Sampling and statistical analyses of BTS measurements

Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200 m, leading to non-independent regression residuals. Systematic temporal variations may also introduce model bias resulting in a shift in the predicted lower limit of permafrost. Bot...

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Published in:Permafrost and Periglacial Processes
Main Authors: Brenning, A. (Alexander), Gruber, S. (Stephan), Hoelzle, M. (Martin)
Format: Article in Journal/Newspaper
Language:English
Published: 2005
Subjects:
Online Access:https://ir.library.carleton.ca/pub/19153
https://doi.org/10.1002/ppp.541
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author Brenning, A. (Alexander)
Gruber, S. (Stephan)
Hoelzle, M. (Martin)
author_facet Brenning, A. (Alexander)
Gruber, S. (Stephan)
Hoelzle, M. (Martin)
author_sort Brenning, A. (Alexander)
collection Carleton University's Institutional Repository
container_issue 4
container_start_page 383
container_title Permafrost and Periglacial Processes
container_volume 16
description Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200 m, leading to non-independent regression residuals. Systematic temporal variations may also introduce model bias resulting in a shift in the predicted lower limit of permafrost. Both phenomena are analysed. The selection of an appropriate sampling design for a BTS measurement program appears critical in order to minimize problems typical of observational data in complex terrain. Copyright
format Article in Journal/Newspaper
genre permafrost
Permafrost and Periglacial Processes
genre_facet permafrost
Permafrost and Periglacial Processes
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institution Open Polar
language English
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op_container_end_page 393
op_doi https://doi.org/10.1002/ppp.541
op_relation https://ir.library.carleton.ca/pub/19153
doi:10.1002/ppp.541
op_rights info:eu-repo/semantics/openAccess
op_source Permafrost and Periglacial Processes vol. 16 no. 4, pp. 383-393
publishDate 2005
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spelling ftcarletonunivir:oai:carleton.ca:19153 2025-01-17T00:14:46+00:00 Sampling and statistical analyses of BTS measurements Brenning, A. (Alexander) Gruber, S. (Stephan) Hoelzle, M. (Martin) 2005-10-01 https://ir.library.carleton.ca/pub/19153 https://doi.org/10.1002/ppp.541 en eng https://ir.library.carleton.ca/pub/19153 doi:10.1002/ppp.541 info:eu-repo/semantics/openAccess Permafrost and Periglacial Processes vol. 16 no. 4, pp. 383-393 BTS Mountain permafrost Sampling design Spatiotemporal variability Statistical analysis info:eu-repo/semantics/article 2005 ftcarletonunivir https://doi.org/10.1002/ppp.541 2022-02-06T21:52:02Z Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200 m, leading to non-independent regression residuals. Systematic temporal variations may also introduce model bias resulting in a shift in the predicted lower limit of permafrost. Both phenomena are analysed. The selection of an appropriate sampling design for a BTS measurement program appears critical in order to minimize problems typical of observational data in complex terrain. Copyright Article in Journal/Newspaper permafrost Permafrost and Periglacial Processes Carleton University's Institutional Repository Permafrost and Periglacial Processes 16 4 383 393
spellingShingle BTS
Mountain permafrost
Sampling design
Spatiotemporal variability
Statistical analysis
Brenning, A. (Alexander)
Gruber, S. (Stephan)
Hoelzle, M. (Martin)
Sampling and statistical analyses of BTS measurements
title Sampling and statistical analyses of BTS measurements
title_full Sampling and statistical analyses of BTS measurements
title_fullStr Sampling and statistical analyses of BTS measurements
title_full_unstemmed Sampling and statistical analyses of BTS measurements
title_short Sampling and statistical analyses of BTS measurements
title_sort sampling and statistical analyses of bts measurements
topic BTS
Mountain permafrost
Sampling design
Spatiotemporal variability
Statistical analysis
topic_facet BTS
Mountain permafrost
Sampling design
Spatiotemporal variability
Statistical analysis
url https://ir.library.carleton.ca/pub/19153
https://doi.org/10.1002/ppp.541