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Snow Distribution and Influence in T...

Mcnulty, Katherine,

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Snow Distribution and Influence in Taylor Valley, Antarctica, Using Remote Sensing /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Snow Distribution and Influence in Taylor Valley, Antarctica, Using Remote Sensing // Katherine Mcnulty.
Author:	Mcnulty, Katherine,
Description:	1 electronic resource (65 pages)
Notes:	Source: Masters Abstracts International, Volume: 85-03.
Contained By:	Masters Abstracts International85-03.
Subject:	Permafrost. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30556488
ISBN:	9798380259569

Snow Distribution and Influence in Taylor Valley, Antarctica, Using Remote Sensing /
Mcnulty, Katherine,

Snow Distribution and Influence in Taylor Valley, Antarctica, Using Remote Sensing /Katherine Mcnulty. - 1 electronic resource (65 pages)

Source: Masters Abstracts International, Volume: 85-03.

The McMurdo Dry Valleys is the largest ice-free area in Antarctica, but seasonal snow covers the valley floors sporadically throughout the year. In this study, a model to estimate areal snow coverage from satellite imagery was created. An area-volume model was created to estimate the amount of snow water equivalent (SWE) from the snow area extracted from the imagery. Snow cover influences the total albedo, the hydrologic budget, and the soil moisture and soil temperature in Taylor Valley (TV). Quantifying snow precipitation in TV is challenging because snow redistributes with winds, sublimates, or melts within a short period. Previous estimates found the amount of snow precipitation in TV is small, less than 100 mm/a. (SWE); even so, snow cover may influence processes in the valley. To better understand the controls and feedbacks of snow cover in the valley, a long-term record of spatially distributed abundance is required. This research creates a long-term record of snow cover data in TV using satellite images. The area of snowpacks was calculated by creating a classification scheme based on the brightness of panchromatic images. During the 2021-2022 field season, 250 m x 250 m sampling quadrats were surveyed to approximate how area and volume relate to SWE. Volumetric SWE was calculated by measuring in situ the length, width, depth, and density of each snowpack in the quadrat. There is a strong relationship between the area and the volume of the snowpacks (R2=0.942, P=0.182). With this information, estimates of the SWE can be made from the area calculated from satellite imagery. The average snow area for the entire extent of TV in late winter/early summer (September-December) from 2004 to 2022 is 65.26 km2 , the average SWE is 0.0310 km3, and the average SWE depth is 75.72 mm. The amount of areal snow coverage is important when calculating the energy balance of TV, as well as understanding the availability of soil moisture to the soil ecosystem year-to-year. The available SWE can also influence seasonal surface and subsurface hydrology. While most precipitated snow in TV will sublimate or be redistributed by the wind, it is important to quantify how much snow has accumulated each season, especially with a warming climate, which could drastically influence snow accumulation and dynamics in TV.

English

ISBN: 9798380259569Subjects--Topical Terms:

1001005
Permafrost.

Snow Distribution and Influence in Taylor Valley, Antarctica, Using Remote Sensing /
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520 $a The McMurdo Dry Valleys is the largest ice-free area in Antarctica, but seasonal snow covers the valley floors sporadically throughout the year. In this study, a model to estimate areal snow coverage from satellite imagery was created. An area-volume model was created to estimate the amount of snow water equivalent (SWE) from the snow area extracted from the imagery. Snow cover influences the total albedo, the hydrologic budget, and the soil moisture and soil temperature in Taylor Valley (TV). Quantifying snow precipitation in TV is challenging because snow redistributes with winds, sublimates, or melts within a short period. Previous estimates found the amount of snow precipitation in TV is small, less than 100 mm/a. (SWE); even so, snow cover may influence processes in the valley. To better understand the controls and feedbacks of snow cover in the valley, a long-term record of spatially distributed abundance is required. This research creates a long-term record of snow cover data in TV using satellite images. The area of snowpacks was calculated by creating a classification scheme based on the brightness of panchromatic images. During the 2021-2022 field season, 250 m x 250 m sampling quadrats were surveyed to approximate how area and volume relate to SWE. Volumetric SWE was calculated by measuring in situ the length, width, depth, and density of each snowpack in the quadrat. There is a strong relationship between the area and the volume of the snowpacks (R2=0.942, P=0.182). With this information, estimates of the SWE can be made from the area calculated from satellite imagery. The average snow area for the entire extent of TV in late winter/early summer (September-December) from 2004 to 2022 is 65.26 km2 , the average SWE is 0.0310 km3, and the average SWE depth is 75.72 mm. The amount of areal snow coverage is important when calculating the energy balance of TV, as well as understanding the availability of soil moisture to the soil ecosystem year-to-year. The available SWE can also influence seasonal surface and subsurface hydrology. While most precipitated snow in TV will sublimate or be redistributed by the wind, it is important to quantify how much snow has accumulated each season, especially with a warming climate, which could drastically influence snow accumulation and dynamics in TV.
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