Supplementary material for "Numerical issues in modeling ice sheet instabilities such as binge-purge type cyclic ice stream surging"
Notice bibliographique
Résumé
Running the models: GSM: A full description of the GSM with the associated code archive and complete documentation will soon be submitted and then linked here. We are happy to provide the code upon individual request. The input files used specifically for "Numerical issues in modeling ice sheet instabilities such as binge-purge type cyclic ice stream surging" are described here. The GSM uses bed masks to set the sediment cover of each grid cell. The bed masks for all four resolutions (25 km, 12.5 km, 6.25 km, and 3.125 km) with an abrupt transition between soft sediment and hard bedrock are: inputGSM01.bedMskLISsqHighRes25kmSymmetric.dat inputGSM02.bedMskLISsqHighRes12p5kmSymmetric.dat inputGSM03.bedMskLISsqHighRes6p25kmSymmetric.dat inputGSM04.bedMskLISsqHighRes3p125kmSymmetric.dat The GSM bed masks with a small (3.125 km) and wide (25 km) transition zone between soft sediment and hard bedrock are: inputGSM05.bedMskLISsqHighRes3p125kmSymmetricSmallSmoothTransition.dat inputGSM06.bedMskLISsqHighRes3p125kmSymmetricSmoothTransition.dat Similar to the sediment cover, the GSM uses a topography mask to set the bed elevation. The topography files with a small (3.125 km) and wide (25 km) transition zone between the pseudo-Hudson Strait and Hudson Bay at 200 m below sea level, the surrounding at sea level, and the ocean grid cells at 500 m below sea level are: inputGSM07.topo3p125kmSymmetricSmallSmooth.dat inputGSM08.topo3p125kmSymmetricSmooth.dat The GSM setup used here requires 9 input parameters. The parameters are read as parameter vectors from a parameter file. The GSM parameter vectors used in this paper are: 1.00 0.30 0.81 1.20 1.30 2.60 1.44 1.20 0.30 (parameter vector 00) 1.00 2.00 0.80 1.20 0.75 1.07 1.00 0.50 0.30 (parameter vector 01) 0.59 1.20 1.00 1.20 0.52 2.87 1.27 0.82 0.20 (parameter vector 02) 1.00 2.00 1.00 0.54 0.27 1.52 1.17 0.95 0.20 (parameter vector 03) 1.00 1.50 1.00 1.20 0.60 1.52 0.97 0.60 0.10 (parameter vector 04) C_rmu, C_fslid, lapsr, PDDmelt, hpre, PrecRef, rTnorth, n_b PISM: Instructions on how to install and run PISM can be found in the PISM online manual. The experiments in "Numerical issues in modeling ice sheet instabilities such as binge-purge type cyclic ice stream surging" were conducted with PISM v2.0.2. On a Unix/Linux-based system, the PISM base setup can be run by mpiexec -n 8 pismr -Mx 120 -My 120 -Mz 60 -Lz 1e4 -y 2e5 \ -Mbz 20 -Lbz 1000 \ -bootstrap -i inputFile.nc -o outputfFile.nc \ -stress_balance ssa+sia -stress_balance.sia.max_diffusivity 1e3 \ -adapt_ratio 0.01 \ -grid.registration center \ -hydrology null \ -extra_file extraOutputFile.nc -extra_vars thk,temppabase,velsurf_mag,velbar_mag,flux_mag,diffusivity,bmelt,taud_mag,tauc,tillphi,velbase_mag -extra_times \0:1000:2e5 \ -ts_file extraTimeSeriesFile.nc -ts_times 0:100:2e5" inputPISM01.pismInputFilesDist.py uses a parameter file (containing the parameter vectors) to create the inputFile.nc required in the command above. The PISM parameter vectors used in this paper are: 0.54 19.81 205.25 7.68e-12 236.14 9.01e-09 (parameter vector 00) 0.56 19.44 408.81 4.55e-12 232.60 9.45e-09 (parameter vector 01) 0.60 21.13 237.37 2.65e-12 221.58 3.05e-09 (parameter vector 02) 0.54 24.78 411.83 8.89e-12 239.09 5.88e-09 (parameter vector 03) 0.61 26.85 221.41 3.42e-12 223.38 4.70e-09 (parameter vector 04) 0.52 19.50 188.54 3.22e-12 236.63 7.92e-09 (parameter vector 05) 0.81 25.69 173.93 3.82e-12 242.02 1.97e-09 (parameter vector 06) 0.66 29.94 148.59 7.41e-12 224.49 9.31e-09 (parameter vector 07) 0.55 15.25 92.53 5.63e-12 244.18 4.42e-09 (parameter vector 08) 0.74 19.80 401.31 3.02e-12 228.42 3.58e-09 (parameter vector 09) soft, hard, Bmax, Sb, Tmin, St Analysis scripts to determine the surge characteristics (GSM and PISM) The analysis scripts (four Python and one Bash script) are used to conduct the analysis described in "Numerical issues in modeling ice sheet instabilities such as binge-purge type cyclic ice stream surging". analysis01.runPeaks.sh: Top-level bash script that sequentially runs all four python scripts. analysis02.rPeakidSQts.py: Identifies the surges (peaks) and calculates the surge characteristics for every parameter vector and model setup. analysis03.readStats.py: Takes the output of analysis02.rPeakidSQts.py and calculates the average (across all parameter vectors) change in surge characteristics between the base setup and every comparison model setup. analysis04.rRMSEmeanBIASidSQts.py: Calculates the ice volume RMSE (Root Mean Square Error) and mean bias for every parameter vector and model setup (compared to the base setup) analysis05.rmseMeanBias.py: Takes the output of analysis04.rRMSEmeanBIASidSQts.py and calculates the average (across all parameter vectors) ice volume RMSE and mean bias between the base