Elevation Changes of West-Central Greenland Glaciers From 1985 to 2012 From Remote Sensing

Huber, Jacqueline; McNabb, Robert; Zemp, Michael

doi:10.3389/feart.2020.00035

Cited by 22 publications

(20 citation statements)

References 31 publications

(87 reference statements)

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“…Following Zemp and others (2013) and Huber and others (2020), the uncertainty of area-averaged elevation change ( σ ) was estimated from three components: the uncertainty related to spatial autocorrelation in elevation differences ( σ autocorr ), the uncertainty related to the residual elevation errors after co-registration ( σ coreg ) and the uncertainty due to data voids ( σ void ), although this approach may underestimate the total error (Berthier and others, 2012, 2016). …”

Section: Methodsmentioning

confidence: 97%

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

et al. 2020

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Glacier mass loss in Alaska has implications for global sea level rise, fresh water input into the Gulf of Alaska and terrestrial fresh water resources. We map all glaciers (>4000 km2) on the Kenai Peninsula, south central Alaska, for the years 1986, 1995, 2005 and 2016, using satellite images. Changes in surface elevation and volume are determined by differencing a digital elevation model (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer stereo images in 2005 from the Interferometric Synthetic Aperture Radar DEM of 2014. The glacier area shrunk by 543 ± 123 km2 (12 ± 3%) between 1986 and 2016. The region-wide mass-balance rate between 2005 and 2014 was −0.94 ± 0.12 m w.e. a−1 (−3.84 ± 0.50 Gt a−1), which is almost twice as negative than found for earlier periods in previous studies indicating an acceleration in glacier mass loss in this region. Area-averaged mass changes were most negative for lake-terminating glaciers (−1.37 ± 0.13 m w.e. a−1), followed by land-terminating glaciers (−1.02 ± 0.13 m w.e. a−1) and tidewater glaciers (−0.45 ± 0.14 m w.e. a−1). Unambiguous attribution of the observed acceleration in mass loss over the last decades is hampered by the scarcity of observational data, especially at high elevation, and by large interannual variability.

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Section: Methodsmentioning

confidence: 97%

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

et al. 2020

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“…The uncertainties in the estimation of geodetic mass balance due the uncertainty in DEM differencing, radar signal penetration, uncertainty due to void fill, glacier outlines and mass conversion were considered. For the uncertainty assessment, we followed the methodology after Huber et al, (2020) with an additional term to account for the radar penetration error ( σ penetration 2 ) (Abdullah et al, 2020) assuming that all the errors are uncorrelated and random.…”

Section: B) Geodetic Mass Balancementioning

confidence: 99%

“…We assumed a mean value d=950 for glaciers in the study area (Abdullah et al, 2020). The uncertainty due to the TanDEM-X date (σTDXdate) was assumed to be equal to be ±2 times the annual elevation change rate from 2000 to 2012 355 (Huber et al, 2020). The uncertainty in radar penetration was assumed as high as the correction factor itself (Huber et al, 2020).…”

Section: B) Geodetic Mass Balancementioning

confidence: 99%

“…The uncertainty due to the TanDEM-X date (σTDXdate) was assumed to be equal to be ±2 times the annual elevation change rate from 2000 to 2012 355 (Huber et al, 2020). The uncertainty in radar penetration was assumed as high as the correction factor itself (Huber et al, 2020). A constant value of ±60 kg m -3 was used to account for the uncertainty associated with the volume to mass conversion (Huss, 2013).…”

Section: B) Geodetic Mass Balancementioning

confidence: 99%

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Evaluation of the global glacier inventories and assessment of glacier elevation changes over north-western Himalaya

Abdullah¹,

Bhat²

2021

Preprint

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Abstract. The study evaluates the global glacier inventories available for the study area viz., RGI, GAMDAM and ICIMOD, with the newly generated Kashmir University Glacier Inventory (KUGI) for three Himalaya basins; Jhelum, Suru and Chenab in the north-western Himalaya, comprising of 2096 glaciers spread over an area of 3300 km2. The KUGI was prepared from the Landsat data supplemented by Digital Elevation Model, Google Earth images and limited field surveys. The KUGI comprises of 154 glaciers in the Jhelum, 328 in the Suru and 1614 in the Chenab basin, corresponding to the glacier area of 85.9 ± 11.4 km2, 487 ± 16.2 km2 and 2727 ± 90.2 km2 respectively. The investigation revealed that most of the glaciers in the study area are

