Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows
Melt rate models are fundamental for understanding the impacts of climate change on glaciers and the subsequent effects on habitats and sea level rise. Ice melt models have mostly been derived from energy balance or air temperature index calculations. This research demonstrates that satellite-derive...
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ftunivwaikato:oai:researchcommons.waikato.ac.nz:10289/13762 2023-12-17T10:20:31+01:00 Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows Brabyn, Lars Stichbury, Glen 2020 application/pdf https://hdl.handle.net/10289/13762 https://doi.org/10.1007/s10661-020-08396-x en eng Springer Nature Environmental monitoring and assessment Brabyn, L., & Stichbury, G. (2020). Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows. Environmental Monitoring and Assessment, 192(7). https://doi.org/10.1007/s10661-020-08396-x 0167-6369 https://hdl.handle.net/10289/13762 doi:10.1007/s10661-020-08396-x 1573-2959 This is a post-peer-review, pre-copyedit version of an article published in Environmental Monitoring and Assessment. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10661-020-08396-x © 2020 Springer Nature Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Antarctic glaciers Landsat Land surface temperature Melt rate MODIS Taylor Valley Energy balance Meltwater Climate Journal Article 2020 ftunivwaikato https://doi.org/10.1007/s10661-020-08396-x 2023-11-21T18:25:45Z Melt rate models are fundamental for understanding the impacts of climate change on glaciers and the subsequent effects on habitats and sea level rise. Ice melt models have mostly been derived from energy balance or air temperature index calculations. This research demonstrates that satellite-derived land surface temperature (LST) measurements provide a simpler method for estimating surface melt rate that substitutes for energy balance models. Since these satellite images are continuous (distributed) across space, they do not need calibration for topography. Antarctic glacier melt discharge data from nearby stream gauges were used to calibrate an LST-derived melt model. The model calculations are simplified by the fact that groundwater flow is assumed to be minimal due to permafrost, and the glaciers are assumed to only melt on the surface. A new method called the Temperature Area Sum model is developed, which builds on an existing Temperature Area Index model. A daily melt rate model is developed using 77 Landsat 8 images and calculates the volume of meltwater produced per hectare for any given LST between − 7 and 0 °C. A seasonal average daily melt rate model is also developed that uses 1660 MODIS images. The utility of the seasonal MODIS model is demonstrated by calculating melt rates, water flows and wetness across the entire Ross Sea Region. An unexpected large wet area to the southwest of the Ross Ice Shelf requires further investigation and demonstrates the usefulness of these models for large remote areas. Surface melt rate and wetness can now be calculated for different climate change scenarios. Article in Journal/Newspaper Antarc* Antarctic Ice Ice Shelf permafrost Ross Ice Shelf Ross Sea The University of Waikato: Research Commons Antarctic Ross Sea Ross Ice Shelf Taylor Valley ENVELOPE(163.000,163.000,-77.617,-77.617) Environmental Monitoring and Assessment 192 7 |
institution |
Open Polar |
collection |
The University of Waikato: Research Commons |
op_collection_id |
ftunivwaikato |
language |
English |
topic |
Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Antarctic glaciers Landsat Land surface temperature Melt rate MODIS Taylor Valley Energy balance Meltwater Climate |
spellingShingle |
Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Antarctic glaciers Landsat Land surface temperature Melt rate MODIS Taylor Valley Energy balance Meltwater Climate Brabyn, Lars Stichbury, Glen Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
topic_facet |
Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Antarctic glaciers Landsat Land surface temperature Melt rate MODIS Taylor Valley Energy balance Meltwater Climate |
description |
Melt rate models are fundamental for understanding the impacts of climate change on glaciers and the subsequent effects on habitats and sea level rise. Ice melt models have mostly been derived from energy balance or air temperature index calculations. This research demonstrates that satellite-derived land surface temperature (LST) measurements provide a simpler method for estimating surface melt rate that substitutes for energy balance models. Since these satellite images are continuous (distributed) across space, they do not need calibration for topography. Antarctic glacier melt discharge data from nearby stream gauges were used to calibrate an LST-derived melt model. The model calculations are simplified by the fact that groundwater flow is assumed to be minimal due to permafrost, and the glaciers are assumed to only melt on the surface. A new method called the Temperature Area Sum model is developed, which builds on an existing Temperature Area Index model. A daily melt rate model is developed using 77 Landsat 8 images and calculates the volume of meltwater produced per hectare for any given LST between − 7 and 0 °C. A seasonal average daily melt rate model is also developed that uses 1660 MODIS images. The utility of the seasonal MODIS model is demonstrated by calculating melt rates, water flows and wetness across the entire Ross Sea Region. An unexpected large wet area to the southwest of the Ross Ice Shelf requires further investigation and demonstrates the usefulness of these models for large remote areas. Surface melt rate and wetness can now be calculated for different climate change scenarios. |
format |
Article in Journal/Newspaper |
author |
Brabyn, Lars Stichbury, Glen |
author_facet |
Brabyn, Lars Stichbury, Glen |
author_sort |
Brabyn, Lars |
title |
Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
title_short |
Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
title_full |
Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
title_fullStr |
Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
title_full_unstemmed |
Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows |
title_sort |
calculating the surface melt rate of antarctic glaciers using satellite-derived temperatures and stream flows |
publisher |
Springer Nature |
publishDate |
2020 |
url |
https://hdl.handle.net/10289/13762 https://doi.org/10.1007/s10661-020-08396-x |
long_lat |
ENVELOPE(163.000,163.000,-77.617,-77.617) |
geographic |
Antarctic Ross Sea Ross Ice Shelf Taylor Valley |
geographic_facet |
Antarctic Ross Sea Ross Ice Shelf Taylor Valley |
genre |
Antarc* Antarctic Ice Ice Shelf permafrost Ross Ice Shelf Ross Sea |
genre_facet |
Antarc* Antarctic Ice Ice Shelf permafrost Ross Ice Shelf Ross Sea |
op_relation |
Environmental monitoring and assessment Brabyn, L., & Stichbury, G. (2020). Calculating the surface melt rate of Antarctic glaciers using satellite-derived temperatures and stream flows. Environmental Monitoring and Assessment, 192(7). https://doi.org/10.1007/s10661-020-08396-x 0167-6369 https://hdl.handle.net/10289/13762 doi:10.1007/s10661-020-08396-x 1573-2959 |
op_rights |
This is a post-peer-review, pre-copyedit version of an article published in Environmental Monitoring and Assessment. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10661-020-08396-x © 2020 Springer Nature |
op_doi |
https://doi.org/10.1007/s10661-020-08396-x |
container_title |
Environmental Monitoring and Assessment |
container_volume |
192 |
container_issue |
7 |
_version_ |
1785522980968726528 |