setup and every comparison model setup. Video 01: Glacial Systems Model (GSM) - surge onset Shown are the ice sheet surface elevation (white/black contour lines), the Shallow Ice Approximation (SIA) part of the deformation work, the heating due to the Shallow Shelf Approximation (SSA) dynamics, the heat generated by basal shearing, the basal temperature with respect to the pressure melting point, the ice velocity at the base of the ice sheet in the x-direction (positive values represent eastward velocities), and the ice velocity at the base of the ice sheet in the y-direction (positive values represent northward flow) for parameter vector 1. The horizontal grid resolution is 3.125 km and the maximum model time step is 1 yr. The animation time step is 10 yr with a total run time of 200 yr. The animation is focused on the pseudo-Hudson Strait mouth with the ocean situated east of 450 km. The green and grey lines mark the warm-based area and the ice sheet margin, respectively. Note that the velocities in the GSM are defined on a staggered grid and the velocity fields in x- and y-direction are therefore shifted by half a grid cell length in x- and y-direction, respectively. Video 02: Glacial Systems Model (GSM) - surge propagation and termination Shown are the ice sheet surface elevation (white/black contour lines), the Shallow Ice Approximation (SIA) part of the deformation work, the heating due to the Shallow Shelf Approximation (SSA) dynamics, the heat generated by basal shearing, the basal temperature with respect to the pressure melting point, the ice velocity at the base of the ice sheet in the x-direction (positive values represent eastward velocities), and the ice velocity at the base of the ice sheet in the y-direction (positive values represent northward flow) for parameter vector 1. The horizontal grid resolution is 3.125 km and the maximum model time step is 1 yr. The animation time step is 10 yr with a total run time of 200 yr. The magenta line outlines the soft sediment pseudo-Hudson Bay and Hudson Strait area. The green and grey lines mark the warm-based area and the ice sheet margin, respectively. Note that the velocities in the GSM are defined on a staggered grid and the velocity fields in x- and y-direction are therefore shifted by half a grid cell length in x- and y-direction, respectively. Video 03: Glacial Systems Model (GSM) - abrupt vs. 25 km wide transition between a soft and hard bed Shown are the ice sheet surface elevation (white/black contour lines), the basal temperature with respect to the pressure melting point (left column), the ice velocity at the base of the ice sheet in the x-direction (center column, positive values represent eastward velocities), and the ice velocity at the base of the ice sheet in the y-direction (right column, positive values represent northward flow) for parameter vector 1. The upper row uses an abrupt transition between soft sediment and hard bedrock, whereas the bottom row has a 25 km wide transition zone. The horizontal grid resolution is 3.125 km and the maximum model time step is 1 yr. The animation time step is 10 yr with a total run time of 4 kyr. The magenta line outlines the soft sediment pseudo-Hudson Bay and Hudson Strait area. The hatched magenta area in the bottom row indicates the transition region surrounding the pseudo-Hudson Strait. The green and grey lines mark the warm-based area and the ice sheet margin, respectively. Note that the velocities in the GSM are defined on a staggered grid and the velocity fields in x- and y-direction are therefore shifted by half a grid cell length in x- and y-direction, respectively. Video 04: Glacial Systems Model (GSM) - pseudo-Hudson Bay and Hudson Strait topography - two different slopes Shown are the ice sheet surface elevation (white/black contour lines), the basal temperature with respect to the pressure melting point (left column), the ice velocity at the base of the ice sheet in the x-direction (center column, positive values represent eastward velocities), and the ice velocity at the base of the ice sheet in the y-direction (right column, positive values represent northward flow) for parameter vector 1. The upper row uses a 200 m deep pseudo-Hudson Bay and Hudson Strait topography with a 3.125 km transition zone (steep slope), whereas the bottom row has a 25 km wide transition zone (more gentle slope). The horizontal grid resolution is 3.125 km and the maximum model time step is 1 yr. The animation time step is 10 yr with a total run time of 4.5 kyr. The magenta line outlines the soft sediment pseudo-Hudson Bay and Hudson Strait area. The hatched magenta areas indicate the transition region (sediment and topography) surrounding the pseudo-Hudson Strait. The green and grey lines mark the warm-based area and the ice sheet margin, respec
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,790 | 0,389 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».