Yang, Ruitang (2024): Glacier velocity maps over 2014-2019 on the Kenai Peninsula, Alaska [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.971786 (DOI registration in progress)
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Abstract:
We used the Python Glacier Evolution Model (PyGEM) to model monthly glacier-wide climatic mass balance and runoff for all glaciers on the Peninsula from 2005 to 2019. It estimates the climatic mass balance (the sum of accumulation, melt, and refreezing) for each glacier using ~10 m elevation bins, the ice thickness, and a monthly time step forced with near-surface air temperature and precipitation data. The model is calibrated by the Geodetic mass balance data and validated by the in-situ data from US Geological Survey Benchmark Glaciers datasets (https://doi.pangaea.de/10.1594/PANGAEA.970133). We also used the Sentinel-1 data basing offset tracking method to derive velocity maps for glaciers on the Kenai Peninsula from Oct 2014 to Dec 2019 (this dataset).
Related to:
Yang, Ruitang (2024): Glacier mass balance and runoff over 2005-2019 on the Kenai Peninsula, Alaska [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.970133
Funding:
European Research Council (ERC), grant/award no. 101096057: Past and Future High-resolution Global Glacier Mass Changes (GLACMASS)
National Aeronautics and Space Administration (NASA), grant/award no. 80NSSC20K1296: Quantifying Contributions from Glaciers and Terrestrial Hydrology to Recent and Future Sea Level Change
State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, grant/award no. SKLCS-ZZ-2022
The Research Council of Norway (RCN), grant/award no. 324131: Global glacier modeling: Do non-linear feedbacks matter for century-scale projections?
Coverage:
Latitude: 60.094000 * Longitude: -149.995000
Date/Time Start: 2014-10-22T00:00:00 * Date/Time End: 2019-12-13T00:00:00
Minimum ORDINAL NUMBER: 1 * Maximum ORDINAL NUMBER: 92
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | ORDINAL NUMBER | Ord No | Yang, Ruitang | Geocode – Series number | ||
| 2 | Raster graphic, GeoTIFF format | GeoTIFF | Yang, Ruitang | |||
| 3 | Raster graphic, GeoTIFF format (File Size) | GeoTIFF (Size) | Bytes | Yang, Ruitang | ||
| 4 | Sensor unit | Unit | Yang, Ruitang | Scene 1 | ||
| 5 | Data collection date | DC date | Yang, Ruitang | Scene 1: Acquisition date | ||
| 6 | Sensor unit | Unit | Yang, Ruitang | Scene 2 | ||
| 7 | Data collection date | DC date | Yang, Ruitang | Scene 2: Acquisition date | ||
| 8 | Time in days | Time | days | Yang, Ruitang | Time period between acquisition | |
| 9 | Uncertainty of co-registration, median | sigma coreg | m/day | Yang, Ruitang | ||
| 10 | Uncertainty of co-registration, median absolute deviation | sigma coreg MAD | m/day | Yang, Ruitang | ||
| 11 | Intensity-offset tracking algorithm, uncertainty | sigma track | m/day | Yang, Ruitang | ||
| 12 | Total uncertainty of median | sigma M | m/day | Yang, Ruitang | ||
| 13 | Total uncertainty of median absolute deviation | sigma MAD | m/day | Yang, Ruitang | ||
| 14 | Coverage | Cov | % | Yang, Ruitang | spacial |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
1104 data points