.3p2-CESM2-SSP585-2km.txt:</strong> time series of Antarctic sector-integrated annual surface melt from CESM2-forced RACMO2.3p2 SSP5-8.5 projection (SSP585), statistically downscaled to 2 km resolution (2015-2099).</li></ol><p>Antarctic sectors include the Antarctic Peninsula (APIS), the West Antarctic ice sheet (WAIS), the East Antarctic ice sheet (EAIS), the grounded Antarctic ice sheet (AIS), the floating ice shelves (Ice shelves), and the whole of Antarctica (ANT) including both the AIS and Ice shelves. The APIS, WAIS, EAIS and AIS sectors include land ice from neighbouring Antarctic islands.</p><p> </p><p><strong>Netcdf files:</strong></p><ol><li><strong>smb_rec.1979-2021.BN_RACMO2.3p2_ANT27_ERA5-3h.AIS.2km.YY.nc: </strong>map of annual SMB (kg per m² or mm w.e. per year) from ERA5-forced RACMO2.3p2 at 27 km, statistically downscaled to 2 km resolution, covering the whole of Antarctica (1979-2021).</li><li><strong>snowmelt.1979-2021.BN_RACMO2.3p2_ANT27_ERA5-3h.AIS.2km.YY.nc: </strong>map of annual surface melt (kg per m² or mm w.e. per year) from ERA5-forced RACMO2.3p2 at 27 km, statistically downscaled to 2 km resolution, covering the whole of Antarctica (1979-2021).</li><li><strong>snowmelt.1950-2014.BN_RACMO2.3p2_ANT27_CESM2_HIST.AIS.2km.YY.nc: </strong>map of annual surface melt (kg per m² or mm w.e. per year) from CESM2-forced RACMO2.3p2 historical reconstruction (HIST), statistically downscaled to 2 km resolution, covering the whole of Antarctica (1950-2014).</li><li><strong>snowmelt.2015-2099.BN_RACMO2.3p2_ANT27_CESM2_SSP126.AIS.2km.YY.nc: </strong>map of annual surface melt (kg per m² or mm w.e. per year) from CESM2-forced RACMO2.3p2 SSP1-2.6 projection (SSP126), statistically downscaled to 2 km resolution, covering the whole of Antarctica (2015-2099).</li><li><strong>snowmelt.2015-2099.BN_RACMO2.3p2_ANT27_CESM2_SSP245.AIS.2km.YY.nc: </strong>map of annual surface melt (kg per m² or mm w.e. per year) from CESM2-forced RACMO2.3p2 SSP2-4.5 projection (SSP245), statistically downscaled to 2 km resolution, covering the whole of Antarctica (2015-2099).</li><li><strong>snowmelt.2015-2099.BN_RACMO2.3p2_ANT27_CESM2_SSP585.AIS.2km.YY.nc: </strong>map of annual surface melt (kg per m² or mm w.e. per year) from CESM2-forced RACMO2.3p2 SSP5-8.5 projection (SSP585), statistically downscaled to 2 km resolution, covering the whole of Antarctica (2015-2099).</li><li><strong>ANT_masks.2km.nc</strong>: file including the grounded AIS mask (AIS), Antarctic sectors mask (Sectors), floating ice shelves mask (Shelves), surface elevation down-sampled from REMA (Topography), latitude and longitude on the 2 km grid<strong>. </strong>The sector mask includes: 0 – Ocean, 1 – APIS, 2 – WAIS, 3 – EAIS, 4 – APIS islands, 5 – WAIS islands, 6 – EAIS islands, and 7 – ice shelves.<strong> </strong></li></ol><p>The projection used for statistical downscaling is Polar Stereographic South (EPSG:3031) with a spatial resolution of 2 km x 2 km. </p><p> </p><p><strong>Additional data: </strong>The gridded, daily downscaled SMB data sets from the ERA-forced RACMO2.3p2 simulation, and the CESM2-forced RACMO2.3p2 projections under a low-end SSP1-2.6, moderate SSP2-4.5 and high-end SSP5-8.5 warming scenario are freely available from the authors upon request and without conditions (contact: bnoel@uliege.be). Besides SMB, the data sets include total precipitation (snow and rain), snowfall, total melt (snow and ice), runoff, refreezing and retention, drifting snow erosion, and total sublimation (surface and drifting snow) at 2 km horizontal resolution. </p><p> </p><p><strong>Abstract:</strong> Antarctic ice sheet (AIS) mass loss is predominantly driven by increased solid ice discharge, but its variability is governed by surface processes. Snowfall fluctuations control the surface mass balance (SMB) of the grounded AIS, while meltwater ponding can trigger ice shelf collapse potentially accelerating discharge. Surface processes are essential to quantify AIS mass change, but remain poorly represented in climate models typically running at 25-100 km resolution. Here we present SMB and surface melt products statistically downscaled to 2 km resolution for the contemporary climate (1979-2021) and low, moderate and high-end warming scenarios until 2100. We show that statistical downscaling modestly enhances contemporary SMB (3%), which is sufficient to reconcile modelled and satellite mass change. Furthermore, melt strongly increases (46%), notably near the grounding line, in better agreement with in-situ and satellite records. The melt increase persists by 2100 in all warming scenarios, revealing higher surface melt rates than previously estimated.</p>
Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model
<p>=========================================================================<br>Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model<br>=========================================================================</p><p>-----------------------<br>INTRODUCTION<br>-----------------------</p><p>This dataset contains the data and scripts required to reproduce the figures and tables presented in the study:<br>"Disentangling the drivers of future Antarctic ice loss with a historically-calibrated ice-sheet model" in <i>The Cryosphere</i>.</p><p>We perform an ensemble of simulations of the Antarctic ice sheet between 1950 and 3014, forced by a panel of CMIP6 climate models, starting from present-day geometry with the Kori-ULB ice-sheet model v0.9. We calibrate our ensemble in a Bayesian framework to produce observationally-calibrated Antarctic projections used to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge on the one hand, and the surface mass balance on the other. All simulations are performed at a spatial resolution of 16 km.</p><p>Hindcasts of the behaviour of the AIS over the period 1950-2014 CE are reproduced using changes in oceanic and atmospheric boundary conditions derived from the CMIP5 climate model NorESM1-M. As of the year 2015 CE, climate projections derived from a subset of CMIP6 climate models (MRI-ESM2-0, IPSL-CM6A-LR, CESM2-WACCM and UKESM1-0-LL) are used as forcing until the year 2300 CE. Afterwards, no climate trend is applied. The forcing applied is derived from both the Shared Socioeconomic Pathways (SSP) 5-8.5 and 1-2.6 scenarios. </p><p>------------------------------<br>PROVIDED SCRIPTS: <br>------------------------------</p><p> - 'KoriModelAll.m' and 'KoriInputParams.m': Kori-ULB ice flow model (more info at https://github.com/FrankPat/Kori-ULB)<br> - 'Compute_Bayesian_Weight.m': calculation of the ensemble likelihood weights used in the Bayesian calibration.<br> - 'Plot_parameter_space_distributions.m': calculation and plots of prior and posterior parameter probability distributions.<br> - 'Plot_sea_level_distributions.m': calculation and plots of prior and posterior sea-level distributions.<br> - 'Plot_mass_balance_components_distributions.m': calculation and plots of mass balance components distributions.<br> - 'Plot_mean_thickness_change.m': calculation and plots of calibrated mean thickness change.<br> - 'Plot_ungrounded_probability.m': calculation and plots of the marginal probability of being ungrounded.<br> - 'Plot_SMB_sensitivity.m': Calculation and plots of surface mass balance sensitivity.<br> - 'run_MISMIPplus.m' and 'MISMIPplus.m': run and compare MISMIP+ experiment</p><p>-------------------------<br>PROVIDED DATA: <br>-------------------------</p><ul><li>'LHSensemble.mat': 100x9 matrices containing the values of the 100-member ensemble sampled (using maximin Latin Hypercube) within the parameter space in Table 1.<ul><li>1rst column ((:,1)) contains values of atmospheric present-day climatology (CLIMatm): MARv3.11 (1) - RACMOv2.3p2 (2)</li><li>2nd column ((:,2)) contains values of oceanic present-day climatology (CLIMocn): Jourdain2020 (1) - Schmidtko2014 (2)</li><li>3rd column ((:,3)) contains values of the atmospheric lapse rate (°C/km)</li><li>4th column ((:,4)) contains values of the thickness of the thermally-active layer influencing surface refreezing (m)</li><li>5th column ((:,5)) contains values of the contains values of the Degree day factor for the melting of ice (mm/PDD)</li><li>6th column ((:,6)) contains values of the contains values of the Degree day factor for the melting of snow (mm/PDD)</li><li>7th column ((:,7)) contains values of the applied Sub-shelf melt parameterisation: Quadratic-local Antarctic slope parameterisation (1) - PICO model (2) - Plume model (3) - ISMIP6 Nonlocal quadratic parameterisation (4) - ISMIP6 Nonlocal quadratic parameterisation including dependency on local slope (5)</li><li>8th column ((:,8)) contains values of the effective ice-ocean heat flux: [0.1 x 10^-5 - 10 x 10^-5] m/s for gammaT* in PICO - [1 x 10^-4 - 10 x 10^-4] for Cd^1/2Gamma_TS in Plume - [1 x 10^-4 - 10 x 10^-4] for K in Quadratic-local Antarctic slope parameterisation - [1 x 10^4 - 4 x 10^4] m/yr for gamma0 in ISMIP6 Nonlocal quadratic parameterisation - [1 x 10^6 - 4 x 10^6] m/yr for gamma0 in ISMIP6 Nonlocal quadratic parameterisation with slope dependency</li><li>9th column ((:,9)) contains values of the CMIP6 climate model applied for climate forcing: MRI-ESM2-0 (1) - UKESM1-0-LL (2) - CESM2-WACCM (3) - IPSL-CM6A-LR (4)<br><br>'LHval' and 'LHS' contain the absolute values and the values of the parameters scaled linearly between 0 and 1 (0: minimum value, 1:maximum value) of the nine parameters, respectively.