Sampling and statistical analyses of BTS measurements

Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200m, 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...

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Bibliographic Details
Main Authors: Er Brenning, Stephan Gruber, Martin Hoelzle
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2005
Subjects:
permafrost
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.9076
http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.546.9076 2023-05-15T17:57:18+02:00 Sampling and statistical analyses of BTS measurements Er Brenning Stephan Gruber Martin Hoelzle The Pennsylvania State University CiteSeerX Archives 2005 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.9076 http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.9076 http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf text 2005 ftciteseerx 2016-01-08T11:19:58Z Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200m, 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 measure-ment program appears critical in order to minimize problems typical of observational data in complex Text permafrost Unknown
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description Basal temperature of snow (BTS) data show characteristic spatial autocorrelations at distances typically less than 200m, 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 measure-ment program appears critical in order to minimize problems typical of observational data in complex
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Er Brenning
Stephan Gruber
Martin Hoelzle
spellingShingle Er Brenning
Stephan Gruber
Martin Hoelzle
Sampling and statistical analyses of BTS measurements
author_facet Er Brenning
Stephan Gruber
Martin Hoelzle
author_sort Er Brenning
title Sampling and statistical analyses of BTS measurements
title_short 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_sort sampling and statistical analyses of bts measurements
publishDate 2005
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.9076
http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf
genre permafrost
genre_facet permafrost
op_source http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.9076
http://www.geo.unizh.ch/~hoelzle/brenningetal2005.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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