Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions
Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Sa...
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Published in: | Remote sensing of environment Vol. 283; p. 113307 |
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15-12-2022
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Abstract | Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two end member study sites. We analyze ∼3 years of data for Reynolds Creek Experimental Watershed in Idaho's Owyhee Mountains and Wolverine Glacier in southcentral Alaska's Kenai Mountains. Our analysis reveals decimeter-scale uncertainties in derived snow depth and glacier mass balance at the watershed scale. Both accuracy and precision decrease as slope increases: the magnitudes of the median and median of the absolute deviation of elevation errors (MAD) vary from ∼0.2 m for slopes <5° to >1 m for slopes >20°. For glacierized regions, failure to account for intra- and inter-annual evolution of glacier surface elevations can strongly bias ATL06 elevations, resulting in under-estimation of the mass balance gradient with elevation. Based on these results, we conclude that ATL08 and ATL06 observations are best suited for characterization of watershed-scale snow depth and mass balance gradients over relatively shallow slopes with thick snowpacks. In these regions, ICESat-2 elevation residual-derived snow depth and mass balance transects can provide valuable watershed scale constraints on terrain parameter- and model-derived estimates of snow accumulation and melt.
•ICESat-2 level3a datasets can be used to map watershed-scale snow depth gradients.•ATL08 ground elevations must be corrected for slope-dependent bias.•ATL08 ground elevation uncertainty increases with slope to >1 m above 20 degrees.•Mass balance gradients from ATL06 data require reference elevation timeseries.•ATL06 mass balance gradients can capture seasonal variability in maritime climates. |
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AbstractList | Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two end member study sites. We analyze ∼3 years of data for Reynolds Creek Experimental Watershed in Idaho's Owyhee Mountains and Wolverine Glacier in southcentral Alaska's Kenai Mountains. Our analysis reveals decimeter-scale uncertainties in derived snow depth and glacier mass balance at the watershed scale. Both accuracy and precision decrease as slope increases: the magnitudes of the median and median of the absolute deviation of elevation errors (MAD) vary from ∼0.2 m for slopes <5° to >1 m for slopes >20°. For glacierized regions, failure to account for intra- and inter-annual evolution of glacier surface elevations can strongly bias ATL06 elevations, resulting in under-estimation of the mass balance gradient with elevation. Based on these results, we conclude that ATL08 and ATL06 observations are best suited for characterization of watershed-scale snow depth and mass balance gradients over relatively shallow slopes with thick snowpacks. In these regions, ICESat-2 elevation residual-derived snow depth and mass balance transects can provide valuable watershed scale constraints on terrain parameter- and model-derived estimates of snow accumulation and melt.
•ICESat-2 level3a datasets can be used to map watershed-scale snow depth gradients.•ATL08 ground elevations must be corrected for slope-dependent bias.•ATL08 ground elevation uncertainty increases with slope to >1 m above 20 degrees.•Mass balance gradients from ATL06 data require reference elevation timeseries.•ATL06 mass balance gradients can capture seasonal variability in maritime climates. |
ArticleNumber | 113307 |
Author | O'Neel, Shad Florentine, Caitlyn Elkin, Colten M. McNeil, Christopher Sass, Louis Marshall, H.P. Enderlin, Ellyn M. Gendreau, Madeline |
Author_xml | – sequence: 1 givenname: Ellyn M. surname: Enderlin fullname: Enderlin, Ellyn M. email: ellynenderlin@boisestate.edu organization: Boise State University Department of Geosciences, 1910 W University Drive, Boise, ID 83703; United States of America – sequence: 2 givenname: Colten M. surname: Elkin fullname: Elkin, Colten M. organization: Boise State University Department of Geosciences, 1910 W University Drive, Boise, ID 83703; United States of America – sequence: 3 givenname: Madeline surname: Gendreau fullname: Gendreau, Madeline organization: Boise State University Department of Geosciences, 1910 W University Drive, Boise, ID 83703; United States of America – sequence: 4 givenname: H.P. surname: Marshall fullname: Marshall, H.P. organization: Boise State University Department of Geosciences, 1910 W University Drive, Boise, ID 83703; United States of America – sequence: 5 givenname: Shad surname: O'Neel fullname: O'Neel, Shad organization: Boise State University Department of Geosciences, 1910 W University Drive, Boise, ID 83703; United States of America – sequence: 6 givenname: Christopher surname: McNeil fullname: McNeil, Christopher organization: United States Geological Survey, Alaska Science Center, 4210 University Drive, Anchorage, AK 99508, United States of America – sequence: 7 givenname: Caitlyn surname: Florentine fullname: Florentine, Caitlyn organization: United States Geological Survey, Northern Rocky Mountain Science Cente, 169 Mather Drive, West, Glacier, MT 59936, United States of America – sequence: 8 givenname: Louis surname: Sass fullname: Sass, Louis organization: United States Geological Survey, Alaska Science Center, 4210 University Drive, Anchorage, AK 99508, United States of America |
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CitedBy_id | crossref_primary_10_1029_2022EA002479 crossref_primary_10_5194_tc_18_889_2024 crossref_primary_10_1016_j_rse_2023_113817 crossref_primary_10_1016_j_rse_2023_113843 crossref_primary_10_1016_j_earscirev_2024_104751 crossref_primary_10_3390_rs16010203 crossref_primary_10_1038_s41597_024_03428_4 crossref_primary_10_1016_j_rse_2024_114163 crossref_primary_10_3390_rs16030546 crossref_primary_10_1002_hyp_14996 crossref_primary_10_5194_hess_27_4637_2023 crossref_primary_10_5194_tc_17_2779_2023 crossref_primary_10_3389_feart_2023_1076732 |
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Keywords | Validation ATL06 Snow Glacier ICESat-2 Terrain LiDAR Vegetation ATL08 |
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Title | Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions |
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