<br> </li></ul></li><li>'HIST_ENSEMBLE_DATA.mat' contains the following variables describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014).<ul><li>H_ensemble: 4D matrix of dimension [X, Y, snap_time, ensemble member] with ice thickness field (in meters) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid.</li><li>MASK_ensemble: 4D matrix of dimension [X, Y, snap_time, ensemble member] with grounded mask field (in meters) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid. <br>It distinguishes grounded ice (1: grounded) from ocean or floating ice (0: ocean/floating).</li><li>mbcomp_ensemble: 3D matrix of dimension [time, mbcomp, ensemble member] with timeseries (yearly values at years time) of various mass balance components for the 100 ensemble members (in gigatons per year, Gt/yr). <br>The components mbcomp include the following ice-sheet aggregated and grounded ice sheet components:<br> (1) Ice-sheet aggregated surface mass balance<br> (2) Ice-sheet aggregated accumulation<br> (3) Ice-sheet aggregated surface melt<br> (4) Ice-sheet aggregated runoff<br> (5) Ice-sheet aggregated rain<br> (6) sub-shelf melt<br> (7) dynamic ice loss (calving)<br> (8) surface mass balance over the grounded ice sheet<br> (9) accumulation over the grounded ice sheet<br> (10) surface melt over the grounded ice sheet<br> (11) runoff over the grounded ice sheet<br> (12) rain over the grounded ice sheet <br> (13) Net mass balance (rate of HAF change)</li><li>SLC_ensemble: 2D matrix of dimension [ensemble member, time] with timeseries (yearly values at years time) of the ice-sheet sea-level contribution (in m) <br> </li></ul></li><li>'HIST_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK.mat': same as 'HIST_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when neglecting the melt-elevation feedback.<br> </li><li>'HIST_ENSEMBLE_DATA_HYDROFRAC.mat': same as 'HIST_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).<br> </li><li>'CONTROL_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 when considering constant present-day conditions as of the year 2015.<br> </li><li>'SSP126_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP1-2.6 scenario.<br> </li><li>'SSP585_ENSEMBLE_DATA.mat': contains the variables H_ensemble, MASK_ensemble, mbcomp_ensemble and SLC_ensemble (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario. It also contains the variable Runoff_ensemble, a 4D matrix of dimension [X, Y, snap_time, ensemble member] with surface runoff field (in m/yr i.e.) for the 100 ensemble members at different years (snap_time). X and Y represent spatial coordinates on a grid, as used in Fig. 7.<br> </li><li>'SSP585_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback.<br> </li><li>'SSP585_ENSEMBLE_DATA_HYDROFRAC.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).<br> </li><li>'SSP585_ENSEMBLE_DATA_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when considering constant oceanic present-day conditions as of the year 2015.<br> </li><li>'SSP585_ENSEMBLE_DATA_NO_ELEVATION_FEEDBACK_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback and considering constant oceanic present-day conditions as of the year 2015.<br> </li><li>'SSP585_ENSEMBLE_DATA_OCEAN_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario considering constant atmospheric present-day conditions as of the year 2015.<br> </li><li>'HIST_ENSEMBLE_DATA_BASIN.mat' contains the following variables describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) integrated over 27 drainage basins (http://imbie.org/imbie-2016/drainage-basins/).<ul><li>SLC_ensemble_basin: 3D matrix of dimension [basin, ensemble member, time] with timeseries (yearly values at years time) of the ice-sheet sea-level contribution (in m) by basin</li><li>mbcomp_ensemble_basin: 4D matrix of dimension [basin, time, mbcomp, ensemble member] with timeseries (yearly values at years time) of various mass balance components for the 100 ensemble members (in gigatons per year, Gt/yr) by basin. The components mbcomp include the same ice-sheet aggregated and grounded ice-sheet components as in 'HIST_ENSEMBLE_DATA.mat'.