This repository contains the data and scripts used to reproduce figures for “Accelerating glacier recession contrasts rock glacier stability in a temperate mountain range.” The collection covers the Teton Range, Wyoming, USA, and spans 1967 to 2024. Contents include a 1967 photogrammetric DEM generated from historical aerial imagery using structure from motion methods (Knuth et al., 2023); a PDF Metashape report documenting the generation of the 1967 DEM; elevation change rasters for 1967 to 2014 and 2014 to 2022 derived from 2014 and 2022 USGS LiDAR and the 1967 and 2014 DEMs; polygon shapefiles for cirque glaciers, rock glaciers, perennial snowfields, and watershed boundaries; stream temperature observations on 15 August of each year from 2015 to 2024 at sites representative of glacier, rock glacier, and snowfield meltwater sources; and tabular and raster data used to compare local glacier elevation change with published datasets from Hugonnet et al. (2021) and Menounos et al. (2019). File formats include GeoTIFF, ESRI Shapefile, and CSV. Processing steps, coordinate reference systems, and units are documented in the README, along with scripts and instructions to regenerate all analyses and figures. These data support studies of cryospheric thinning, alpine hydrology, and model benchmarking in temperate mountain environments.

Dataset DOI: 10.5061/dryad.dz08kps9g

Description of the data and file structure

Data for “Accelerating glacier recession contrasts rock glacier stability in a temperate mountain range”

Study area: Teton Range, Wyoming, USA

File types: GeoTIFF (.tif), ESRI Shapefile (.shp with sidecar files), CSV (.csv)

This repository contains the data and scripts used to reproduce figures for the manuscript titled above. The archive includes digital elevation models (DEMs), elevation-change products, vector outlines of cryospheric landforms and watersheds, stream-temperature observations, and comparison datasets used in the paper. These data support studies of cryospheric thinning and alpine hydrology in the Teton Range.

Contents overview

Raster datasets (.tif) - DEMs, elevation change, and topographic derivatives
Shapefiles - Cirque glacier, rock glacier, snowfield, and watershed polygons
CSV files - Stream temperature and watershed snow extent summaries, plus a published glacier-change table

Raster Datasets (.tif)

Raster datasets represent geographic information as a grid of pixels, where each cell stores a value for that location. There are 13 raster files in this repository.

1. USGS_2014_2022_lidar_dhdt_reprojected.tif

Rate of elevation change for the Teton Range from the 2014 and 2022 LiDAR datasets. The units are in m yr-1. Original LiDAR data are available from USGS:

2014: https://portal.opentopography.org/usgsDataset?dsid=USGS_LPC_WY_GrandTetonElkRefuge_2014_LAS_2016les in this repository.

2022: https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/WY_GrandTetonNP_D22/WY_GrandTetonNP_1_D22/

The 2022 dataset was downloaded tile by tile and mosaicked in ArcGIS Pro using the Mosaic tool.

The 2014 and 2022 DEMs were co-registered using the ref (1)

approach with the demcoreg Python code ref (2): https://github.com/dshean/demcoreg

2. 1967-08-03_2_re-coregistered.tif

DEM derived from 1967 historical aerial imagery. This DEM contains voids that were filled using a local hypsometric infill method following ref (3). The workflow is implemented in XDEM_local_hypsometry_infill.ipynb.

Used by: Uncertainity_analysis_DEM_dh_dt.ipynb, supplementary_fig_1.ipynb

3. local_hyps_1967_2014_elev_rate.tif

Rate of elevation change for 1967 to 2014 for the Teton Range. The 1967 DEM was first infilled using local hypsometric infill, then DEM differencing was done in ArcGIS Pro. The difference for 1967 to 2014 was divided by 47 to compute the rate of change. The units are in m yr^-1).

Used by: Uncertainity_analysis_DEM_dh_dt.ipynb

4. northness_teton_range_1m.tif

5. solar_rad_normalized_teton_range.tif

6. Teton_slope_2022_reprojected.tif

Topographic rasters derived from the 2022 LiDAR DEM.

northness_teton_range_1m.tif: Derived in ArcGIS Pro by computing slope and aspect from the 2022 LiDAR DEM, then calculating normalized northness using

northness = cos(aspect in radians) * sin(slope in radians)

Values range from −1 (south-facing) to +1 (north-facing), with 0 for flat terrain.

Used by: supplementary_fig_1.ipynb

solar_rad_normalized_teton_range.tif: Solar radiation calculated with the Area Solar Radiation tool in ArcGIS Spatial Analyst for June to September using default settings for latitude, sky size, and atmospheric transmittance. Output values (Wh m⁻²) were normalized in ArcGIS Pro.

Used by: supplementary_fig_1.ipynb

Teton_slope_2022_reprojected.tif: Slope derived from the 2022 LiDAR DEM using the Slope tool in ArcGIS Pro. Units are degrees.

Used by: Uncertainity_analysis_DEM_dh_dt.ipynb

7. Elevation_Change_CirqueGlacier_1967_2014_local_hyp.tif

8. Elevation_Change_RockGlacier_1967_2014_local_hyp.tif

9. Elevation_Change_SnowField_1967_2014_local_hyp.tif

Elevation change for cirque glaciers, rock glaciers, and snowfields from 1967 to 2014. Units are meters of elevation change. Derived by differencing the infilled 1967 DEM and the 2014 LiDAR DEM in ArcGIS Pro, then clipping by each landform shapefile with the Clip tool.

