Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 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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Main Authors: Er Brenning, Stephan Gruber, Martin Hoelzle
Other Authors: The Pennsylvania State University CiteSeerX Archives
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Language:English
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.494.5174
http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.494.5174 2023-05-15T17:57:23+02:00 Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements Er Brenning Stephan Gruber Martin Hoelzle The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.494.5174 http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.494.5174 http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf text ftciteseerx 2016-01-08T08:41:52Z 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 measure-ment program appears critical in order to minimize problems typical of observational data in complex Text permafrost Unknown
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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 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
Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
author_facet Er Brenning
Stephan Gruber
Martin Hoelzle
author_sort Er Brenning
title Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
title_short Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
title_full Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
title_fullStr Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
title_full_unstemmed Published online in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/ppp.541 Sampling and Statistical Analyses of BTS Measurements
title_sort published online in wiley interscience (www.interscience.wiley.com). doi:10.1002/ppp.541 sampling and statistical analyses of bts measurements
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.494.5174
http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf
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http://www.geo.uzh.ch/~stgruber/pubs/2005_brenning-PPP.pdf
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