C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B)
Perennial snowfields, such as those found in the Brooks Range in Alaska, are critical to alpine and arctic ecosystems, as they influence downslope hydrology, vegetation, geology, and serve as habitat for an array of wildlife, including caribou. Caribou are a crucial food and cultural resource for Al...
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2023
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Online Access: | http://dx.doi.org/10.22541/essoar.167591078.86003631/v1 |
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crwinnower:10.22541/essoar.167591078.86003631/v1 2024-06-02T08:02:04+00:00 C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) Tedesche, Molly E Fassnacht, Steven R Trochim, Erin D Wolken, Gabriel J 2023 http://dx.doi.org/10.22541/essoar.167591078.86003631/v1 unknown Authorea, Inc. posted-content 2023 crwinnower https://doi.org/10.22541/essoar.167591078.86003631/v1 2024-05-07T14:19:27Z Perennial snowfields, such as those found in the Brooks Range in Alaska, are critical to alpine and arctic ecosystems, as they influence downslope hydrology, vegetation, geology, and serve as habitat for an array of wildlife, including caribou. Caribou are a crucial food and cultural resource for Alaska Native subsistence hunters. To understand extent changes and persistence of perennial snowfields, we developed a spatially distributed perennial snowfield melt model using the temperature melt index method, paired with multivariate binary logistic regression. Input data for calibration and evaluation of the model are a synthesis of climate reanalysis data and satellite imagery from both multi-spectral (optical) data and synthetic aperture radar (SAR). Temporal and spatial scale variations among input datasets, as well as variations in distribution and extents of the snowfields themselves, were accounted for using several methods. Snowfield metrics derived from remote sensing data were evaluated by comparison with field collected data. Probabilities of perennial snowfield melt at several thresholds were modeled using terrain-adjusted gridded temperature and net solar radiation data with a digital elevation model (DEM). Conditions of snowfield disappearance or persistence, from one melt season to the next, were derived from Sentinel-2 optical imagery. Pixel wise melt-onset and freeze-up dates were determined using a Sentinel-1 SAR backscatter intensity differencing approach. The model was calibrated in a focused study domain within the Brooks Range and evaluated in an alternate location around the Alaska Native village of Anaktuvuk Pass. Results of the perennial snowfield melt model indicate best performance at probability thresholds from 50% to 70%. Local community members from the village of Anaktuvuk Pass were involved in field work decision making processes, as well as with data collection. The application of this model will be for quantifying one of many potential contributing factors to changes in arctic ... Other/Unknown Material Arctic Brooks Range Alaska The Winnower Arctic |
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Open Polar |
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The Winnower |
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crwinnower |
language |
unknown |
description |
Perennial snowfields, such as those found in the Brooks Range in Alaska, are critical to alpine and arctic ecosystems, as they influence downslope hydrology, vegetation, geology, and serve as habitat for an array of wildlife, including caribou. Caribou are a crucial food and cultural resource for Alaska Native subsistence hunters. To understand extent changes and persistence of perennial snowfields, we developed a spatially distributed perennial snowfield melt model using the temperature melt index method, paired with multivariate binary logistic regression. Input data for calibration and evaluation of the model are a synthesis of climate reanalysis data and satellite imagery from both multi-spectral (optical) data and synthetic aperture radar (SAR). Temporal and spatial scale variations among input datasets, as well as variations in distribution and extents of the snowfields themselves, were accounted for using several methods. Snowfield metrics derived from remote sensing data were evaluated by comparison with field collected data. Probabilities of perennial snowfield melt at several thresholds were modeled using terrain-adjusted gridded temperature and net solar radiation data with a digital elevation model (DEM). Conditions of snowfield disappearance or persistence, from one melt season to the next, were derived from Sentinel-2 optical imagery. Pixel wise melt-onset and freeze-up dates were determined using a Sentinel-1 SAR backscatter intensity differencing approach. The model was calibrated in a focused study domain within the Brooks Range and evaluated in an alternate location around the Alaska Native village of Anaktuvuk Pass. Results of the perennial snowfield melt model indicate best performance at probability thresholds from 50% to 70%. Local community members from the village of Anaktuvuk Pass were involved in field work decision making processes, as well as with data collection. The application of this model will be for quantifying one of many potential contributing factors to changes in arctic ... |
format |
Other/Unknown Material |
author |
Tedesche, Molly E Fassnacht, Steven R Trochim, Erin D Wolken, Gabriel J |
spellingShingle |
Tedesche, Molly E Fassnacht, Steven R Trochim, Erin D Wolken, Gabriel J C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
author_facet |
Tedesche, Molly E Fassnacht, Steven R Trochim, Erin D Wolken, Gabriel J |
author_sort |
Tedesche, Molly E |
title |
C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
title_short |
C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
title_full |
C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
title_fullStr |
C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
title_full_unstemmed |
C32B-03: A Perennial Snowfield Melt Model as a Synthesis of Climate, Field, and Remotely Sensed Data from the Brooks Range, Alaska (AGU 2022, Oral Session C32B) |
title_sort |
c32b-03: a perennial snowfield melt model as a synthesis of climate, field, and remotely sensed data from the brooks range, alaska (agu 2022, oral session c32b) |
publisher |
Authorea, Inc. |
publishDate |
2023 |
url |
http://dx.doi.org/10.22541/essoar.167591078.86003631/v1 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Brooks Range Alaska |
genre_facet |
Arctic Brooks Range Alaska |
op_doi |
https://doi.org/10.22541/essoar.167591078.86003631/v1 |
_version_ |
1800746571147509760 |