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“…Though, the SRTM DEM was obtained over a shorter period of time (11-20 February, 2000) but the timestamp of each TANDEM-X acquisition is not same and is spread over a wider period. This has the potential to add to the uncertainty of glacier thickness and mass changes which has been considered in the uncertainty analysis in the present study 40 . The bias correction and uncertainty analysis is discussed in detail in the Supplementary Sections 3 and 4.…”

Section: Dem Corrections and Elevation Changesmentioning

confidence: 99%

The satellite observed glacier mass changes over the Upper Indus Basin during 2000–2012

Abdullah

Romshoo

Rashid

2020

Sci Rep

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Decadal glacier thickness changes over the Upper indus Basin in the Jammu and Kashmir Himalaya were estimated using the TanDEM-X and SRTM-C Digital Elevation Models (DEMs) from 2000 to 2012. In the study area 12,243 glaciers having 19,727 ± 1,054 km 2 area have thinned on an average of − 0.35 ± 0.33 m a −1 during the observation period. The highest thinning of − 1.69 ± 0.60 m a −1 was observed in the Pir Panjal while as the marginal thinning of − 0.11 ± 0.32 m a −1 was observed for the glaciers in the Karakoram. The observed glacier thickness changes indicated a strong influence of the topographic parameters. Higher thickness reduction was observed on the glaciers situated at lower altitudes (− 1.40 ± 0.53 m a −1) and with shallower slopes (− 1.52 ± 0.40 m a −1). Significantly higher negative thickness changes were observed from the glaciers situated on the southern slopes (− 0.55 ± 0.37 m a −1). The thickness loss was higher on the debris-covered glaciers (− 0.50 ± 0.38 m a −1) than on the clean glaciers (− 0.32 ± 0.33 m a −1). The cumulative glacier mass loss of − 70.32 ± 66.69 Gt was observed during the observation period, which, if continued, would significantly affect the sustainability of water resources in the basin. The recent reports on the enhanced glacier-melt in the Himalayan region 1 encompassing the Upper Indus Basin (UIB) and the consequent impacts on the water, food and energy security 2 stimulated various scientific studies to investigate the health and dynamics of glaciers in the UIB 3-5,7-16. However, most of the studies have focussed on the changes in the glacier area, snout recession, Equilibrium Line Altitude (ELA), impacts of the increasing temperatures, the influence of debris-cover 4,5. Glacier mass balance is the most important indicator of glacier health and is regarded as the direct and immediate glacier response to any changes in climate 6. However, glaciological mass balance, though considered more accurate method for glacier mass balance, is restricted to a few glaciers in the UIB owing to its rugged terrain, logistic challenges and security impediments 3. In view of these constraints, the geodetic mass balance has emerged as a credible alternate approach to assess glacier mass balance changes at local and regional scales in the UIB 7-15. The past studies have reported significant variability in glacier mass changes over the High Mountain Asia (HMA) region. Gardelle et al. 15 for instance, provided comprehensive regional mass balance estimates over the Hindu-Kush Karakoram Himalaya (HKH) region between 2000 and 2011, and highlighted the higher mass wastage in the western Himalaya, moderate mass loss in the eastern and central Himalaya, small mass losses in the Hindu-Kush and stability or even slight mass gain in the Karakoram and Pamir sub-regions. The variability in the mass balance of glaciers in various Hindu-Kush Himalayan regions has been largely attributed to the peculiar topographic and climatic setting of each of the mountain ranges 16. However, it has been observed that the...

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Elevation Changes of West-Central Greenland Glaciers From 1985 to 2012 From Remote Sensing

Cited by 22 publications

References 31 publications

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

Evaluation of the global glacier inventories and assessment of glacier elevation changes over north-western Himalaya

The satellite observed glacier mass changes over the Upper Indus Basin during 2000–2012

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