<br> </li></ul></li><li>'HIST_ENSEMBLE_DATA_BASIN_NO_ELEVATION_DATA.mat': same as 'HIST_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when neglecting the melt-elevation feedback.<br> </li><li>'HIST_ENSEMBLE_DATA_BASIN_HYDROFRAC.mat': same as 'HIST_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the historical period (1950-2014) when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).<br> </li><li>'SSP126_ENSEMBLE_DATA_BASIN.mat': contains the variables SLC_ensemble_basin and mbcomp_ensemble_basin (as in 'HIST_ENSEMBLE_DATA°BASIN') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP1-2.6 scenario.<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN.mat': contains the variables SLC_ensemble_basin and mbcomp_ensemble_basin (as in 'HIST_ENSEMBLE_DATA') describing the evolution of the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario.<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN_NO_ELEVATION_FEEDBACK.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under a SSP5-8.5 scenario when neglecting the melt-elevation feedback.<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN_HYDROFRAC.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when including surface melt-driven hydrofracturing of the ice shelves (estimated following Pollard et al., 2015).<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when considering constant oceanic present-day conditions as of the year 2015.<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN_NO_ELEVATION_FEEDBACK_ATM_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario when neglecting the melt-elevation feedback and considering constant oceanic present-day conditions as of the year 2015.<br> </li><li>'SSP585_ENSEMBLE_DATA_BASIN_OCEAN_ONLY.mat': same as 'SSP585_ENSEMBLE_DATA_BASIN.mat' for the 100-member ensemble of simulations of the Antarctic ice sheet over the period 2015-3014 under an SSP5-8.5 scenario considering constant atmospheric present-day conditions as of the year 2015.<br> </li><li>'GCM_SSPXXX_mean_aTs.mat': Timeseries of the regionally-averaged (between 90–60°S) annual near-surface (2-m) air temperature anomaly (°C) projected by the climate model 'GCM' from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) between 2015 and 2300 under the SSPXXX emission scenario, compared to the 1995-2014 reference period. SSPXXX may be 'SSP126' and 'SSP585' and GCM may be 'MRI-ESM2-0', 'CESM2-WACCM', 'IPSL-CM6A-LR', or 'UKESM1-0-LL'.<br> </li><li>'CALIBRATION DATA.mat': values ('val'), uncertainty ('sigma'), beginning ('year1') and end ('year2') of the average time period of the 12 regionally and temporally aggregated IMBIE data used in the Bayesian calibration (Table 2 in this study, coming from Table 2 from Otosaka et al., 2023)<br> </li><li>'INIT_MAR_aNorESM1-M_1950.mat' and 'INIT_RACMO_aNorESM1-M_1950.mat': Ice-sheet initial states at year 1950 obtained with the 1995-2014 atmospheric climatology from MARv3.11(Kittel eta l.,2021) or RACMOv2.3p2 (van Wessem et al., 2018), respectively, adjusted with a 1945-1955 anomaly from NorESM1-M. H is the ice thickness (in meters), B is the bedrock topography (in meters), and u is the surface velocity (in m/yr). These files were provided as input files to Kori-ULB to produce the projections. More info on the input files and their variables can be found here: https://github.com/FrankPat/Kori-ULB.</li></ul><p>----------------------------------------------------------<br>MATLAB FUNCTIONS USED IN SCRIPTS: <br>----------------------------------------------------------</p><p>- imagescn: imagesc with transparent NaNs, by Chad Greene (2023), downloaded from MATLAB Central File Exchange (https://www.mathworks.com/matlabcentral/fileexchange/61293-imagescn), <br>- brewermap: provides all ColorBrewer colorschemes for MATLAB, by Stephen23. Downloaded from https://github.com/DrosteEffect/BrewerMap.<br>- crameri: returns perceptually-uniform scientific colormaps created by Fabio Crameri (requires CrameriColourMaps8.0.mat)</p><p>----------------------------------------------------------------------------------<br>EXTERNAL DATA NOT CONTAINED IN THIS REPOSITORY:<br>----------------------------------------------------------------------------------</p><p>- BedMachine data used for the present-day grounding lines in Figures 2 and 7: It is BedMachine v2 (Morlighem et al., 2020) and can be found here: https://nsidc.org/data/nsidc-0756/versions/2.