Distribution of debris thickness and its effect on ice melt at Hailuogou glacier, southeastern Tibetan Plateau, using in situ surveys and ASTER imagery

Zhang, Yong; Fujita, Koji; Liu, Shiyin; Liu, Qiao; Nuimura, T.

doi:10.3189/002214311798843331

Cited by 147 publications

(178 citation statements)

References 32 publications

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“…The few available field measurements do not support a relationship between debris thickness and elevation (e.g., Mihalcea et al, 2006;Reid et al, 2012). However, measurements on the Tibetan Plateau (Zhang et al, 2011) in Nepal (Nicholson and Benn, 2012), and in the Karakoram (Mihalcea et al, 2008a) indicate that thicker values are more prevalent near glacier termini, while thinner ones are more ubiquitous up-glacier.…”

Section: Specification Of Debris Extent and Thickness In Wrf D3mentioning

confidence: 97%

“…Specifying the debris thickness was more complex, since this field varies strongly over small spatial scales. For example, Nicholson and Benn (2012) reported very heterogeneous debris thicknesses on the Ngozumpa glacier, Nepal, varying between 0.5 and 2.0 m over distances of less than 100 m. Spatial variability arises from many factors, including hillslope fluxes to the glacier; surface and subsurface transport and, the presence of ice cliffs, melt ponds and crevasses (e.g., Brock et al, 2010;Zhang et al, 2011). The few available field measurements do not support a relationship between debris thickness and elevation (e.g., Mihalcea et al, 2006;Reid et al, 2012).…”

Section: Specification Of Debris Extent and Thickness In Wrf D3mentioning

confidence: 99%

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Impact of debris cover on glacier ablation and atmosphere–glacier feedbacks in the Karakoram

et al. 2015

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Abstract. The Karakoram range of the Hindu-Kush Himalaya is characterized by both extensive glaciation and a widespread prevalence of surficial debris cover on the glaciers. Surface debris exerts a strong control on glacier surface-energy and mass fluxes and, by modifying surface boundary conditions, has the potential to alter atmosphereglacier feedbacks. To date, the influence of debris on Karakoram glaciers has only been directly assessed by a small number of glaciological measurements over short periods. Here, we include supraglacial debris in a high-resolution, interactively coupled atmosphere-glacier modeling system. To investigate glaciological and meteorological changes that arise due to the presence of debris, we perform two simulations using the coupled model from 1 May to 1 October 2004: one that treats all glacier surfaces as debris-free and one that introduces a simplified specification for the debris thickness. The basin-averaged impact of debris is a reduction in ablation of ∼ 14 %, although the difference exceeds 5 m w.e. on the lowest-altitude glacier tongues. The relatively modest reduction in basin-mean mass loss results in part from non-negligible sub-debris melt rates under thicker covers and from compensating increases in melt under thinner debris, and may help to explain the lack of distinct differences in recent elevation changes between clean and debriscovered ice. The presence of debris also strongly alters the surface boundary condition and thus heat exchanges with the atmosphere; near-surface meteorological fields at lower elevations and their vertical gradients; and the atmospheric boundary layer development. These findings are relevant for glacio-hydrological studies on debris-covered glaciers and contribute towards an improved understanding of glacier behavior in the Karakoram.

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Section: Specification Of Debris Extent and Thickness In Wrf D3mentioning

confidence: 97%

Section: Specification Of Debris Extent and Thickness In Wrf D3mentioning

confidence: 99%

Impact of debris cover on glacier ablation and atmosphere–glacier feedbacks in the Karakoram

et al. 2015

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“…Nakawo and Rana (1999) also commented on areas with exposed ice cliffs reducing the surface temperature of the pixel, thereby lowering the calculated thermal resistances. Zhang et al (2011) did not address the low values of thermal resistances, but did attribute the small disagreement between modeled and observed melt rates to the unknown variations in meteorological conditions caused by altitude, aspect, and shading in different areas, as well as the unknown nature of water content in the debris. The mixed-pixel effect and the spatial variation in meteorological conditions may reduce the thermal resistances, but it is unlikely to cause the satellitederived thermal resistances to be 1 or 2 orders of a magnitude lower than those found in the field.…”

Section: R Rounce and D C Mckinney: Debris Thickness Of Glaciermentioning

confidence: 99%

“…These studies use surface temperature data from satellite imagery in conjunction with an energy balance model to solve for the thermal resistance, which is the debris thickness divided by the thermal conductivity (Nakawo and Rana, 1999;Nakawo et al, 1999;Suzuki et al, 2007;Zhang et al, 2011). If the thermal conductivity of the debris is known, the model can solve directly for debris thickness (Foster et al, 2012).…”

