GENERAL INFORMATION 1. Title of Dataset: Data associated with: Seasonal acceleration of Petermann Glacier, Greenland, from changes in subglacial hydrology 2. Author Information: A. Principal Investigator Contact Information Name: Shivani Ehrenfeucht Institution: University of California- Irvine Email: sehrenfe@uci.edu B. Co-Author Name: Mathieu Morlighem Institution: Dartmouth College Email: Mathieu.Morlighem@dartmouth.edu C. Co-Author Name: Eric Rignot Institution: University of California- Irvine Email: erignot@uci.edu D. Co-Author Name: Christine Dow Institution: University of Waterloo Email: christine.dow@uwaterloo.ca E. Co-Author Name: Jeremie Mouginot Institution: Université Grenoble Alpes Email: Jeremie.mouginot@univ-grenoble-alpes.fr 3. Journal: Geophysical Research Letters 4. Created on 2022-01-21 --------------------------------------------------------------------------------------------------- DATA & FILE OVERVIEW ------------------------------ 1. Relationship Between Files: runme_GlaDS.m and runme_ISSM.m run the Ice-sheet and Sea-level System Model (ISSM) and the Glacier Drainage System Model (GlaDS) respectively. GlaDS is implemented within ISSM, which is open access and available for download at https://issm.jpl.nasa.gov/. These scripts were run using ISSM version 4.2 and MATLAB version R2021a. Directions for use: The runme MATLAB scripts run in a series of steps where each step creates and saves a model. Model output from runme scripts are located in the Models folder. Line 1 of both runme_GlaDS.m and runme_ISSM.m defines the step that will be run if the script is executed. For example, if line 1 of runme_GlaDS.m reads "steps = [1];" and then runme_GlaDS is executed, the code will run through the commands to generate the hydrology mesh contained within step 1 of the script and then save a model corresponding to step 1. Once a model for step 1 is saved, step 2 can be run by changing line 1 of runme_GlaDS.m to "steps = [2];" and then typing runme_GlaDS into the MATLAB consol. This will first load the model corresponding step 1, then run the commands corresponding to step 2, and save the updated model as a new file. Execute runme_GlaDS.m by typing runme_GlaDS into the MATLAB consol. It will produce output similar to the following for step 1: >> runme_GlaDS step #1: Mesh -- Generating first mesh -- Interpolating Ian's composite velocities -- Getting thickness from MC dataset -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading thickness -- BedMachine Greenland: interpolating thickness -- Selecting regions of refinement -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading mask -- BedMachine Greenland: interpolating mask -- remeshing with metric: velocity Anisotropic mesh adaptation WARNING: mesh present but no geometry found. Reconstructing... new number of triangles = 4183 -- Interpolating Ian's composite velocities -- Getting thickness from MC dataset -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading thickness -- BedMachine Greenland: interpolating thickness -- Selecting regions of refinement -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading mask -- BedMachine Greenland: interpolating mask -- remeshing with metric: velocity Anisotropic mesh adaptation WARNING: mesh present but no geometry found. Reconstructing... new number of triangles = 3409 -- Interpolating Ian's composite velocities -- Getting thickness from MC dataset -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading thickness -- BedMachine Greenland: interpolating thickness -- Selecting regions of refinement -- BedMachine Greenland version: 2021-08-26 -- BedMachine Greenland: loading mask -- BedMachine Greenland: interpolating mask -- remeshing with metric: velocity Anisotropic mesh adaptation WARNING: mesh present but no geometry found. Reconstructing... new number of triangles = 3307 saving model as: ./Models_GlaDS/Petermann_hydro_GlaDS_Mesh Petermann_GlaDS.par and Petermann_ISSM.par are used to parameterize the two models in step 2 of runme_GlaDS.m and runme_ISSM.m. These are located with the two runme files in the Code folder. The parameterization step is used to define initial ice geometry, temperature, and other material characteristics. Exp files are used throughout both runme scripts and are located in the Exp folder. These files are spatial contours used to define the model domain outlines and to isolate specific regions of the model domains where numerical instabilities arise. Two additional data files are used within the runme scripts to force the model simulations by adding runoff to the hydrology model and effective pressure to the ice flow model. These are located in the Forcing folder. Extensive information on how to set up and run ISSM and GlaDS is avaliable