<br>- The delineation of the 27 Zwally Basins used to identify and separate the West and East Antarctic ice sheets and the Antarctic Peninsula can be found at http://imbie.org/imbie-2016/drainage-basins/<br>- Outputs from MAR(CNRM-CM6-1) and MAR(CESM2) used in Figures 7 and S10. The data can be downloaded at 10.5281/zenodo.4529004 and 10.5281/zenodo.4529002, respectively. It was then interpolated to the 16-km grid used by Kori-ULB.<br>- CESM2-WACCM outputs used in Figure 7 were downloaded from the CMIP6 search interface (https://esgf-node.llnl.gov/search/cmip6/) and interpolated to the 16-km grid used by Kori-ULB.<br>- The CMIP6 forcing data used in this study (and plotted in Figures S6 and S7) are accessible through the CMIP6 search interface (https://esgf-node.llnl.gov/search/cmip6/). They have been interpolated to the interpolated to the 16-km grid used by Kori-ULB.</p><p>---------------------<br>REFERENCES: <br>---------------------</p><p>Kittel, C., Amory, C., Agosta, C., Jourdain, N. C., Hofer, S., Delhasse, A., Doutreloup, S., Huot, P.-V., Lang, C., Fichefet, T., and Fettweis, X.: Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet, The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, 2021.</p><p>Morlighem, M., Rignot, E., Binder, T. et al. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet. Nat. Geosci. 13, 132–137 (2020). https://doi.org/10.1038/s41561-019-0510-8</p><p>Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023.</p><p>Pollard, D., DeConto, R. M., and Alley, R. B.: Potential Antarctic Ice Sheet retreat driven by hydrofracturing and ice cliff failure, Earth and Planetary Science Letters, 412, 112–121, https://doi.org/10.1016/j.epsl.2014.12.035, 2015.<br> <br>van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018.</p>
Future freshwater fluxes from the Antarctic ice sheet
<p>===============================================================<br>Future freshwater fluxes from the Antarctic ice sheet (dataset)<br>===============================================================</p> <p>-----------------------<br>INTRODUCTION<br>-----------------------</p> <p>This dataset contains historically-calibrated projections of Antarctic freshwater fluxes (ice-shelf melting, iceberg calving, and surface meltwater runoff) under low and very-high emission scenarios for 27 drainage basins and 5 ocean sectors until 2300.</p> <p>We perform, with the Kori-ULB ice-sheet model v0.91, an ensemble of historically-calibrated simulations of the Antarctic ice sheet between 1990 and 2300 forced by atmospheric and oceanic projections inferred from a subset of models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under low- and very high-emission scenarios. </p> <p>We refer to the associated manuscript for more information on the applied methodology.</p> <p>-------------------------<br>PROVIDED DATA<br>-------------------------</p> <ul> <li>'<em>SSP126_FWF_1990_2300_ZwallyBasins.nc</em>' and '<em>SSP585_FWF_1990_2300_ZwallyBasins.nc</em>' each contain yearly timeseries of the [5 25 50 75 95] percentiles for the calibrated probabilistic projections of Antarctic net mass balance, surface mass balance, sub-shelf melt, and calving fluxes (in Gt/yr) for each of the 27 Zwally drainage basins (see http://imbie.org/imbie-2016/drainage-basins/) under a SSP1-2.6 and SSP5-8.5 scenario, respectively.<br><br></li> <li>'<em>SSP126_FWF_1990_2300_OceanSectors.nc</em>' and '<em>SSP585_FWF_1990_2300_OceanSectors.nc</em>' each contain yearly timeseries of the [5 25 50 75 95] percentiles for the calibrated probabilistic projections of Antarctic net mass balance, surface mass balance, sub-shelf melt, and calving fluxes (in Gt/yr) for each of the 5 ocean sectors (Weddell Sea, Indian Ocean, western Pacific Ocean, Ross Sea, Amundsen & Bellingshausen Sea) under a SSP1-2.6 and SSP5-8.5 scenario, respectively.<br><br></li> <li>'<em>SSP126_FWF_1990_2300_AIS.nc</em>' and '<em>SSP585_FWF_1990_2300_AIS.nc</em>' each contain yearly timeseries of the [5 25 50 75 95] percentiles for the calibrated probabilistic projections of Antarctic net mass balance, surface meltwater runoff, sub-shelf melt, and calving fluxes (in Gt/yr) for the Antarctic Ice Sheet under a SSP1-2.6 and SSP5-8.5 scenario, respectively.</li> </ul>