Used by: fig2_Violen_plot_and_supp_fig_6.ipynb

10. Elevation_Change_CirqueGlacier_2014_2022.tif

11. Elevation_Change_RockGlacier_2022_new.tif

12. Elevation_Change_SnowField_2014_2022.tif

Elevation change for cirque glaciers, rock glaciers, and snowfields from 2014 to 2022. Units are meters of elevation change. Derived by differencing the 2014 and 2022 LiDAR DEMs in ArcGIS Pro, then clipping by each landform shapefile with the Clip tool.

Used by: fig2_Violen_plot_and_supp_fig_6.ipynb

Elevation_Change_CirqueGlacier_2014_2022.tif is also used by supplementary_fig_11.ipynb.

13. menounos_glacier_elev_change.tif

Elevation change dataset for the Teton area used in ref(4). This raster is clipped to the Teton Range from the larger dataset provided in that paper. DEMs in that work were derived from ASTER.

Shapefiles

ESRI Shapefiles store vector data and require multiple files in the same folder to read properly. Common extensions include: .cpg, .dbf, .prj, .sbn, .sbx, .shp, .shp.xml, .shx. This dataset contains four shapefiles:

1. Cirque glacier polygons: teton_outline_final.shp (with associated shapefile extensions)

2. Rock glacier polygons: rock_glacier.shp (with associated shapefile extensions)

3. Snowfield polygons: Snow_field_threshold_w_lidar_difference.shp (with associated shapefile extensions)

4. Watershed polygons: Watershed_polygon.shp (with associated shapefile extensions)

CSV files

CSV files are comma-delimited text files.

1. source_epred_time_data.csv

Stream temperature data used in the analysis. Three columns: date of measurement, stream temperature (°C), and landform category (rock glacier, snowfield, glacier).

Since 2015, the Teton Alpine Stream Research project has collected stream temperature at sites across the Teton Range, Wyoming, USA. In situ loggers (HOBO Water Temperature Pro V2) recorded water temperature hourly. This file contains processed data grouped by landform category.

2. Teton_watershed_Sentinel_2_2015_2024.csv

Percentage of snowfield area at the end of summer in each watershed from 2015 to 2022. Derived in Google Earth Engine. For each year, the best cloud-free Sentinel-2 image was selected, the NDSI was computed, and snow and shadow masks were applied. Thresholds were tested and selected visually to represent end-of-summer snow as consistently as possible across years.

3. dh_02_rgi60_pergla_rates.csv

Dataset from ref(5). Contains RGI IDs and surface elevation change for each glacier over the study periods in that work. Used by fig2_Violen_plot_and_supp_fig_6.ipynb

Columns:

rgiid: RGI 6.0 glacier identifier
period: time interval of reported change
area: glacier area (m²)
dhdt: surface elevation change rate (m yr^-1)
err_dhdt: uncertainty in dhdt (m yr^-1)
dvoldt: volume change rate (m³ yr^-1)
err_dvoldt: uncertainty in dvoldt (m³ yr^-1)
dmdt: mass change rate (Gt yr^-1)
err_dmdt: uncertainty in dmdt (Gt yr^-1)
dmdtda: area-normalized mass change rate (m w.e. yr^-1)
err_dmdtda: uncertainty in dmdtda (m w.e. yr^-1)
perc_area_meas: percent of glacier area measured
perc_area_res: percent of glacier area resolved
valid_obs: number of valid observations
valid_obs_py: number of valid observations per year
reg: regional identifier

In this study, we used rgiid, period, and dhdt.

PDF file

1. 1967-08-03_metashape_report.pdf

PDF report containing information on the processing workflow used to generate the 1967 historical DEM in Agisoft Metashape

Limitation and notes

The 1967 DEM was derived from historical aerial imagery and contains areas of higher uncertainty. Voids were filled using local hypsometric interpolation
Stream temperature thresholds and masks for Sentinel-2 snow detection were selected visually for each year to balance cloud and shadow contamination. End-of-summer snow percentages are subject to those choices.

Citation :

C. Nuth, A. Kääb, Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. The Cryosphere 5, 271–290 (2011).
D. E. Shean, O. Alexandrov, Z. M. Moratto, B. E. Smith, I. R. Joughin, C. Porter, P. Morin, An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery. ISPRS J. Photogramm. Remote Sens. 116, 101–117 (2016).
R. McNabb, C. Nuth, A. Kääb, L. Girod, Sensitivity of glacier volume change estimation to DEM void interpolation. The Cryosphere 13, 895–910 (2019).
B. Menounos, R. Hugonnet, D. Shean, A. Gardner, I. Howat, E. Berthier, B. Pelto, C. Tennant, J. Shea, M. Noh, F. Brun, A. Dehecq, Heterogeneous Changes in Western North American Glaciers Linked to Decadal Variability in Zonal Wind Strength. Geophys. Res. Lett. 46, 200–209 (2019).
R. Hugonnet, R. McNabb, E. Berthier, B. Menounos, C. Nuth, L. Girod, D. Farinotti, M. Huss, I. Dussaillant, F. Brun, A. Kääb, Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726–731 (2021).