within the ISSM website, https://issm.jpl.nasa.gov/documentation/. Methodolgy relevant to this work is described in the main manuscript published by GRL, and additional details about model setup are contained within the supplemental document to the manuscript. Scripts to reproduce the figures in the main document are available in the Code folder. ------------- 2. File List: ------------------- 2.1 In Code folder: ** runme_GlaDS.m MATLAB script which sets up and runs GlaDS hydrology model. Early steps create model mesh from a given domain and parameterize the model. Final step initializes and starts the transient run which calculates hydrology variables from given forcings over the set time period. ** Petermann_GlaDS.par Script used during the parameterization step (2) of runme_GlaDS.m. Petermann_GlaDS.par establishes boundary conditions, ice geometry, and initial values for various fields (e.g. basal friction, surface velocity). ** runme_ISSM.m MATLAB script which sets up and runs the ice flow model, used to calculate ice velocity. Large mesh is created, the model is parameterized using Petermann_ISSM.par, and then an inversion algorithm is used to compute basal friction and ice rheology which are necessary to calculate ice velocity. We use winter effective pressure calculated by GlaDS to initialize the inversion. After the inversion step, effective pressure time series (Neff_big_SC_02_CC_2.mat) are loaded and used to force transient simulation and calculate ice velocity. ** Petermann_ISSM.par Script used during the parameterization step (2) of runme_ISSM.m. ----------------------------- 2.1.1 In Plot Code subfolder: ** cube_timeseries_vOCT2019.csv Ice surface velocity satellite data used to evaluate model output and in plotting functions. These data are used in Figure1_ISSMmaps.m and in Figure3_Results.m. Variables are organized into 27 columns: Column 1. Datetime: the year-month-day of corresponding data Column 2. date: datestamp of raw data Column 3-27. point0 to point24: velocity (m/yr) at specified point along a central flow line of Petermann Glacier. ** Figure1_ISSMmaps.m Script used to generate Figure 1 from main document. To run this function an ice flow model with geometry must be loaded in MATLAB (runme_ISSM.m step 2 or later). To generate a figure using a model called md, type this line in MATLAB: >> Figure1_ISSMmaps(md); ** Figure2_GlaDSmaps.m Script used to generate Figure 2 from main document. To run this function the hydrology model containing final reuslts must be loaded (runme_GlaDS.m step 5: Transient). To run, type this line in MATLAB: >> Figure2_GlaDSmaps(md); ** Figure3_Results.m Script used to generate Figure 3 from main document. To run this function the ice flow model containing final results must be loaded (runme_ISSM.m step 6: Transient). This function has a second input, which is the index corresponding to the point location of the timeseries that will be plotted. To run, type this line in MATLAB: >> Figure3_Results(md, 10); -------------------------- 2.1.1.1 In pngs subfolder: ** Greenland_PG.png This image shows the full outline of Greenland with a red box indicating the region of interest for this study: Petermann Glacier. This image is loaded into a subplot of Figure1_ISSMmaps.m ** landsat_GlaDS_alpha03.png The background image used in subplots displaying GlaDS output in Figure2_GlaDSmaps.m ** landsat_ISSM_alpha03.png The background image used in subplots displaying ISSM output in Figure1_ISSMmaps.m -------------------------------- 2.1.1.2 In shapeFiles subfolder: ** flowline1.shp Shape file defining the flowline shown in subplot A of Figure 1, generated by Figure1_ISSMmaps.m. ** pgRefGL_1996.shp Shape file defining the location of Petermann's grounding line as measured in 1996. This file is used in subplots A and C of Figure 1, generated by Figure1_ISSMmaps.m ---------------------- 2.2 In Forcing folder: ** MAR_Runoff_Integrated_2008to2018.mat Melt water runoff data were provided from the regional climate model, MAR (Modèle Atmosphérique Régional. Specific datasets from MARv3.9 provide daily surface mass balance and climate data spanning the Greenland Ice Sheet. We integrate runoff over the hydrology model domain for each daily map between 2008-01-01 and 2018-12-31, and save the resulting time series. This is used to force the hydrology model during transient simulations. Variables are organized into two rows: Row 1. Integrated runoff for full model domain (meters 3 water equivalent per second) Row 2. Date (decimal year) ** Neff_big_SC_02_CC_2.mat Effective pressure (Pa) data used to force the ice flow model. Where the ice flow model and hydrology model domains overlaps, GlaDS calculated effective pressure is used. Where there is no GlaDS output