Floating and bedfast lake ice regimes across Arctic Alaska using space-borne SAR imagery from 1992-2016
This dataset contains seven shapefiles of lake-rich regions in Arctic Alaska which detail late-winter lake ice regimes. Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ic...
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| Format: | Dataset |
| Language: | English |
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Arctic Data Center
2018
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| Online Access: | https://dx.doi.org/10.18739/a2cj87k8h https://arcticdata.io/catalog/#view/doi:10.18739/A2CJ87K8H |
| Summary: | This dataset contains seven shapefiles of lake-rich regions in Arctic Alaska which detail late-winter lake ice regimes. Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 synthetic aperture radar (SAR) imagery for the seven lake-rich regions to analyze lake ice regime extents and dynamics over a 25-year period (1992-2016). This research was a part of the Arctic Lake Ice Systems Science (ALISS) project (http://arcticlakeice.org/) . Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes - lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced. |
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