Economic impacts of melting of the Antarctic Ice Sheet
<p>Dataset supporting figures and tables in Dietz, Simon and Koninx, Felix (forthcoming), "Economic impacts of melting of the Antarctic Ice Sheet", Nature Communications</p>
Subglacial hydrology modulates basal sliding response of the Antarctic ice sheet to climate forcing
<p><strong><em>Kazmierczak22_data.zip</em></strong><strong> contains the </strong><strong>dataset for the publication </strong><strong>« </strong>Subglacial hydrology modulates basal sliding response of the Antarctic ice sheet to climate forcing » <strong>and </strong><strong>the <em>MATLAB</em> codes used to create the figures appearing in the paper. For more details, please, open the <em>Read me.txt</em> file. </strong></p>
Data for "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model"
<p>Data to accompany:</p> <p>O’Neill, J.F., Edwards, T.L., Martin, D.F., Shafer, C., Cornford, S.L., Seroussi, H.L., Nowicki, S., Adhikari, M., Gregoire, L.J.. (2024). "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model in the Cryosphere". <em>The Cryosphere</em>. DOI: 10.5194/egusphere-2024-441 (preprint)</p> <p>Zipped directories called ismip6_<em>expname</em>_8km containing NetCDFs of output data from each experiment, on an 8 km EPSG3031 polar stereographic common grid for ISMIP6. Variable names are the same as those used for ISMIP6 i.e: land ice mass (lim), land ice mass above floatation (limnsw), floating area (iareaf), grounded area (iareag), thickness (lithk), x component of mean velocity (xvelmean), y component of mean velocity (yvelmean), basal mass flux (libmassbffl), acabf (surface mass balance), sftflf (floating ice mask), sftgrf (grounded ice mask), sftgif (ice mask), dlithkdt (ice thickness imbalance), base (elevation at base of ice sheet) and orog (surface elevation of ice sheet). These latter two are only included for the experiments plotted in Figure 11 in "ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model in the Cryosphere".</p> <p> </p> <p>Also included are csv data for summary variables, masked regionally, and by sectors detailed in the main paper. Please contact J ONeill with any questions or requests. </p>
Datasets used in van den Akker et al (2024) 'Present day mass loss rates are a precursor precursor for West Antarctic Ice Sheet Collapse
<p>This repository contains the default initialization and the continuation runs shown in the paper. </p>
Antarctic Ice Sheet simulations driven by CMIP6 climate models under historical and SSP5-8.5 scenarios
<p><strong>Antarctic Ice Sheet simulations driven by CMIP6 climate models under historical and SSP5-8.5 scenarios</strong></p> <p>This dataset contains output ice sheet model runs forced by climate boundary conditions provided by CMIP6 climate model output. Each experiment set is archived in separate compressed tar.gz files. </p> <p>Description of the experiment sets, including the model setup, key parameters, climate forcings, and their main objectives are documented in Table 1 of Li, DeConto, Pollard (2023) Climate model differences contribute deep uncertainty in future Antarctic ice loss, Science Advances.</p> <p>Two kinds of output are included in each ice sheet run: fort.22 files contain time series of several key variables for the Antarctic Ice Sheet (area, volume, sea-level equivalent, etc.); fort.92.nc files contain 2D and 3D fields such as ice thickness and velocity at specific time slices.</p> <p> </p> <p> </p>
Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes
<p>These files accompany the paper: 'Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes'.</p> <p>Please cite the accompanying paper if you find this data useful.</p> <p><strong>Contents</strong><br> This dataset contains netCDF files with all the mean sea level scenarios and the accompanying uncertainties. The file 'esl_results.xlsx' contains the estimated GPD parameters for each tide-gauge site, as well as the estimated 100-year amplification factor and allowance. The files result_concise_table_af.pdf and result_concise_table_al.pdf contain easy-to-access overviews of the amplification factors and allowances sorted per station.<br> </p> <p>(c) 2019 California Institute of Technology. U.S. Government sponsorship acknowledged.<br> This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</p>
Results of ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century
