Response of the Energy Balance on the Margin of the Greenland Ice Sheet to Temperature Changes

Braithwaite, Roger J.; Olesen, Ole Β.

doi:10.1017/s0022143000009461

Cited by 33 publications

(12 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, they become increasingly influential (up to 80%) in overcast and windy conditions [ Holmgren , ; Marcus et al ., ; Giesen et al ., ] and for glacierized regions characterized by maritime climates [ Hay and Fitzharris , ; Ishikawa et al ., ]. Critically, their relative contribution to overall ice surface mass loss is predicted to become more significant in a warming climate [ Braithwaite and Olesen , ], making it imperative that the key influences on turbulent fluxes are better understood. One of the most important of these influences is the aerodynamic roughness height z 0 , which is related to ice surface topographic roughness, in a complex way.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic roughness of glacial ice surfaces derived from high‐resolution topographic data

et al. 2016

View full text Add to dashboard Cite

This paper presents new methods of estimating the aerodynamic roughness (z 0 ) of glacier ice directly from three-dimensional point clouds and digital elevation models (DEMs), examines temporal variability of z 0 , and presents the first fully distributed map of z 0 estimates across the ablation zone of an Arctic glacier. The aerodynamic roughness of glacier ice surfaces is an important component of energy balance models and meltwater runoff estimates through its influence on turbulent fluxes of latent and sensible heat. In a warming climate these fluxes are predicted to become more significant in contributing to overall melt volumes. Ice z 0 is commonly estimated from measurements of ice surface microtopography, typically from topographic profiles taken perpendicular to the prevailing wind direction. Recent advances in surveying permit rapid acquisition of high-resolution topographic data allowing revision of assumptions underlying conventional z 0 measurement. Using Structure from Motion (SfM) photogrammetry with Multi-View Stereo (MVS) to survey ice surfaces with millimeter-scale accuracy, z 0 variation over 3 orders of magnitude was observed. Different surface types demonstrated different temporal trajectories in z 0 through 3 days of intense melt. A glacier-scale 2 m resolution DEM was obtained through terrestrial laser scanning (TLS), and subgrid roughness was significantly related to plot-scale z 0 . Thus, we show for the first time that glacier-scale TLS or SfM-MVS surveys can characterize z 0 variability over a glacier surface potentially leading to distributed representations of z 0 in surface energy balance models.

show abstract

Section: Introductionmentioning

confidence: 99%

Aerodynamic roughness of glacial ice surfaces derived from high‐resolution topographic data

et al. 2016

View full text Add to dashboard Cite

show abstract

“…1). In the light of this, and given that degree-day factors for snow and clean ice vary significantly in space and time (Braithwaite and Olesen, 1990;Hock, 2003), degree-day factors derived for debris-covered ice are likely to be highly site-specific. Hence, currently available empirical and semi-empirical melt functions are spatially limited in their applications.…”

Section: Introductionmentioning

confidence: 99%

Calculating ice melt beneath a debris layer using meteorological data

Nicholson¹,

2006

View full text Add to dashboard Cite

Generalized numerical models of sub-debris ice ablation are preferable to empirical approaches for predicting runoff and glacier response to climate change, as empirical methods are sitespecific and strongly dependent upon the conditions prevailing during the measurement period. We present a modified surface energy-balance model to calculate melt beneath a surface debris layer from daily mean meteorological variables. Despite numerous simplifications, the model performs well and modelled melt rates give a good match to observed melt rates, suggesting that this model can produce reliable estimates of ablation rate beneath debris layers several decimetres thick. This is a useful improvement on previous models which are inappropriate for thick debris cover. PREVIOUS WORKSub-debris melt rate, M (surface lowering in m s -1 ), can be calculated as:where Q m is downward energy flux at the base of the layer (W m -2 ), i is the density of ice (900 kg m -3 ) and L f is the latent heat of fusion (334 kJ kg -1 ). As the energy flux through the debris layer is dominated by heat conduction down a

show abstract

“…Several approaches have been developed for estimating ablation rates, such as empirical regression and degree-day modeling from weather station data, and surface energy balance modeling. The regression and degree-day approaches heavily rely on the availability of local data, and therefore are highly site-specific [15,80]. Consequently, more recent studies use the surface energy balance approach for modeling ablation rate.…”

Section: Ablation Dynamicsmentioning

confidence: 99%

Modeling Surface Processes on Debris-Covered Glaciers: A Review with Reference to the High Mountain Asia

Huo

Chi

2021

Water

View full text Add to dashboard Cite

Surface processes on debris-covered glaciers are governed by a variety of controlling factors including climate, debris load, water bodies, and topography. Currently, we have not achieved a general consensus on the role of supraglacial processes in regulating climate–glacier sensitivity in High Mountain Asia, which is mainly due to a lack of an integrated understanding of glacier surface dynamics as a function of debris properties, mass movement, and ponding. Therefore, further investigations on supraglacial processes is needed in order to provide more accurate assessments of the hydrological cycle, water resources, and natural hazards in the region. Given the scarcity of long-term in situ data and the difficulty of conducting fieldwork on these glaciers, many numerical models have been developed by recent studies. This review summarizes our current knowledge of surface processes on debris-covered glaciers with an emphasis on the related modeling efforts. We present an integrated view on how numerical modeling provide insights into glacier surface ablation, supraglacial debris transport, morphological variation, pond dynamics, and ice-cliff evolution. We also highlight the remote sensing approaches that facilitate modeling, and discuss the limitations of existing models regarding their capabilities to address coupled processes on debris-covered glaciers and suggest research directions.

show abstract

Response of the Energy Balance on the Margin of the Greenland Ice Sheet to Temperature Changes

Cited by 33 publications

References 4 publications

Aerodynamic roughness of glacial ice surfaces derived from high‐resolution topographic data

Aerodynamic roughness of glacial ice surfaces derived from high‐resolution topographic data

Calculating ice melt beneath a debris layer using meteorological data

Modeling Surface Processes on Debris-Covered Glaciers: A Review with Reference to the High Mountain Asia

Contact Info

Product

Resources

About