Measurements of ice surface elevation change from a network of twelve bamboo ablation stakes installed in the western Greenland ice sheet ablation zone (67.0496o N, 49.0201o W, 1215 m a.s.l.). Stakes were installed by drilling 3 m deep holes into the ice, inserting the bamboo stakes, and allowing them to freeze into the ice for 24 hours. Following the 24 hour freeze-in period, measurements of the distance from the top of the stake to its base were recorded at nominal 3 hour intervals continuously from 12:00 local time (UTC-2) on 6 July 2016 to 23:00 local time on 12 July 2016. Prior to each measurement, a 24×24 cm square wooden ablation board was placed at the base of the stake and oriented to true north. This board operated as a datum from which the stake height above the ice surface was measured.

Measurements of ice surface elevation change from a network of twelve bamboo ablation stakes installed in the western Greenland ice sheet ablation zone (67.0496o N, 49.0201o W, 1215 m a.s.l.). Stakes were installed by drilling 3 m deep holes into the ice, inserting the bamboo stakes, and allowing them to freeze into the ice for 24 hours. Following the 24 hour freeze-in period, measurements of the distance from the top of the stake to its base were recorded at nominal 3 hour intervals continuously from 12:00 local time (UTC-2) on 6 July 2016 to 23:00 local time on 12 July 2016. Prior to each measurement, a 24×24 cm square wooden ablation board was placed at the base of the stake and oriented to true north. This board operated as a datum from which the stake height above the ice surface was measured.

This dataset contains water level records derived from ICESat-2 for 227,386 lakes spanning Oct 14, 2018 to July 16, 2020. These records have been updated to reflect an error in the calculation of lake area in the previous version which led to an overestimation of lake area at high latitudes. For details on how this correction was performed, please see the 2023 Addenda to Cooley et al (2021). A complete description of the method used to derive water level from ICESat-2 can be found in Cooley et al (2021), but is briefly summarized below: We create a conservative water mask modified from the Global Surface Water Occurrence (GSWO) product (Pekel et al., 2016); We intersect ATL08 mean terrain height returns with this water mask, requiring water bodies to receive at least three ICESat-2 point observations on the same day to be included in the analysis; We filter observations based on the mean standard deviation of returns, among other factors; We aggregate observations to monthly timesteps; We calculate seasonal variability in water level as the maximum minus the minimum monthly water level over the 22-month period. This dataset contains: ICESat2_lake_variability_v2_updated.shp: A shapefile containing lake points and summary statistics (i.e. height variability, storage variability, etc) *updated to include corrected lake area and storage values ICESat2_lake_height_time_series_v2_updated.csv: A csv file of the monthly water height time series used to calculate the global lake level variability *updated to include corrected lake area values 265 water mask GeoTiffs: Water masks created from GSWO which we intersect with ICESat-2 data to produce the water level time series *unchanged from previous version ICESat2_mask_reference_v2_updated.csv – A csv file which lists the corresponding water mask for each water body in the dataset *updated to include corrected lake area values USGS_height_validation_v2_updated.csv – A csv file containing the height comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses *updated to include corrected lake area values USGS_range_validation_ v2_updated.csv – A csv file containing the range comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses *updated to include corrected lake area values California_storage_validation_v2_updated.csv – A csv file containing the storage comparison between ICESat-2 and California Department of Water Resource gauges used for validation and uncertainty analyses *updated to include corrected lake area and storage values See the README file for a more detailed description of this dataset. Anyone wishing to use this dataset should cite Cooley et al. 2021) and contact Sarah Cooley at [email protected] with a description of the work and any questions so that we may offer guidance in regards to the best usage of our dataset. Cooley, S.W., Ryan, J.C., and Smith, L.C., (2021), Human alteration of global surface water storage variability, Nature, https://doi.org/10.1038/s41586-021-03262-3

