Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain
Measurements of environmental variables are often used to validate and calibrate physically-based models. Depending on their application, the models are used at different scales, ranging from few meters to tens of kilometers. Environmental variables can vary strongly within the grid cells of these m...
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ftcopernicus:oai:publications.copernicus.org:tc10057 2023-05-15T17:58:05+02:00 Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain Gubler, S. Fiddes, J. Keller, M. Gruber, S. 2018-09-27 application/pdf https://doi.org/10.5194/tc-5-431-2011 https://tc.copernicus.org/articles/5/431/2011/ eng eng doi:10.5194/tc-5-431-2011 https://tc.copernicus.org/articles/5/431/2011/ eISSN: 1994-0424 Text 2018 ftcopernicus https://doi.org/10.5194/tc-5-431-2011 2020-07-20T16:26:08Z Measurements of environmental variables are often used to validate and calibrate physically-based models. Depending on their application, the models are used at different scales, ranging from few meters to tens of kilometers. Environmental variables can vary strongly within the grid cells of these models. Validating a model with a single measurement is therefore delicate and susceptible to induce bias in further model applications. To address the question of uncertainty associated with scale in permafrost models, we present data of 390 spatially-distributed ground surface temperature measurements recorded in terrain of high topographic variability in the Swiss Alps. We illustrate a way to program, deploy and refind a large number of measurement devices efficiently, and present a strategy to reduce data loss reported in earlier studies. Data after the first year of deployment is presented. The measurements represent the variability of ground surface temperatures at two different scales ranging from few meters to some kilometers. On the coarser scale, the dependence of mean annual ground surface temperature on elevation, slope, aspect and ground cover type is modelled with a multiple linear regression model. Sampled mean annual ground surface temperatures vary from −4 °C to 5 °C within an area of approximately 16 km 2 subject to elevational differences of approximately 1000 m. The measurements also indicate that mean annual ground surface temperatures vary up to 6 °C (i.e., from −2 °C to 4 °C) even within an elevational band of 300 m. Furthermore, fine-scale variations can be high (up to 2.5 °C) at distances of less than 14 m in homogeneous terrain. The effect of this high variability of an environmental variable on model validation and applications in alpine regions is discussed. Text permafrost Copernicus Publications: E-Journals The Cryosphere 5 2 431 443 |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
language |
English |
description |
Measurements of environmental variables are often used to validate and calibrate physically-based models. Depending on their application, the models are used at different scales, ranging from few meters to tens of kilometers. Environmental variables can vary strongly within the grid cells of these models. Validating a model with a single measurement is therefore delicate and susceptible to induce bias in further model applications. To address the question of uncertainty associated with scale in permafrost models, we present data of 390 spatially-distributed ground surface temperature measurements recorded in terrain of high topographic variability in the Swiss Alps. We illustrate a way to program, deploy and refind a large number of measurement devices efficiently, and present a strategy to reduce data loss reported in earlier studies. Data after the first year of deployment is presented. The measurements represent the variability of ground surface temperatures at two different scales ranging from few meters to some kilometers. On the coarser scale, the dependence of mean annual ground surface temperature on elevation, slope, aspect and ground cover type is modelled with a multiple linear regression model. Sampled mean annual ground surface temperatures vary from −4 °C to 5 °C within an area of approximately 16 km 2 subject to elevational differences of approximately 1000 m. The measurements also indicate that mean annual ground surface temperatures vary up to 6 °C (i.e., from −2 °C to 4 °C) even within an elevational band of 300 m. Furthermore, fine-scale variations can be high (up to 2.5 °C) at distances of less than 14 m in homogeneous terrain. The effect of this high variability of an environmental variable on model validation and applications in alpine regions is discussed. |
format |
Text |
author |
Gubler, S. Fiddes, J. Keller, M. Gruber, S. |
spellingShingle |
Gubler, S. Fiddes, J. Keller, M. Gruber, S. Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
author_facet |
Gubler, S. Fiddes, J. Keller, M. Gruber, S. |
author_sort |
Gubler, S. |
title |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
title_short |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
title_full |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
title_fullStr |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
title_full_unstemmed |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
title_sort |
scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-5-431-2011 https://tc.copernicus.org/articles/5/431/2011/ |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-5-431-2011 https://tc.copernicus.org/articles/5/431/2011/ |
op_doi |
https://doi.org/10.5194/tc-5-431-2011 |
container_title |
The Cryosphere |
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5 |
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2 |
container_start_page |
431 |
op_container_end_page |
443 |
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1766166627736354816 |