Vicente Melo-Velasco, Evan Miles, Michael McCarthy, Thomas E. Shaw, Catriona Fyffe, Adrià Fontrodona-Bach, Francesca Pellicciotti
{"title":"Method Dependence in Thermal Conductivity and Aerodynamic Roughness Length Estimates on a Debris-Covered Glacier","authors":"Vicente Melo-Velasco, Evan Miles, Michael McCarthy, Thomas E. Shaw, Catriona Fyffe, Adrià Fontrodona-Bach, Francesca Pellicciotti","doi":"10.1029/2025JF008360","DOIUrl":null,"url":null,"abstract":"<p>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 <span></span><math>\n <semantics>\n <mrow>\n <mo>(</mo>\n <mi>k</mi>\n <mo>)</mo>\n </mrow>\n <annotation> $(k)$</annotation>\n </semantics></math> and aerodynamic roughness length <span></span><math>\n <semantics>\n <mrow>\n <mfenced>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mfenced>\n </mrow>\n <annotation> $\\left({z}_{0}\\right)$</annotation>\n </semantics></math>. 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, <span></span><math>\n <semantics>\n <mrow>\n <mi>k</mi>\n </mrow>\n <annotation> $k$</annotation>\n </semantics></math> and <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${z}_{0}$</annotation>\n </semantics></math> 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 <span></span><math>\n <semantics>\n <mrow>\n <mi>k</mi>\n </mrow>\n <annotation> $k$</annotation>\n </semantics></math> and <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${z}_{0}$</annotation>\n </semantics></math> 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 <span></span><math>\n <semantics>\n <mrow>\n <mi>k</mi>\n </mrow>\n <annotation> $k$</annotation>\n </semantics></math> against measured melt appears a viable approach to constrain melt simulations. Determining <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${z}_{0}$</annotation>\n </semantics></math> seems less critical, as it has a smaller impact on total melt. Profile aerodynamic method measurements for estimating <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${z}_{0}$</annotation>\n </semantics></math>, 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 <span></span><math>\n <semantics>\n <mrow>\n <mi>k</mi>\n </mrow>\n <annotation> $k$</annotation>\n </semantics></math> and <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${z}_{0}$</annotation>\n </semantics></math> 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.</p>","PeriodicalId":15887,"journal":{"name":"Journal of Geophysical Research: Earth Surface","volume":"130 6","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025JF008360","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Earth Surface","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2025JF008360","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
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 and aerodynamic roughness length . 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, and 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 and 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 against measured melt appears a viable approach to constrain melt simulations. Determining seems less critical, as it has a smaller impact on total melt. Profile aerodynamic method measurements for estimating , 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 and 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.