This dataset contains water level records derived from ICESat-2 for 227,386 lakes spanning Oct 14, 2018 to July 16, 2020. These records have been updated to reflect an error in the calculation of lake area in the previous version which led to an overestimation of lake area at high latitudes. For details on how this correction was performed, please see the 2023 Addenda to Cooley et al (2021). A complete description of the method used to derive water level from ICESat-2 can be found in Cooley et al (2021), but is briefly summarized below: We create a conservative water mask modified from the Global Surface Water Occurrence (GSWO) product (Pekel et al., 2016); We intersect ATL08 mean terrain height returns with this water mask, requiring water bodies to receive at least three ICESat-2 point observations on the same day to be included in the analysis; We filter observations based on the mean standard deviation of returns, among other factors; We aggregate observations to monthly timesteps; We calculate seasonal variability in water level as the maximum minus the minimum monthly water level over the 22-month period. This dataset contains: ICESat2_lake_variability_v2_updated.shp: A shapefile containing lake points and summary statistics (i.e. height variability, storage variability, etc) *updated to include corrected lake area and storage values ICESat2_lake_height_time_series_v2_updated.csv: A csv file of the monthly water height time series used to calculate the global lake level variability *updated to include corrected lake area values 265 water mask GeoTiffs: Water masks created from GSWO which we intersect with ICESat-2 data to produce the water level time series *unchanged from previous version ICESat2_mask_reference_v2_updated.csv – A csv file which lists the corresponding water mask for each water body in the dataset *updated to include corrected lake area values USGS_height_validation_v2_updated.csv – A csv file containing the height comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses *updated to include corrected lake area values USGS_range_validation_ v2_updated.csv – A csv file containing the range comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses *updated to include corrected lake area values California_storage_validation_v2_updated.csv – A csv file containing the storage comparison between ICESat-2 and California Department of Water Resource gauges used for validation and uncertainty analyses *updated to include corrected lake area and storage values See the README file for a more detailed description of this dataset. Anyone wishing to use this dataset should cite Cooley et al. 2021) and contact Sarah Cooley at [email protected] with a description of the work and any questions so that we may offer guidance in regards to the best usage of our dataset. Cooley, S.W., Ryan, J.C., and Smith, L.C., (2021), Human alteration of global surface water storage variability, Nature, https://doi.org/10.1038/s41586-021-03262-3

This data set accompanies a paper (Kyzivat & Smith, 2023, https://doi.org/10.1029/2023GL104825) looking at the relative importance of three variables in upscaling Arctic lake methane emissions: the area of small, non-inventoried lakes; lake aquatic vegetation coverage; and potential double counting with wetlands. A baseline bottom-up emissions estimate based on temperature and lake area is provided for all inventoried lakes within the Boreal-Arctic Wetland and Lake Dataset (BAWLD, Olefeldt et al., 2021, https://doi.org/10.18739/A2C824F9X), with estimates for extrapolated lake area bins below the inventory resolution. The data set includes two comma separated value (CSV) files with an index column corresponding to either lakes in the HydroLAKES inventory (Messager et al., 2016; https://www.hydrosheds.org/products/hydrolakes), or grid cells in BAWLD. The global surface water data set (GSW, Pekel et al., 2016) was used to derive lake aquatic vegetation (LAV) and potential wetland double-counting, defined as areas within lakes corresponding to less than 50% water occurrence. A third CSV dataset provides estimates for lake and aquatic vegetation areas and methane emissions for extrapolated area bins corresponding to lakes below the 0.5 km2 inventory threshold used in the paper. The python package developed for this data analysis is also included. Further details are given below and in the accompanying publication.

This record is for the dataset “ABoVE: Wetland Inundation Coverage at Yukon Flats, AK and PA Delta, Canada, 2017-2019” at <a href= " https://doi.org/10.3334/ORNLDAAC/1901">https://doi.org/10.3334/ORNLDAAC/1901</a><p><p> This dataset provides time series of wetland inundation coverage maps and corresponding inundation frequency maps at ~10-meter resolution estimated every 12 days during the free-water period (May to October) for the years 2017-2019 over the Yukon Flats (YK) portion of the Yukon River, Alaska, USA, and the Peace-Athabasca Delta (PAD), Alberta, Canada. Wetland inundation coverage was determined by a two-step modified decision-tree classification approach that first used Sentinel-1 C-band SAR to identify likely inundated areas across a study site and was followed by a decision-tree classification step with C-band SAR backscatter statistics thresholds to distinguish among different inundation components. The result of this process was five classes for each inundation map, namely Open Water (OW), Floating Plants (FP), Emergent Plants (EP), Flooded Vegetation (FV), and Dry Land (DRY). After all the individual (every 12 days) inundation coverage maps were derived for a study site, they were generalized to two-class maps which maintained only inundation status. These generalized maps were then stacked and summarized to produce the inundation frequency map for the site. In these maps, higher values signify more frequently inundated areas, with the maximum value representing permanently inundated pixels. The Sentinel-1 inundation mapping capability demonstrated here provided frequent, broad-scale mapping of different wetland inundation components. Integration of such products with process-based methane (CH4) models would improve simulation of CH4 emissions from wetlands. <p>This dataset can be downloaded at <a href= " https://doi.org/10.3334/ORNLDAAC/1901">https://doi.org/10.3334/ORNLDAAC/1901</a>

