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Surface mass balance of Arctic glaci...

Gardner, Alex Sandy.

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Surface mass balance of Arctic glaciers: Climate influences and modeling approaches.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Surface mass balance of Arctic glaciers: Climate influences and modeling approaches./
Author:	Gardner, Alex Sandy.
Description:	195 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: 7304.
Contained By:	Dissertation Abstracts International71-12B.
Subject:	Climate Change. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR62916
ISBN:	9780494629161

Surface mass balance of Arctic glaciers: Climate influences and modeling approaches.
Gardner, Alex Sandy.

Surface mass balance of Arctic glaciers: Climate influences and modeling approaches. - 195 p.

Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: 7304.

Thesis (Ph.D.)--University of Alberta (Canada), 2010.

Land ice is losing mass to the world's oceans at an accelerated rate. The world's glaciers contain much less ice than the ice sheets but contribute equally to eustatic sea level rise and are expected to continue to do so over the coming centuries if global temperatures continue to rise. It is therefore important to characterize the mass balance of these glaciers and its relationship to climate trends and variability. In the Canadian High Arctic, analysis of long-term surface mass balance records shows a shift to more negative mass balances after 1987 and is coincident with a change in the mean location of the July circumpolar vortex, a mid-troposphere cyclonic feature known to have a strong influence on Arctic summer climate. Since 1987 the occurrence of July vortices centered in the Eastern Hemisphere have increased significantly. This change is associated with an increased frequency of tropospheric ridging over the Canadian High Arctic, higher surface air temperatures, and more negative glacier mass balance. However, regional scale mass balance modeling is needed to determine whether or not the long-term mass balance measurements in this region accurately reflect the mass balance of the entire Canadian High Arctic.

ISBN: 9780494629161Subjects--Topical Terms:

894284
Climate Change.

Surface mass balance of Arctic glaciers: Climate influences and modeling approaches.
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245 1 0 $a Surface mass balance of Arctic glaciers: Climate influences and modeling approaches.
300 $a 195 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-12, Section: B, page: 7304.
502 $a Thesis (Ph.D.)--University of Alberta (Canada), 2010.
520 $a Land ice is losing mass to the world's oceans at an accelerated rate. The world's glaciers contain much less ice than the ice sheets but contribute equally to eustatic sea level rise and are expected to continue to do so over the coming centuries if global temperatures continue to rise. It is therefore important to characterize the mass balance of these glaciers and its relationship to climate trends and variability. In the Canadian High Arctic, analysis of long-term surface mass balance records shows a shift to more negative mass balances after 1987 and is coincident with a change in the mean location of the July circumpolar vortex, a mid-troposphere cyclonic feature known to have a strong influence on Arctic summer climate. Since 1987 the occurrence of July vortices centered in the Eastern Hemisphere have increased significantly. This change is associated with an increased frequency of tropospheric ridging over the Canadian High Arctic, higher surface air temperatures, and more negative glacier mass balance. However, regional scale mass balance modeling is needed to determine whether or not the long-term mass balance measurements in this region accurately reflect the mass balance of the entire Canadian High Arctic.
520 $a The Canadian High Arctic is characterized by high relief and complex terrain that result in steep horizontal gradients in surface mass balance, which can only be resolved if models are run at high spatial resolutions. For such runs, models often require input fields such as air temperature that are derived by downscaling of output from climate models or reanalyses. Downscaling is often performed using a specified relationship between temperature and elevation (a lapse rate). Although a constant lapse rate is often assumed, this is not well justified by observations. To improve upon this assumption, near-surface temperature lapse rates during the summer ablation season were derived from surface measurements on 4 Arctic glaciers. Near-surface lapse rates vary systematically with free-air temperatures and are less steep than the free-air lapse rates that have often been used in mass balance modeling. Available observations were used to derive a new variable temperature downscaling method based on temperature dependent daily lapse rates. This method was implemented in a temperature index mass balance model, and results were compared with those derived from a constant linear lapse rate. Compared with other approaches, model estimates of surface mass balance fit observations much better when variable, temperature dependent lapse rates are used. To better account for glacier-climate feedbacks within mass balance models, more physically explicit representations of snow and ice processes must be used. Since absorption of shortwave radiation is often the single largest source of energy for melt, one of the most important parameters to model correctly is surface albedo. To move beyond the limitations of empirical snow and ice albedo parameterizations often used in surface mass balance models, a computationally simple, theoretically-based parameterization for snow and ice albedo was developed. Unlike previous parameterizations, it provides a single set of equations for the estimation of both snow and ice albedo. The parameterization also produces accurate results for a much wider range of snow, ice, and atmospheric conditions.
590 $a School code: 0351.
650 4 $a Climate Change. $3 894284
650 4 $a Geomorphology. $3 542703
650 4 $a Atmospheric Sciences. $3 1019179
650 4 $a Remote Sensing. $3 1018559
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