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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).
Keyword(s):
Alaska; glacier; glacier runoff; Kenai; mass balance
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:
Chinese Academy of Sciences (CAS), grant/award no. 131B62KYSB20180003
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
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):
Kenai_Peninsula_2014-2019 * Latitude: 60.094000 * Longitude: -149.995000 * Date/Time Start: 2014-10-22T00:00:00 * Date/Time End: 2019-12-13T00:00:00 * Method/Device: Satellite imagery (SATI)
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
ORDINAL NUMBEROrd NoYang, RuitangGeocode – Series number
Raster graphic, GeoTIFF formatGeoTIFFYang, Ruitang
Raster graphic, GeoTIFF format (File Size)GeoTIFF (Size)BytesYang, Ruitang
Sensor unitUnitYang, RuitangScene 1
Data collection dateDC dateYang, RuitangScene 1: Acquisition date
Sensor unitUnitYang, RuitangScene 2
Data collection dateDC dateYang, RuitangScene 2: Acquisition date
Time in daysTimedaysYang, RuitangTime period between acquisition
Uncertainty of co-registration, mediansigma coregm/dayYang, Ruitang
10 Uncertainty of co-registration, median absolute deviationsigma coreg MADm/dayYang, Ruitang
11 Intensity-offset tracking algorithm, uncertaintysigma trackm/dayYang, Ruitang
12 Total uncertainty of mediansigma Mm/dayYang, Ruitang
13 Total uncertainty of median absolute deviationsigma MADm/dayYang, Ruitang
14 CoverageCov%Yang, Ruitangspacial
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
1104 data points

Data

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Ord No
(Series number)

GeoTIFF

GeoTIFF (Size) [Bytes]

Unit
(Scene 1)

DC date
(Scene 1: Acquisition date)

Unit
(Scene 2)

DC date
(Scene 2: Acquisition date)

Time [days]
(Time period between acquisition)

sigma coreg [m/day]
10 
sigma coreg MAD [m/day]
11 
sigma track [m/day]
12 
sigma M [m/day]
13 
sigma MAD [m/day]
14 
Cov [%]
(spacial)
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