This dataset contains in situ observations of meltwater discharge through supraglacial stream networks and auxiliary data. Forty-six discrete discharge measurements and continuous water level measurements were collected for 62 days (13 June to 13 August) in 2016 for a 0.56 square kilometer supraglacial stream catchment in southwest Greenland. The dataset also contains water level observations in a cryoconite hole, shapefiles of the catchment boundary, gauging station location, and stream network. The dataset consists of the following files: Discharge_summary.csv : contains the 46 discrete discharge measurements (along with velocity and area) Discharge_profiles.csv : contains cross-sectional stream profiles of discharge for every 0.2 meters over the stream bed with reference to its deepest point Discharge_timeseries.csv : contains time series of stream water level and discharge with a 5-minute temporal resolution Cryoconite_hole_water_level.csv : contains time series of water level measured from a cryoconite hole with a 5-minute temporal resolution is shown Gauging_Station.zip : contains an ESRI shapefile with point data of the gauging station Stream_network.zip : contains an ESRI shapefile with the stream network Catchment_boundary.zip : contains an ESRI shapefile with the catchment boundary Please refer to the publication associated with this dataset for detailed uncertainty analysis and more information: Muthyala, R., Rennermalm, Å. K., Leidman, S. Z., Cooper, M. G., Cooley, S. W., Smith, L. C., and van As, D.: Supraglacial streamflow and meteorological drivers from southwest Greenland, The Cryosphere, 16, 2245–2263, https://doi.org/10.5194/tc-16-2245-2022, 2022.

This record is for the dataset “ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019 ” at <a href="https://doi.org/10.3334/ORNLDAAC/1643 ">https://doi.org/10.3334/ORNLDAAC/1643</a><p><p> This dataset contains a high-resolution land cover classification focused on water and wetland vegetation classes over three NASA ABoVE Campaign regions: Yukon Flats, Alaska, USA; the Peace-Athabasca Delta, Alberta; and the Canadian Shield, Northwest Territories (NWT), Canada. The product was derived from L-band synthetic aperture radar (SAR) acquisitions from the airborne NASA UAVSAR instrument in 2017-2019. The classification was trained and validated from field visits, UAV images, satellite imagery as well as other ABoVE datasets. Classifications in all regions are provided as both preliminary 13-class versions and final, simplified 5-class versions. Training and test data used for the classifier are also included as well as characteristics of lakes in the study area. This land cover classification was developed to support a project focusing on potential methane emissions from the shallow near-shore, or littoral, regions of lakes. The emergent aquatic vegetation classes can be used as a proxy for these littoral zones. Wetland vegetation classifications are provided as gridded raster files with an approximately 5-meter spatial resolution and aligned with the original UAVSAR footprints. Composite mosaics that aggregate these UAVSAR scenes by region and day of acquisition, if applicable, are also provided. Classifications in all regions are provided as both preliminary 13-class versions and final 5-class versions. <p> This dataset can be downloaded at <a href="https://doi.org/10.3334/ORNLDAAC/1643 ">https://doi.org/10.3334/ORNLDAAC/1643</a>

This dataset contains water level records derived from ICESat-2 for 227,386 lakes spanning Oct 14, 2018 to July 16, 2020. A complete description of the method used to derive water level from ICESat-2 can be found in Cooley et al (2021), but is briefly summarized below: We create a conservative water mask modified from the Global Surface Water Occurrence (GSWO) product (Pekel et al., 2016); We intersect ATL08 mean terrain height returns with this water mask, requiring water bodies to receive at least three ICESat-2 point observations on the same day to be included in the analysis; We filter observations based on the mean standard deviation of returns, among other factors; We aggregate observations to monthly timesteps; We calculate seasonal variability in water level as the maximum minus the minimum monthly water level over the 22-month period. This dataset contains: ICESat2_lake_variability_v1_Nov2020.shp: A shapefile containing lake points and summary statistics (i.e. height variability, storage variability, etc) ICESat2_lake_height_time_series_v1_Nov2020.csv: A csv file of the monthly water height time series used to calculate the global lake level variability 265 water mask GeoTiffs: Water masks created from GSWO which we intersect with ICESat-2 data to produce the water level time series. ICESat2_mask_reference_v1_Nov2020.csv – A csv file which lists the corresponding water mask for each water body in the dataset USGS_height_validation_v1_Nov2020.csv – A csv file containing the height comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses USGS_range_validation_v1_Nov2020.csv – A csv file containing the range comparison between ICESat-2 and USGS gauges used for validation and uncertainty analyses California_storage_validation_v1_Nov2020.csv – A csv file containing the storage comparison between ICESat-2 and California Department of Water Resource gauges used for validation and uncertainty analyses See the README file for a more detailed description of this dataset. Anyone wishing to use this dataset should cite Cooley et al. 2021) and contact Sarah Cooley at [email protected] with a description of the work and any questions so that we may offer guidance in regards to the best usage of our dataset. Cooley, S.W., Ryan, J.C., and Smith, L.C., (2021), Human alteration of global surface water storage variability, Nature, https://doi.org/10.1038/s41586-021-03262-3

This dataset contains the raw irradiance values that can be used to compute transmittance and attenuation coefficient, and are not interpolated or filtered, so the user can decide how to use the data.