<p>This archive provides the ice sheet model outputs produced as part of the publication "ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century", published in The Cryosphere, <a href="https://tc.copernicus.org/articles/14/3033/2020/">https://tc.copernicus.org/articles/14/3033/2020/</a></p> <p>Seroussi, H., Nowicki, S., Payne, A. J., Goelzer, H., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Albrecht, T., Asay-Davis, X., Barthel, A., Calov, R., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Larour, E., Leguy, G. R., Lowry, D. P., Little, C. M., Morlighem, M., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Schlegel, N.-J., Shepherd, A., Simon, E., Smith, R. S., Straneo, F., Sun, S., Trusel, L. D., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century, The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, 2020.</p> <p>Contact: Helene Seroussi, Helene.seroussi@jpl.nasa.gov</p> <p>Further information on ISMIP6 and ISMIP6 Antarctica Projections can be found here:<br> http://www.climate-cryosphere.org/activities/targeted/ismip6<br> http://www.climate-cryosphere.org/wiki/index.php?title=ISMIP6-Projections-Antarctica</p> <p>Users should cite the original publication when using all or part of the data. <br> In order to document CMIP6’s scientific impact and enable ongoing support of CMIP, users are also obligated to acknowledge CMIP6, ISMIP6 and the participating modeling groups.</p> <p>About the dataset:</p> <p>- The results are based on model output computed from the ISMIP6 native grids that vary between models. <br> - The results are calculated over the ice-covered area of Antarctica, corrected for map projection errors, ice sheet model specific densities taken into account.<br> - Results for the experiments 'exp*' are provided both as raw results and calculated as differences to the control experiment (ctrl_proj_open or ctrl_proj_std depending on the experiment). The later files are named with "minus_ctrl_proj" to indicate that the control run is substracted.<br> - Results for ctrl_proj_open, ctrl_proj_std, hist_open and hist_std are not corrected to remove the control run.</p> <p><br> ------------------------------------------------</p> <p>Directory structure:</p> <p>groupname1<br> modelname1<br> expid<br> computed_iareafl_AIS_groupname1_modelname1_expid.nc<br> computed_iareafl_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_iareagr_AIS_groupname1_modelname1_expid.nc<br> computed_iareagr_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_icearea_AIS_groupname1_modelname1_expid.nc<br> computed_icearea_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_ivol_AIS_groupname1_modelname1_expid.nc<br> computed_ivol_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_ivaf_AIS_groupname1_modelname1_expid.nc<br> computed_ivaf_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_smb_AIS_groupname1_modelname1_expid.nc<br> computed_smb_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_smbgr_AIS_groupname1_modelname1_expid.nc<br> computed_smbgr_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> computed_bmbfl_AIS_groupname1_modelname1_expid.nc<br> computed_bmbfl_minus_ctrl_proj_AIS_groupname1_modelname1_expid.nc<br> ...</p> <p>-------------------------------------------------</p> <p><br> Description of variables:</p> <p>icearea - ice area [m^2]<br> iareafl - floating ice area [m^2]<br> iareagr - grounded ice area [m^2]<br> ivol - ice volume [m^3]<br> ivaf - ice volume above floatation [m^3]<br> smb - spatially integrated surface mass balance [kg/s]<br> smbgr - spatially integrated surface mass balance over grounded ice [kg/s]<br> bmbfl - spatially integrated basal melt rate under floating ice (negative for melting ice) [kg/s]</p> <p>Variables per file:</p> <p>rhoi - model specific ice density [kg m-3]<br> rhow - model specific ocean water density [kg m-3]</p> <p>time - time, in years</p> <p>[variable] - global variable integrated over the Antarctica ice sheet<br> [variable]_region_1 - variable integrated over West Antarctica<br> [variable]_region_2 - variable integrated over East Antarctica<br> [variable]_region_3 - variable integrated over the Antarctic Peninsula<br> [variable]_sector_X - variable integrated over the X sector of the Antarctic ice sheet (18 sectors, from 1 to 18)</p> <p>--------------------------------------------------</p> <p><br> Data usage notice:<br> If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below.