Dataset DOI: 10.5061/dryad.sn02v6xkr

The data included here fall into two categories:

(1) cosmogenic nuclide modeling to supplement and interpret 10Be and 14C measurements from Denver Glacier in southeastern Alaska (nuclide-model)

(2) Elmer/Ice 3D ice-flow model outputs, originally published by Helanow et al. (2021) and re-used here for derived analysis regarding potential controls on glacial erosion (ice-flow-outputs)

Description of the data and file structure

Files and variables

File: alaska_cosmo_erosion_data.zip

Description: This file contains two main directories:

nuclide_model: This contains input files, output files, and scripts for modeling cosmogenic nuclide production and carrying out the match/filter procedure. Briefly, we use a set of input files (sample-specific production profile, sample-specific metadata, snow shielding file, exposure/burial histories file, erosion rates file) to model nuclide concentrations. We compare modeled concentrations to measured concentrations, storing "matches" in the subdirectory match_independent. We then use the spatial arrangement of samples to filter out unacceptable results, storing model outputs for this step in the subdirectory match_downvalley. 

Contents of subdirectories:

1. /prod_dat: model inputs; nuclide production profiles with depth for each sample. Each file refers to a specific sample (e.g., "Skag01_comb_prof.csv") and has four rows. The first row is depth [cm], the second row is the 10Be production rate [atoms/g/yr], the third row is the 14C production rate [atoms/g/yr], and the fourth row is the 26Al production rate [atoms/g/yr]. Production rates are scaled using the nuclide-dependent "LSDn" scaling (Lifton et al., 2014), averaging the scaling factor over the last 11 ka to simplify depth profiles. For calculating production rates, we use the CRONUS-Earth global primary calibration dataset for 10Be (Borchers et al., 2016) and a global calibration dataset for 14C (Koester and Lifton, 2023). Muon production is geographically scaled with energy-dependent atmospheric attenuation of muons ("Method 1A" of Balco, 2017). A spallogenic attenuation length scale of 140 g cm^-2 is used for ¹⁰Be and 160 g cm^-2 is used for ¹⁴C. Production profiles stored in these files are not scaled to account for topographic shielding.

2. /sample_dat: model inputs; sample-specific metadata. Each file refers to a specific sample (e.g., "dat_Skag01.csv"). Variables used in the model procedure are:

   • thickness [cm]: The thickness of each sample collected.
   • shielding factor [unitless]: The topographic shielding factor to scale production rates (number between 0 and 1).
   • Be_conc [atoms/g]: Accelerator mass spectrometry (AMS) measured 10Be concentration.
   • Be_1sig [atoms/g]: AMS measured internal uncertainty in 10Be concentration.
   • C_conc [atoms/g]: AMS measured 14Ce concentration.
   • C_1sig [atoms/g]: AMS measured internal uncertainty in 14Ce concentration.
   • such as thickness, shielding factor, 10Be and 14C measurements.

   Two additional files include the down-core data. be10_core_dat.csv contains tabular data, with a column for measurement depth [cm], 10Be concentration [atoms/g] and 10Be uncertainty [atoms/g]. c14_core_dat.csv is formatted the same, but with columns for 14C concentration and uncertainty [atoms/g].

3. /swe: model inputs; two files containing information about snow water equivalents, used as model inputs.

   • snow0.csv: A row of 12 "0" values, indicating no snow shielding.
   • Skag_SWE_modern.csv: A row of 12 values, representing monthly average snow water equivalent depths [cm] from January (column 1) to December (column 12).

4. /match_independent: model outputs; contains data structures storing the 'matched' exposure-burial-erosion scenarios of the ~90 million tested for each paired ¹⁴C-¹⁰Be sample using the nuclide forward model, treating each sample independently from other samples. There are two types of files: 

   • XX_match_1sig_1D.csv: This is a column of integer values, referring to the indices of the history file (histories_11ka_450k.csv) that return a match using the 1-sigma uncertainty criteria described in Brooks et al. (2026).

   • XX_match_2sig_2D.csv: Binary (0 or 1) tabular data of size 450,000 rows x 201 columns. The number of rows matches the number of histories (histories_11ka_450k.csv) and the number of columns matches the number of erosion rates (erosion_rates.csv). Each element represents a model output from the combination of history (row number) and erosion rate (column number) - a value of 1 indicates a "match" and a value of 0 indicates no match.

     Here "XX" refers to the sample ID (e.g., "skag02"). Two other files contain down-core model outputs (core_match_3sig_1D.csv, core_match_3sig_2D.csv), with the same file structure as described above.

5. /match_downvalley: model outputs; contains histories for each paired 14C-10Be sample after applying the match/filter procedure leveraging the spatial arrangement of samples.

   • XX.all: Each line contains two integers: an index of histories (from histories_11ka_450k.csv) and an integer (number of matches for that history). This file is concatenated from many different 'matching algorithms' run in parallel and is not post-processed.
   • XX.tot: Post-processed version of XX.all, merging history entries so that each unique history has a single row.

6. /erosion_dat: model outputs; contains probability densities of erosion rates and erosion depths for each bedrock sample.

   • XX_erosion_rate_freqs.csv: The first row contains discrete erosion rates tested [cm/yr] and the second row contains the probability densities [unitless] for the erosion rates.
   • XX_erosion_depth_freqs.csv: The first column contains discrete erosion depths [cm] and the second column contains the probability densities [unitless] for the erosion depths.

   Files

   histories_11ka_450k.csv: 2D array of pseudo-randomly generated histories, rows = different histories, columns = different centuries. 0 = exposure, 1 = burial (note difference when plotting). During exposure, nuclides accumulate as a function of depth in bedrock. During burial, we assume that there is no nuclide accumulation.

   erosion_rates.csv: Column containing erosion rates (0.0 to 0.2 cm/yr in increments of 0.001 cm/yr). Erosion is only applied during periods of glacial burial.

ice-flow-outputs: This contains directories for the 10 m/yr horizontal velocity simulations using Elmer/Ice conducted by Helanow et al. (2021) for Castleguard and Tsanfleuron forefields. One way to view outputs is using Paraview (or similar software) to open PVTU files. Variables are described in the .names files; model procedure is described in Helanow et al. (2021) and shown in .sif file included in each subdirectory.

Code/software

Python scripts (require numpy, pandas, matplotlib)

cosmod_utils.py: Functions for modeling nuclide production and analyzing output; imported as module by other files.

example_forward_model.py: Nuclide forward model procedure for one example sample and reduced set of model inputs. Due to computational cost, the full model procedure is carried out on high-performance and/or high-throughput computing resources. This script requires several input files:

• Sample-specific metadata and nuclide concentrations (located in /sample_dat subdirectory).
• Sample-specific production rate depth profiles (located in /prod_dat subdirectory).
• Erosion rates to test (erosion_rates.csv).

This file returns a set of modeled ¹⁰Be and ¹⁴C concentrations for the given exposure/burial history and erosion rate inputs.

plot_model_results.py: Script to plot main model outputs from the full set of simulations reported in Brooks et al. (2026). This script requires the files erosion_rates.csv and histories_11ka_450k.csv and the files stored in subdirectories /match_indepedent, /match_downvalley, and /erosion_dat.

downvalley_match.py: Example of script that conducts downvalley matching/filtering procedure. This script requires files stored in the /match_independent subdirectory. This script returns files ("XX.csv") which contain indices of matched histories and the number of corresponding matches.