Glacial melt under a porous debris layer

Evatt, Geoffrey W.; Abrahams, I. David; Heil, Matthias; Mayer, Christoph; Kingslake, J.; Mitchell, Sarah; Fowler, A. C.; Clark, Christopher D.

doi:10.3189/2015jog14j235

Cited by 92 publications

(115 citation statements)

References 24 publications

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“…Debris is generally thin at higher elevations and thickens downglacier due to various processes, e.g., rockfall, (re)surfacing of englacial debris and erosion of lateral moraine material (Evatt et al, 2015). In practice, however, debris thickness and ice melt rates can be quite variable on small scales (Rounce and McKinney, 2014), resulting in heterogeneous thinning and the hummocky surface that is often observed on debris-covered glaciers.…”

Section: Introductionmentioning

confidence: 97%

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

et al. 2018

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A layer of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya, and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption, and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with −1.4 ± 1.8, 11.0 ± 5.2, and 15.3 ± 4.7 • C for the three flights (mean ± sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 • C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.

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Section: Introductionmentioning

confidence: 97%

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

et al. 2018

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“…Debris‐covered glaciers are distributed globally, representing a distinctive minority of total glacier area. Although debris‐covered glaciers have received focused study in recent years, the interactions of a debris‐covered glacier with the atmosphere are complex and some physical processes remain poorly understood [ Brock et al , ; Collier et al , , ; Rounce et al , ; Evatt et al , ]. Debris cover heavily modifies the primary processes of energy exchange between the atmosphere and the glacier surface.…”

Section: Introductionmentioning

confidence: 99%

Highly variable aerodynamic roughness length (z₀) for a hummocky debris‐covered glacier

2017

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The aerodynamic roughness length (z0) is an essential parameter in surface energy balance studies, but few literature values exist for debris‐covered glaciers. We use microtopographic and aerodynamic methods to assess the spatial variability of z0 for Lirung Glacier, Nepal. We apply structure from motion to produce digital elevation models for three nested domains: five 1 m2 plots, a 21,300 m2 surface depression, and the lower 550,000 m2 of the debris‐mantled tongue. Wind and temperature sensor towers were installed in the vicinity of the plots within the surface depression in October 2014. We calculate z0 according to a variety of transect‐based microtopographic parameterizations for each plot, then develop a grid version of the algorithms by aggregating data from all transects. This grid approach is applied to the surface depression digital elevation model to characterize z0 spatial variability. The algorithms reproduce the same variability among transects and plots, but z0 estimates vary by an order of magnitude between algorithms. Across the study depression, results from different algorithms are strongly correlated. Using Monin‐Obukov similarity theory, we derive z0 values from the meteorological data. Using different stability criteria, we derive median values of z0 between 0.03 m and 0.05 m, but with considerable uncertainty due to the glacier's complex topography. Considering estimates from these algorithms, results suggest that z0 varies across Lirung Glacier between ∼0.005 m (gravels) to ∼0.5 m (boulders). Future efforts should assess the importance of such variable z0 values in a distributed energy balance model.

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“…However, our knowledge of these glaciers needs to progress to determine their response to current climatic change, and the impact these changes will have on the people who rely on them. Supraglacial debris distribution is important when calculating glacier mass balance, as such debris layers attenuate the ablation of the underlying ice depending on the debris thickness (Evatt et al, 2015;Østrem, 1959). A thin debris layer (up to around 0.02 m thick), when compared to clean ice, enhances melt by increasing the albedo of the glacier surface, causing it to absorb more solar radiation and melt more quickly than debris-free ice.…”

Section: Introductionmentioning

confidence: 99%

Changes in glacier surface cover on Baltoro glacier, Karakoram, north Pakistan, 2001–2012

et al. 2016

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The presence of supraglacial debris on glaciers in the Himalaya-Karakoram affects the ablation rate of these glaciers and their response to climatic change. To understand how supraglacial debris distribution and associated surface features vary spatially and temporally, geomorphological mapping was undertaken on Baltoro Glacier, Karakoram, for three timeseparated images between 2001-2012. Debris is supplied to the glacier system through frequent but small landslides at the glacier margin that form lateral and medial moraines and less frequent but higher volume rockfall events which are more lobate and often discontinuous in form. Debris on the glacier surface is identified as a series of distinct lithological units which merge downglacier of the convergence area between the GodwinAusten and Baltoro South tributary glaciers. Debris distribution varies as a result of complex interaction between tributary glaciers and the main glacier tongue, complicated further by surge events on some tributary glaciers. Glacier flow dynamics mainly controls the evolution of a supraglacial debris layer. Identifying such spatial variability in debris rock type and temporal variability in debris distribution has implications for glacier ablation rate, affecting glacier surface energy balance. Accordingly, spatial and temporal variation in supraglacial debris should be considered when determining mass balance for these glaciers through time. ARTICLE HISTORY

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Glacial melt under a porous debris layer

Cited by 92 publications

References 24 publications

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

Highly variable aerodynamic roughness length (z₀) for a hummocky debris‐covered glacier

Changes in glacier surface cover on Baltoro glacier, Karakoram, north Pakistan, 2001–2012

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Glacial melt under a porous debris layer

Cited by 92 publications

References 24 publications

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

Highly variable aerodynamic roughness length (z0) for a hummocky debris‐covered glacier

Changes in glacier surface cover on Baltoro glacier, Karakoram, north Pakistan, 2001–2012

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Highly variable aerodynamic roughness length (z₀) for a hummocky debris‐covered glacier