</p> <p>"We thank the Climate and Cryosphere (CliC) effort, which provided support for ISMIP6 through sponsoring of workshops, hosting the ISMIP6 website and wiki, and promoted ISMIP6. We acknowledge the World Climate Research Programme, which, through it's Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6."</p> <p>You should also refer to and cite the following papers:</p> <p>Seroussi, H., Nowicki, S., Payne, A. J., Goelzer, H., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Albrecht, T., Asay-Davis, X., Barthel, A., Calov, R., Cullather, R., Dumas, C., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Gregory, J. M., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huybrechts, P., Jourdain, N. C., Kleiner, T., Larour, E., Leguy, G. R., Lowry, D. P., Little, C. M., Morlighem, M., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Reese, R., Schlegel, N.-J., Shepherd, A., Simon, E., Smith, R. S., Straneo, F., Sun, S., Trusel, L. D., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., Zhao, C., Zhang, T., and Zwinger, T.: ISMIP6 Antarctica: a multi-model ensemble of the Antarctic ice sheet evolution over the 21st century, The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, 2020.</p> <p>Nowicki, S., Goelzer, H., Seroussi, H., Payne, A. J., Lipscomb, W. H., Abe-Ouchi, A., Agosta, C., Alexander, P., Asay-Davis, X. S., Barthel, A., Bracegirdle, T. J., Cullather, R., Felikson, D., Fettweis, X., Gregory, J. M., Hattermann, T., Jourdain, N. C., Kuipers Munneke, P., Larour, E., Little, C. M., Morlighem, M., Nias, I., Shepherd, A., Simon, E., Slater, D., Smith, R. S., Straneo, F., Trusel, L. D., van den Broeke, M. R., and van de Wal, R.: Experimental protocol for sea level projections from ISMIP6 stand-alone ice sheet models, The Cryosphere, 14, 2331–2368, https://doi.org/10.5194/tc-14-2331-2020, 2020.</p>
Results of ISMIP6 CMIP6 forced simulations: a multi-model ensemble of the Greenland and Antarctic ice sheet evolution over the 21st century
<p>This archive provides the ice sheet model outputs produced as part of the publication "Payne et al. 2021 Future sea level change under CMIP5 and CMIP6 scenarios from the Greenland and Antarctic ice sheets", published in GRL</p> <p>Contact: Tony Payne a.j.payne@bristol.ac.uk, Sophie Nowicki sophien@buffalo.edu, ismip6@gmail.com </p> <p><br> Further information on ISMIP6 can be found here:<br> http://www.climate-cryosphere.org/activities/targeted/ismip6<br> http://www.climate-cryosphere.org/wiki/index.php?title=ISMIP6-Projections-Antarctica<br> http://www.climate-cryosphere.org/wiki/index.php?title=ISMIP6-Projections-Greenland</p> <p>Data usage notice:<br> If you use any of these results, please acknowledge the work of the people involved in the process producing this data set. Acknowledgements should have language similar to the below (if you only use CMIP5 forcing, remove CMIP6 and vice versa).</p> <p>“We thank the Climate and Cryosphere (CliC) effort, which provided support for ISMIP6 through sponsoring of workshops, hosting the ISMIP6 website and wiki, and promoted ISMIP6. We acknowledge the World Climate Research Programme, which, through it's Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6."</p> <p>You should also refer to and cite the following papers:</p> <p>For Greenland datasets </p> <p>Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319</p> <p>Slater, D. A., Felikson, D., Straneo, F., Goelzer, H., Little, C. M., Morlighem, M., Fettweis, X., and Nowicki, S.: Twenty-first century ocean forcing of the Greenland ice sheet for modelling of sea level contribution , The Cryosphere, 14, 985–1008, https://doi.org/10.5194/tc-14-985-2020, 2020.</p> <p>Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: <br> Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020.</p> <p>For Antarctica datasets</p> <p>Seroussi, H., Nowicki, S., Simon, E., Abe-Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S. F., Quiquet, A., Reerink, T. J., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T.: initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6, The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, 2019.</p> <p>Jourdain, N. C., Asay-Davis, X., Hattermann, T., Straneo, F., Seroussi, H., Little, C. M., and Nowicki, S.: A protocol for calculating basal melt rates in the ISMIP6 Antarctic ice sheet projections, The Cryosphere, 14, 3111–3134, https://doi.org/10.5194/tc-14-3111-2020, 2020.</p> <p><br> Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020.</p> <p> </p>
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