Monthly Frontal Ablation at 147 Tidewater Glaciers in Svalbard (2015-2024)

Frontal ablation measurements have long been limited to annual and decadal temporal resolution, leaving a knowledge gap in the intra-annual and seasonal variability. To address the temporal evolution, improve the process understanding of frontal ablation, and provide much needed reference data for the modeling community, we present a frontal ablation dataset for 147 tidewater glaciers in Svalbard at a monthly temporal resolution. As proper frontal ablation computation requires frontal information (i.e. calving fronts), which is inherently time- and labor-intensive to digitize manually, we employ a multi-temporal deep learning segmentation model (Dreier et al., 2025, 2026) to automate the mapping of glacier termini using a Sentinel-1 SAR image time series from January 2015 to December 2024. The result is a dataset with 15,500 frontal ablation estimates (88% temporal coverage), derived from 15,647 monthly-averaged calving front segmentations. For months missing frontal information in a glacier’s time series, frontal area changes over the data gaps are linearly interpolated to produce an additional 1,840 estimates, giving 99% total temporal coverage. In addition, a monthly time series of ice velocity and discharge is provided, developed from ITS_LIVE velocity datacubes (Gardner et al., 2025) and existing, regional ice thickness products (Fürst et al., 2018; Hugonnet et al., 2021; Malz et al., 2021). Climatic mass balance (CMB) is estimated to correct for ice mass loss due to atmospheric processes between the fluxgate (where ice velocity and thickness are sampled) and the glacier terminus; this area is referred to as the glacier domain. We aggregate daily, modeled CMB outputs from the MAR regional climate model (Fettweis and Grailet, 2024) to a monthly resolution over the glacier domain. Two NetCDF files are published here; (1) the monthly frontal ablation time series for all 147 glaciers and (2) the monthly ice velocity and discharge time series for all glaciers. Data variables are named and descriptions/units are given (when applicable) in both files for additional context. A GeoPackage containing relevant vector geometries for training the segmentation model at Svalbard and producing the frontal ablation time series is also published. The layers include regional ice, ocean, and land zone labels encompassing Svalbard and its tidewater glaciers. The ice zone label was originally derived from the Randolph Glacier Inventory version 6 (RGI Consortium, 2017), but the ice extent is updated at the terminus of each studied glacier using manually digitized terminus polygons (also provided as a layer) from Kochtitzky et al. (2022). The 15,647 monthly-averaged fronts and temporally matching monthly glacier domain polygons are provided as well. Other layers include the fluxgates, fluxgate sampling points, ice flow orientation points (points forward of the fluxgate and behind the glacier terminus), and RGI basin sampling boxes used for the preprocessing of SAR imagery and postprocessing of the segmentation model’s predictions. The main RGI boxes are particularly important as they provide glacier metadata (name, RGI-ID, etc.) and a summary of decadal-averaged results per glacier. All 11 layers are assembled into a preset QGIS project for easy visualization in the 'svalbard_frontal_ablation.qgz' file. Below is a table defining the data variables in the ‘sval_rgi_boxes’ layer in the GeoPackage: Lansat_ID ID of Landsat-8 image used to map the 2019 terminus by Kochtitzky et al. (2022) RGIId Randolph Glacier Inventory version 6 identifier GLIMSId Global Land Ice Measurements from Space identifier Name Tidewater glacier name RGIId_v7 Randolph Glacier Inventory version 7 identifier RGIv7_surge_type Denotes the surge type tag included in RGI v7; 0 = No evidence, 1 = Possible, 2 = Probable, 3 = Observed, 9 = N/A Region Abbreviated tag for Svalbard’s distinct subregions (SS – South Spitsbergen, NW – Northwest Spitsbergen, NE – Northeast Spitsbergen, AF – Austfonna Ice Cap, VF – Vestfonna Ice Cap, BE - Barentsøya and Edgeøya, KV – Kvitøya) terminus_length_km Decadal terminus length of all available terminus geometries (averaged per year, then years averaged over decade) frontal_ablation Decadal frontal ablation rate in Gt a-1 frontal_ablation_unc Decadal frontal ablation rate uncertainty in Gt a-1 FA_rank Indicates the glacier’s rank of frontal ablation magnitude relative to all 147 glaciers, with 1 being the strongest and 147 the weakest peak_year Distinguishes the year with the strongest frontal ablation rate in the glacier’s time series total_percent Total contribution (%) to Svalbard’s total decadal frontal ablation rate ice_discharge Decadal ice discharge rate in Gt a-1 ice_discharge_unc Decadal ice discharge rate uncertainty in Gt a-1 tmc Decadal terminus mass change rate in Gt a-1 (TMC is defined as the decadal frontal area change – CMB) tmc_unc Decadal terminus mass change rate uncertainty in Gt a-1