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Seasonal snowpack is an important predictor of the water resources available in the following spring and early-summer melt season. Total basin snow water equivalent (SWE) estimation usually requires a form of statistical analysis that is implicitly built upon the Gaussian framework. However, it is important to characterize the non-Gaussian properties of snow distribution for accurate large-scale SWE estimation based on remotely sensed or sparse ground-based observations. This study quantified non-Gaussianity using sample negentropy; the Kullback–Leibler divergence from the Gaussian distribution for field-observed snow depth data from the North Slope, Alaska; and three representative SWE distributions in the western USA from the Airborne Snow Observatory (ASO). Snowdrifts around lakeshore cliffs and deep gullies can bring moderate non-Gaussianity in the open, lowland tundra of North Slope, Alaska, while the ASO dataset suggests that subalpine forests may effectively suppress the non-Gaussianity of snow distribution. Thus, non-Gaussianity is found in areas with partial snow cover and wind-induced snowdrifts around topographic breaks on slopes and on other steep terrain features. The snowpacks may be considered weakly Gaussian in coastal regions with open tundra in Alaska and alpine and subalpine terrains in the western USA if the land is completely covered by snow. The wind-induced snowdrift effect can potentially be partitioned from the observed snow spatial distribution guided by its Gaussianity. 

This dataset supports the findings of the research paper submitted to the journal Geophysical Research Letters that documents the rapid thaw of saline permafrost below a shallow thermokarst lake near Utqiagvik, Alaska. The lake, East Twin Lake, is located in the Barrow Environmental Observatory. We conducted repeat drilling-based surveys at East Twin Lake in the Barrow Environmental Observatory near Utqiagvik, Alaska between 2008 and 2023. These field data were integrated with transient electromagnetic (TEM) near-surface geophysics soundings in 2016 and 2022 and analysis of a time-series of wintertime Synthetic Aperture Radar (SAR) satellite imagery from 2015 to 2023 to assess changes in lake and sub-lake properties. Finally, we assessed the impact of thawing saline permafrost on shore erosion by quantifying a regime shift in the lateral expansion rate of East Twin Lake between 1948 and 2022. The datasets consist of a CSV file with the point measurements from the drilling campaign, processed TEM data along with the script, a table of SAR backscatter values extracted for three lakes, and a table with lake expansion rates for East Twin Lake. 

Abstract. Thermokarst lake dynamics, which play an essential role in carbon releasedue to permafrost thaw, are affected by various geomorphological processes.In this study, we derive a three-dimensional (3D) Stefan equation tocharacterize talik geometry under a hypothetical thermokarst lake in thecontinuous permafrost region. Using the Euler equation in the calculus ofvariations, the lower bounds of the talik were determined as an extremum ofthe functional describing the phase boundary area with a fixed total talikvolume. We demonstrate that the semi-ellipsoid geometry of the talik isoptimal for minimizing the total permafrost thaw under the lake for a givenannual heat supply. The model predicting ellipsoidal talik geometry wascompared to talik thickness observations using transient electromagnetic(TEM) soundings in Peatball Lake on the Arctic Coastal Plain (ACP) ofnorthern Alaska. The depth : width ratio of the elliptical sub-lake talik cancharacterize the energy flux anisotropy in the permafrost, although the lakebathymetry cross section may not be elliptic due to the presence ofnear-surface ice-rich permafrost. This theory suggests that talikdevelopment deepens lakes and results in more uniform horizontal lakeexpansion around the perimeter of the lakes, while wind-induced waves andcurrents are likely responsible for the elongation and orientation ofshallow thermokarst lakes without taliks in certain regions such as the ACPof northern Alaska. 

Lakes are abundant features on coastal plains of the Arctic, providing important fish and wildlife habitat and water supply for villages and industry, but also interact with frozen ground (permafrost) and the carbon it stores. Most of these lakes are termed "thermokarst" because they form in ice-rich permafrost and gradually expand over time. The dynamic nature of thermokarst lakes also makes them prone to catastrophic drainage and abrupt conversion to wetlands, called drained thermokarst lake basins (DTLBs). Together, thermokarst lakes and DTLBs cover up to 80% of arctic lowland regions, making understanding their response to ongoing climate change essential for coastal plain environmental assessment. Dating the timing of lake drainage can improve our understanding of the causes and consequences of DTLB formation. This suite of 14C (Carbon-14) ages provides insight into the timing of lake drainage on the North Slope of Alaska across a range of ecosystems and surficial geology types. 

Lakes are abundant features on coastal plains of the Arctic, providing important fish and wildlife habitat and water supply for villages and industry, but also interact with frozen ground (permafrost) and the carbon it stores. Most of these lakes are termed "thermokarst" because they form in ice-rich permafrost and gradually expand over time. The dynamic nature of thermokarst lakes also makes them prone to catastrophic drainage and abrupt conversion to wetlands, called drained thermokarst lake basins (DTLBs). Together, thermokarst lakes and DTLBs cover up to 80% of arctic lowland regions, making understanding their response to ongoing climate change essential for coastal plain environmental assessment. Dating the timing of lake drainage can improve our understanding of the causes and consequences of DTLB formation. This suite of 14C (Carbon-14) ages provides insight into the timing of lake drainage on the North Slope of Alaska across a range of ecosystems and surficial geology types. 

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km2, including a >39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2–95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-latitude carbon cycling. 

This data set contains a classification of the North Slope, Alaska for drained lake basins (DLBs) based on Landsat-8 imagery of the years 2014-2019 and Arctic Digital Elevation Model (ArcticDEM) data. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. This data set is based on a novel and scalable remote sensing-based approach to identify DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. The data set was validated against several prior sub-regional scale datasets and manually classified points. The study area covers greater than 71,000 square kilometers (km2), including a greater than 39,000 km2 area not previously covered in existing DLB data sets. Within the data set, three classes are present: DLB/ambiguous/noDLB. Areas classified as ambiguous could not be classified as DLB or noDLB with sufficient certainty. Users may decide on a case by case basis if they wish to use the conservative estimate of DLB area, therefore omitting areas classified as ambiguous, or to use all three classes. 

This data set contains a classification of the North Slope, Alaska for drained lake basins (DLBs) based on Landsat-8 imagery of the years 2014-2019 and Arctic Digital Elevation Model (ArcticDEM) data. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. This data set is based on a novel and scalable remote sensing-based approach to identify DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. The data set was validated against several prior sub-regional scale datasets and manually classified points. The study area covers greater than 71,000 square kilometers (km2), including a greater than 39,000 km2 area not previously covered in existing DLB data sets. Within the data set, three classes are present: DLB/ambiguous/noDLB. Areas classified as ambiguous could not be classified as DLB or noDLB with sufficient certainty. Users may decide on a case by case basis if they wish to use the conservative estimate of DLB area, therefore omitting areas classified as ambiguous, or to use all three classes.