Improving estimation of glacier volume change: a GLIMS case study of Bering Glacier System, Alaska

Beedle, M. J.; Dyurgerov, Mark B.; Tangborn, Wendell V.; Khalsa, Siri Jodha Singh; Helm, Christopher; Raup, B. H.; Armstrong, R. L.; Barry, Roger G.

doi:10.5194/tc-2-33-2008

Cited by 25 publications

(13 citation statements)

References 25 publications

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“…On the drier eastern side, Llewellyn Glacier is the second largest glacier of the icefield (450 km 2 , 37.5 km long) and is one of the largest glaciers in British Columbia. Llewellyn Glacier has been receding rapidly, especially in the past two decades, and has lost the most area of all the outlet glaciers in the icefield (Beedle and Raup, 2008). Pelto (2017) shows that all major outlet glaciers, other than Taku, have experienced terminus recession during the period 1984-2013.…”

Section: Study Sitementioning

confidence: 99%

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

et al. 2018

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Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate products are too coarse to accurately capture orographic effects. Here we use the linear theory of orographic precipitation model (LT model) to downscale winter precipitation from the Weather Research and Forecasting Model (WRF) over the Juneau Icefield, one of the largest ice masses in North America (>4,000 km 2 ), for the period 1979-2013. The LT model is physically-based yet computationally efficient, combining airflow dynamics and simple cloud microphysics. The resulting 1 km resolution precipitation fields show substantially reduced precipitation on the northeastern portion of the icefield compared to the southwestern side, a pattern that is not well captured in the coarse resolution (20 km) WRF data. Net snow accumulation derived from the LT model precipitation agrees well with point observations across the icefield. To investigate the robustness of the LT model results, we perform a series of sensitivity experiments varying hydrometeor fall speeds, the horizontal resolution of the underlying grid, and the source of the meteorological forcing data. The resulting normalized spatial precipitation pattern is similar for all sensitivity experiments, but local precipitation amounts vary strongly, with greatest sensitivity to variations in snow fall speed. Results indicate that the LT model has great potential to provide improved spatial patterns of winter precipitation for glacier mass balance modeling purposes in complex terrain, but ground observations are necessary to constrain model parameters to match total amounts.

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Section: Study Sitementioning

confidence: 99%

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

et al. 2018

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“…The Bering Glacier, located in southeastern Alaska, is the largest glacier in North America by surface area at 3630 km 2 [ Beedle et al , 2008]. It terminates within Vitus Lake, and is subject to significant mass loss at its terminus due to calving.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of seismic and acoustic signals produced by calving, Bering Glacier, Alaska

Richardson

Waite

FitzGerald

et al. 2010

Geophysical Research Letters

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[1] We recorded 126 calving and iceberg breakup events from the terminus of the Bering Glacier during five days in August 2008 using seismometers and three smallaperture arrays of infrasound sensors. The seismic signals were typically emergent, narrow-band, and lower-frequency, similar to records at other glaciers. The acoustic records were characterized by shorter-duration, higher-frequency signals with more impulsive onsets. We demonstrate that triangular infrasound arrays permit improved locations of calving events over seismic arrivals that rely on a relatively complicated, poorly known, velocity model. Twenty-six of 35 well-located events occurred on icebergs in Vitus Lake, rather than the glacier face. While our data do not permit a complete description of the source process, the distinctive frequency contents and durations in the seismic and infrasound data suggest that the two data types record different aspects of the same process. Citation: Richardson,

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“…The elevation change and volume loss of Bering Glacier have been estimated by different authors using remote-sensing techniques (Arendt et al, 2002;Beedle et al, 2008;Muskett et al, 2009;Berthier et al, 2010;Berthier, 2010). For the period 1972-2003, using the 1972 USGS map as a reference and a glacier area of 4400 km 2 , the geodetic method (ASTER DEM), volume loss for the entire Bering Glacier system equaled 2.6 ± 0.5 km 3 w.e.…”

Section: Validationmentioning

confidence: 99%

“…Transporting large volumes of ice to a lower and warmer elevation over a short time period (several months) increases the ablation rate and alters the mass balance and runoff of a glacier. Observed surges occurred in 1958-1960, 1966-1967, 1981, 1993and 2008-2011(Molnia and Post, 2010). An increase in runoff caused by increased ablation during these periods would therefore be expected if there is a large transport of ice to lower elevations during a surge.…”

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“…There are 49 intervals spaced at 30.48 m (100 feet) with a total area of 2193 km 2 . The total area defined by Beedle et al (2008) of the Bering Glacier System (BGS) is 4373 km 2 or exactly twice the area (within a few km 2 ) of the area in GS, (Beedle et al, 2008). The Bering Glacier System outline includes all ice within the US Board on Geographic Names definition of BGS and excludes nunataks and areas of debris cover).…”

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Mass balance, runoff and surges of Bering Glacier, Alaska

Tangborn

2013

The Cryosphere

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Abstract. The historical net, ablation and accumulation daily balances, as well as runoff of Bering Glacier, Alaska are determined for the 1951-2011 period with the PTAA (precipitation-temperature-area-altitude) model, using daily precipitation and temperature observations collected at the Cordova and Yakutat weather stations, together with the areaaltitude distribution of the glacier. The model mean annual balance for this 61 yr period is −0.6 m w.e., the accumulation balance is +1.4 and the ablation balance is −2.0 m w.e. Average annual runoff is 2.5 m w.e. Periodic surges of this glacier transport large volumes of ice to lower elevations where the ablation rate is higher, producing more negative balances and increasing runoff. Runoff from Bering Glacier (derived from simulated ablation and precipitation as rain) is highly correlated with four of the glacier surges that have occurred since 1951. Ice volume loss for the 1972-2003 period measured with the PTAA model is 2.7 km 3 w.e. a −1 and closely agrees with losses for the same period measured with the geodetic method. It is proposed that the timing and magnitude of daily snow accumulation and runoff, both of which are controlled by the glacier's area-altitude distribution and are calculated with the PTAA model, can be used to determine the probability that a glacier will surge.

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Improving estimation of glacier volume change: a GLIMS case study of Bering Glacier System, Alaska

Cited by 25 publications

References 25 publications

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

Characteristics of seismic and acoustic signals produced by calving, Bering Glacier, Alaska

Mass balance, runoff and surges of Bering Glacier, Alaska

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