Section: R Rounce and D C Mckinney: Debris Thickness Of Glaciermentioning

confidence: 99%

Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

2014

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Abstract. Debris thickness is an important characteristic of debris-covered glaciers in the Everest region of the Himalayas. The debris thickness controls the melt rates of the glaciers, which has large implications for hydrologic models, the glaciers' response to climate change, and the development of glacial lakes. Despite its importance, there is little knowledge of how the debris thickness varies over these glaciers. This paper uses an energy balance model in conjunction with Landsat7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery to derive thermal resistances, which are the debris thickness divided by the thermal conductivity. Model results are reported in terms of debris thickness using an effective thermal conductivity derived from field data. The developed model accounts for the nonlinear temperature gradient in the debris cover to derive reasonable debris thicknesses. Fieldwork performed on ImjaLhotse Shar Glacier in September 2013 was used to compare to the modeled debris thicknesses. Results indicate that accounting for the nonlinear temperature gradient is crucial. Furthermore, correcting the incoming shortwave radiation term for the effects of topography and resampling to the resolution of the thermal band's pixel is imperative to deriving reasonable debris thicknesses. Since the topographic correction is important, the model will improve with the quality of the digital elevation model (DEM). The main limitation of this work is the poor resolution (60 m) of the satellite's thermal band. The derived debris thicknesses are reasonable at this resolution, but trends related to slope and aspect are unable to be modeled on a finer scale. Nonetheless, the study finds this model derives reasonable debris thicknesses on this scale and was applied to other debris-covered glaciers in the Everest region.

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“…Some studies have characterized the small-scale glacier surface topography of debris-covered glaciers using field-based surveys (Iwata et al, 2000;Sakai and Fujita, 2010;Zhang et al, 2011), while other studies focused on understanding patterns at the mountain-range scale (Scherler et al, 2011;Bolch et al, 2012;Gardelle et al, 2013;Racoviteanu et al, 2014). Glacier shrinkage and mass loss has been documented in the Himalaya concomitantly with an increase in debris cover Nuimura et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Spatial patterns in glacier characteristics and area changes from 1962 to 2006 in the Kanchenjunga–Sikkim area, eastern Himalaya

et al. 2015

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Abstract. This study investigates spatial patterns in glacier characteristics and area changes at decadal scales in the eastern Himalaya -Nepal (Arun and Tamor basins), India (Teesta basin in Sikkim) and parts of China and Bhutan -based on various satellite imagery: Corona KH4 imagery, Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission Radiometer (ASTER), QuickBird (QB) and WorldView-2 (WV2). We compare and contrast glacier surface area changes over the period of 1962-2000/2006 and their dependency on glacier topography (elevation, slope, aspect, percent debris cover) and climate (solar radiation, precipitation) on the eastern side of the topographic barrier (Sikkim) versus the western side (Nepal).Glacier mapping from 2000 Landsat ASTER yielded 1463 ± 88 km 2 total glacierized area, of which 569 ± 34 km 2 was located in Sikkim and 488 ± 29 km 2 in eastern Nepal. Supraglacial debris covered 11 % of the total glacierized area, and supraglacial lakes covered about 5.8 % of the debris-covered glacier area alone. Glacier area loss (1962 to 2000) was 0.50 ± 0.2 % yr −1 , with little difference between Nepal (0.53 ± 0.2 % yr −1 ) and Sikkim (0.44 ± 0.2 % yr −1 ). Glacier area change was controlled mostly by glacier area, elevation, altitudinal range and, to a smaller extent, slope and aspect. In the Kanchenjunga-Sikkim area, we estimated a glacier area loss of 0.23 ± 0.08 % yr −1 from 1962 to 2006 based on high-resolution imagery. On a glacier-by-glacier basis, clean glaciers exhibit more area loss on average from 1962 to 2006 (34 %) compared to debris-covered glaciers (22 %). Glaciers in this region of the Himalaya are shrinking at similar rates to those reported for the last decades in other parts of the Himalaya, but individual glacier rates of change vary across the study area with respect to local topography, percent debris cover or glacier elevations.

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Distribution of debris thickness and its effect on ice melt at Hailuogou glacier, southeastern Tibetan Plateau, using in situ surveys and ASTER imagery

Cited by 147 publications

References 32 publications

Impact of debris cover on glacier ablation and atmosphere–glacier feedbacks in the Karakoram

Impact of debris cover on glacier ablation and atmosphere–glacier feedbacks in the Karakoram

Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model

Spatial patterns in glacier characteristics and area changes from 1962 to 2006 in the Kanchenjunga–Sikkim area, eastern Himalaya

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