@inproceedings{22119, author = {Muñoz Hermosilla, José M and Miles, Evan and McCarthy, Michael and Melo Velasco, Juan Vicente and Hardmeier, Florian and GANTAYAT, PRATEEK and Fontrodona-Bach, Adrià and Jouvet, Guillaume and Pellicciotti, Francesca}, booktitle = {EGU General Assembly 2026}, location = {Vienna, Austria & Virtual}, publisher = {European Geosciences Union}, title = {{Constraining debris input to Oberaletsch Glacier using ensemble-based Lagrangian modelling}}, doi = {10.5194/egusphere-egu26-19367}, year = {2026}, } @article{19878, abstract = {Rock debris partially covers glaciers worldwide, with varying extents and distributions, and controls sub‐debris melt rates by modifying energy transfer from the atmosphere to the ice. Two key physical properties controlling this energy exchange are thermal conductivity (k) and aerodynamic roughness length (z0). Accurate representation of these properties in energy‐balance models is critical for understanding climate‐glacier interactions and predicting the behavior of debris‐covered glaciers. However, k and z0 have been derived at very few sites from limited local measurements, using different approaches, and most model applications rely on values reported from these few sites and studies. We derive k and z0 using established and modified approaches from data at three locations on Pirámide Glacier in the central Chilean Andes. By comparing methods and evaluating melt simulated with an energy‐balance model, we reveal substantial differences between approaches. These lead to discrepancies between ice melt from energy‐balance simulations and observed data, and highlight the impact of method choice on calculated ice melt. Optimizing k against measured melt appears a viable approach to constrain melt simulations. Determining z0 seems less critical, as it has a smaller impact on total melt. Profile aerodynamic method measurements for estimating z0, despite higher costs, are independent of ice melt calculations. The large, unexpected differences between methods indicate a substantial knowledge gap. The fact that field‐derived k and z0 fail to work well in energy‐balance models, suggests that model values represent bulk properties distinct from theoretical field measurements. Addressing this gap is essential for improving glacier melt predictions.}, author = {Melo Velasco, Juan Vicente and Miles, Evan and McCarthy, Michael and Shaw, Thomas and Fyffe, Catriona Louise and Fontrodona-Bach, Adrià and Pellicciotti, Francesca}, issn = {2169-9011}, journal = {Journal of Geophysical Research: Earth Surface}, number = {6}, publisher = {Wiley}, title = {{Method dependence in thermal conductivity and aerodynamic roughness length estimates on a debris‐covered glacier}}, doi = {10.1029/2025jf008360}, volume = {130}, year = {2025}, } @article{20546, abstract = {Rocky debris covers around 7.3 % of the global glacier area, influencing ice melt rates and the surface mass balance of glaciers, making the dynamics and hydrology of debris-covered glaciers distinct from those of clean-ice glaciers. Accurate representation of debris in models is challenging, as measurements of the physical properties and thickness of the supraglacial debris layer are scarce. Here, we compile a database of measured and reported bulk physical properties and layer thicknesses of supraglacial debris that we call the supraglacial Debris Database (DebDaB) and that is open to community submissions. The majority of the database (90 %) is compiled from 172 sources in the literature, and the remaining 10 % was previously unpublished. DebDaB contains 8741 data entries for supraglacial debris layer thickness, of which 1770 entries also include sub-debris ablation rates, 179 thermal conductivity of debris, 160 aerodynamic surface roughness length, 79 debris albedo, 59 debris emissivity, and 37 debris porosity. The data are distributed over 84 glaciers in 13 regions in the Global Terrestrial Network for Glaciers. We show regional differences in the distribution of debris thickness measurements in DebDaB and fit simplified Østrem curves to 19 glaciers with sufficient debris thickness and ablation data. The data in DebDaB can be used for energy balance, melt, and surface mass balance studies by incorporating site-specific debris properties or for evaluation of remote sensing estimates of debris thickness and surface roughness. They can also help future field campaigns on debris-covered glaciers by identifying observation gaps. DebDaB's uneven spatial coverage points to sampling biases in community efforts to observe debris-covered glaciers, with some regions (e.g. central Europe and South Asia) well-sampled but others having gaps with prevalent debris (e.g. the Andes and Alaska). Debris thickness measurements are mostly concentrated at lower elevations, leaving higher-elevation debris-covered areas undersampled and suggesting that our knowledge of debris properties might not be representative of all elevations. The aims of DebDaB, as an openly available dataset, are to evolve over time, to be updated, and to add to community submissions as new data on supraglacial properties become available. The data described in this paper can be accessed from Zenodo at https://doi.org/10.5281/zenodo.14224835 (Groeneveld et al., 2025).}, author = {Fontrodona-Bach, Adrià and Groeneveld, Lars and Miles, Evan and McCarthy, Michael and Shaw, Thomas and Melo Velasco, Juan Vicente and Pellicciotti, Francesca}, issn = {1866-3516}, journal = {Earth System Science Data}, number = {8}, pages = {4213--4234}, publisher = {Copernicus Publications}, title = {{DebDaB: A database of supraglacial debris thickness and physical properties}}, doi = {10.5194/essd-17-4213-2025}, volume = {17}, year = {2025}, } @misc{20547, abstract = {DebdaB is a database of measured and reported physical properties and thickness of supraglacial debris that is openly available and open to community submissions. The majority of the database (90%) is compiled from 172 sources in the literature, and the remaining 10% has not been published before. DebDaB contains 8,286 data entries for supraglacial debris thickness, of which 1,852 entries also include sub-debris ablation rates, 167 data entries of thermal conductivity of debris, 157 of aerodynamic surface roughness length, 77 of debris albedo, 56 of debris emissivity and 37 of debris porosity. The data are distributed over 83 glaciers in 13 regions in the Global Terrestrial Network for Glaciers. }, author = {Groeneveld, Lars and Fontrodona-Bach, Adrià and Miles, Evan and McCarthy, Michael and Melo Velasco, Juan Vicente and Shaw, Thomas and Pellicciotti, Francesca and Bauder, Andreas and Buri, Pascal and Kneib, Marin and Kumar, Amit and Mishra, Aditya and Petersen, lene and Renner, Roman and Schmid, Sandro}, publisher = {Zenodo}, title = {{DebDaB: A database of supraglacial debris thickness and physical properties}}, doi = {10.5281/ZENODO.14224835}, year = {2025}, } @inproceedings{22120, author = {Muñoz Hermosilla, José M and Miles, Evan and McCarthy, Michael and Hardmeier, Florian and Melo Velasco, Juan Vicente and Jouvet, Guillaume and Pellicciotti, Francesca}, booktitle = {EGU General Assembly 2025}, location = {Vienna, Austria & Virtual}, publisher = {European Geosciences Union}, title = {{Towards reconstructing debris supply to reproduce the historic changes in debris extent at a Swiss glacier}}, doi = {10.5194/egusphere-egu25-17446}, year = {2025}, }