Toward improvement of satellite-derived thermal resistance for supra-glacial debris
Authors: Nagai Hiroto , Nuimura Takayuki , Takigawa Masayuki , Patel Lavkush , Laha Sourav , Pratap Bhanu , Konya Keiko , Sharma Paramanand , Fujita Koji , Sato Yota , Sakai Akiko 
Published: February 2023

Surface melting of alpine glaciers is spatially and temporally heterogeneous and is strongly influenced by climatic and non-climatic variables. Especially supra-glacial debris causes significant uncertainty on the ice melting rate with its physical property and thickness. A thick debris layer decrease ice melting rate, whereas a thin layer increase it with its low albedo. Therefore, a scientific method for spatial quantification of debris influences on the melting rate should be established to assess future projection of glacier shrinkage corresponding to the climate change.Estimating&#160; thermal resistance (TR), which quantifies how hard the ground heat flux (G) travels to ice-debris interface, with remote-sensing data has been attempted in several studies. However, uncertainties caused by the linear temperature gradient have not been resolved, as well as non-negligible underestimation of TR values. Therefore, this study aims to assess TR calculations on multi-spatial and multi-temporal conditions in detail, and discusses the current state of TR estimation and the potential for further improvement.A study site is defined in Satopanth glacier [30.77&#176;N; 79.40&#176;E], a debris-covered glacier located in Garhwal region, India. Sampling domains of 12 circles with 100-m radius are put with 1-km intervals through the flow line of supra-glacial debris. In addition, four circles of the same size were placed outside the glacier in the lower reaches.To calculate TR, first, broadband albedo and surface temperature (Ts) are calculated from all available Landsat-8 data in an orbit path [Path 145; Row 39] acquired from 2013 to the present (N= 81). These have a revisit cycle of 16 days. Cloud-covered pixels and frozen pixels (Ts < 0&#176;C) are removed. Second, downward shortwave/longwave radiations and sensible/latent heat flux are collected from a 1-hour resolution product of ERA5. Combining these inputs, considering surface energy budget, G is calculated as a residue of energy flux, and then TR is calculated as Ts (&#176;C) divided by G.Our result shows a positive correlation that higher Ts leads higher values of G and TR. This trend have no significant difference between debris-covered surface and off-glacier terrains. It suggests that, in most sample areas with relatively thick debris, G does not reach the ice-debris interface. High-gradient inclinations of G versus Ts increase is identified in a lower part of Ts range (0-5&#176;C). It may be caused by heat absorption because of ice mass under relatively thin debris layer, but such inclination is not reflected in TR&#8217;s gradient. In the lower Ts surfaces (0-5&#176;C), slightly lower R is estimated for thinner-debris domains. For the thinner debris layer TR might reflects debris thickness. These features in other multiple glaciers will be shown and compared in the presentation.Our result suggested that maximum debris thickness of G transfer (DTmax) may be defined. Smaller than the DTmax, G transfer may be estimated, whereas larger than the DTmax, G might be zero. In such domain, spatial distributions of ice cliff and supra-glacial pond are more dominant for melting projection. Further assessments might derive a perspective of multiple models for TR estimation according to debris thickness.