avaliable effective pressure is approximated. Variables are organized into a 7692x1461 matrix. The ice flow model has 7691 vertices, so each collumn corresponds to a full effective pressure map on a specific date. Rows 1-1691: Effective pressure data at correspoinding date and vertex. (Pa) Row 7691: Date (decimal year) ------------------ 2.3 In Exp folder: - Files found here are used within steps of both runme_ISSM.m and runme_GlaDS.m. --------------------- 2.4 In Models folder: -------------------------------- 2.4.1 In Models_GlaDS subfolder: These files are the saved models corresponding to each of the main steps of runme_GlaDS.m. A version of ISSM is required to load and interact with these files. Detailed directions on the download and use of ISSM can be found on the website: https://issm.jpl.nasa.gov/. There are 5 steps that must be run in succession to obtain desired final hydrology results, although any of these models can be loaded in MATLAB in isolation to examine the results from a specific step: Step 1: Mesh Step 2: Param Step 3: InversionFriction Step 4: steadyState Step 5: Transient ** Petermann_hydro_GlaDS_Mesh.mat Mesh generation. All model variables and output are calculated on element vertices defined here. ** Petermann_hydro_GlaDS_Param.mat Initial model parameterization detailed in Petermann_GlaDS.par. ** Petermann_hydro_GlaDS_InversionFriction.mat Inversion step to compute initial basal friction. ISSM uses surface velocities from satellite data in a cost function to approximate friction. ** Petermann_hydro_GlaDS_steadyState.mat The hydrology model is run for 6 months to obtain steady state values for relevant hydrology variables before the transient simulation. ** Petermann_hydro_GlaDS_Transient.mat Hydrology model output from the transient simulation. The model can be loaded in MATLAB by the command: >> md = loadmodel('Petermann_hydro_GlaDS_Transient.mat'); Once the model is loaded, all data used initialize in the model and all results saved to the model can be viewed. md.geometry contains ice geometry (e.g. surface elevation, ice thickness), and md.initialization contains the initial values for various fields (e.g. velocity) as examples. To view what results a model contains: >> md.results ans = struct with fields: StressbalanceSolution: [1x1 struct] TransientSolution: [1x17532 struct] and to view what specific variables are available in the results: >> md.results.TransientSolution ans = 1x17532 struct array with fields: step time EffectivePressure HydraulicPotential HydrologySheetThickness ChannelArea ChannelDischarge SolutionType errlog outlog To plot the model output of a specific field at a specific timestep use the ISSM function plotmodel(). An example effective pressure plot at the 10,000th time step is: >> plotmodel(md, 'data', md.results.TransientSolution(10000).EffectivePressure); Model results span the time period from 2015-01-01 to 2018-12-31, and the timestep is 2 hours. We do not use the first year of data in our results. ------------------------------- 2.4.2 In Models_ISSM subfolder: These files are the saved models from the main steps of runme_ISSM.m. There are 6 steps required to obtain the final ice velocity results discussed in the main document. Step 1: Mesh Step 2: Param Step 3: InversionDoubleBFriction_Budd Step 4: Stressbalance Step 5: InversionDoubleBFriction_Schoof Step 6: Transient ** Petermann_iceFlow_ISSM_Mesh.mat Mesh generation. ** Petermann_iceFlow_ISSM_Param.mat Initial model parameterization detailed in Petermann_ISSM.par. ** Petermann_iceFlow_ISSM_InversionDoubleBFriction_Budd.mat First inversion step. Both ice rheology factor B and basal friction are solved for using ISSM's inversion algorithm. In this step we use a Budd friction law. ** Petermann_iceFlow_Stressbalance.mat Convert from Budd friction law to a Regularized Coloumb friction law. Friction coefficients in different units, and solve for various other necessary parameters. ** Petermann_iceFlow_InversionDoubleBFriction_Schoof.mat Second inversion step. Both ice rheology factor B and basal friction are solved for using ISSM's inversion algorithm. This step uses a Regularized Coulomb friction law (Schoof friction law). Resulting friction is used as the initial basal friction in the transient simulation. During the transient simulation basal friction is updated using effective pressure model output from GlaDS. ** Petermann_iceFlow_ISSM_Transient.mat Model containing the ice flow model results from the transient simulation, including ice velocity. Results span 2007-01-01 to 2018-12-31. We do not use the first 9 years of results, as the model requires this much time to spin up and reach an equilibrium winter velocity. While the model is spinning up we loop 2016 hydrology data.