A dataset supporting projections of 21st-century glacier change for 185 glaciers in Alaska's national parks. It was created by David Rounce using a Bayesian inference framework to calibrate the Python Glacier Evolution Model against airborne laser altimetry data from 1994 to 2021. The data was last updated on 2026-05-19.
Use Cases
- Calibrating glacier evolution models based on spatially-distributed surface elevation change observations.
- Projecting future glacier mass loss under different emissions scenarios for specific Alaskan national parks.
- Reducing parameter uncertainty in glacier models using Bayesian inference frameworks.
- Analyzing subregional variability in glacier mass loss across Alaska.
Strengths
- Calibration uses a 27-year airborne laser altimetry record (1994–2021).
- Covers 185 glaciers representing over half of Alaska's glacier area.
- Model calibration reduced parameter uncertainty by 5–18% and lowered hindcast error by 0.18 m a⁻¹.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Geographic scope is limited to 185 glaciers in Alaska.
Provenance
- Source
- David Rounce via figshare.
- Collection Method
- Data generated using a Bayesian inference framework to calibrate the Python Glacier Evolution Model (PyGEM).
- Time Range
- Observational data from 1994–2021; projections for the 21st century.
- Freshness
- Last updated 2026-05-19 16:08:21; freshness should be verified.
- Geography
- 185 glaciers in Alaska's national parks, including Lake Clark, Denali, Kenai Fjords, Glacier Bay, and Wrangell–St. Elias.