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Table · dataset · 2026

Estimating supraglacial lake bottom ablation rates

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<p dir="ltr">This repository provides the code and datasets corresponding to the manuscript "Estimating supraglacial lake bottom ablation rates by integrating ICESat-2 repeat-track data and multi-temporal Sentinel-2 imagery".

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The repository includes three main folders: Code, Input_data, and Output_data.</p><p><br></p><p dir="ltr"><i>Code</i></p><p dir="ltr">This folder contains three parts.</p><p dir="ltr">01_Meltwater-covered_days_from_Sentinel-2</p><p dir="ltr">This folder contains the code used to extract meltwater-covered days from Sentinel-2 imagery.</p><p dir="ltr">"Step1_Download_s2.ipynb" downloads Sentinel-2 imagery using Google Earth Engine.</p><p dir="ltr">"Step2_Filter_image.ipynb" manually filters the downloaded Sentinel-2 images.</p><p dir="ltr">"Step3_Meltwater-covered_days.ipynb" extracts daily meltwater extent and calculates cumulative meltwater-covered days.</p><p><br></p><p dir="ltr">02_Ablation_depth_from_ICESat-2</p><p dir="ltr">This folder contains the code used to extract elevations from ICESat-2 data.</p><p dir="ltr">"Step1_Ice_surface.ipynb" extracts ice-surface elevations using a modified open-source algorithm.</p><p dir="ltr">"Step2_Ice_surface_to_point.ipynb" aggregates the extracted ice-surface elevations into sample points at 10 m intervals.</p><p dir="ltr">"Step3_Supraglacial_lake_watta.txt" refers to MATLAB code that extracts supraglacial lake surface and bottom elevations using the Watta algorithm.</p><p dir="ltr">"Step4_Supraglacial_lake_watta_to_point.ipynb" aggregates the extracted supraglacial lake elevation into sample points at 10 m intervals.</p><p><br></p><p dir="ltr">03_Ablation_rates</p><p dir="ltr">This folder contains the code used to calculate ablation depths and ablation rates.</p><p dir="ltr">"Step1_Ablation_depth_plot.ipynb" calculates the ablation depths of supraglacial lake bottoms and surrounding bare ice, and generates the corresponding figures.</p><p dir="ltr">"Step2_MAR_create_percentages.py" and "Step3_MAR_effective_melt_days.ipynb" determine the number of effective melt days from MAR data.</p><p dir="ltr">"Step4_Ablation_rate_plot.ipynb" performs linear fitting to obtain ablation rates, and generates the corresponding figures.</p><p><br></p><p dir="ltr"><i>Input_data</i></p><p dir="ltr">This folder mainly contains the shapefile, basic attributes, and ICESat-2 ATL03/06 data sources for an example depression, depression22158, which can be used to test the code.</p><p dir="ltr">The MAR folder provides the shapefiles of the ice-surface catchments corresponding to 26 lakes, the MAR data source used in this study, and its grid information.</p><p dir="ltr">The All_lakes folder provides the shapefiles and basic attributes of the depressions corresponding to 26 lakes.</p><p><br></p><p dir="ltr"><i>Output_data</i></p><p dir="ltr">The ATL03_20190503212504_05440305_006_02.h5_gt2l_depression22158 folder provides the complete processing outputs, results, and figures for the single example depression, depression22158.</p><p dir="ltr">The All_lakes folder provides the main results and figures for the 26 lakes analyzed in this study.</p><p><br></p>

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