A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges

Estimates of permafrost distribution in mountain regions are important for the assessment of climate change effects on natural and human systems. In order to make permafrost analyses and the establishment of guidelines for e.g. construction or hazard assessment comparable and compatible between regi...

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Published in:The Cryosphere
Main Authors: L. Boeckli, A. Brenning, S. Gruber, J. Noetzli
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2012
Subjects:
Online Access:https://doi.org/10.5194/tc-6-125-2012
https://doaj.org/article/99b9ba055d2b4e1a9113a013ab51c8fe
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spelling ftdoajarticles:oai:doaj.org/article:99b9ba055d2b4e1a9113a013ab51c8fe 2023-05-15T17:56:58+02:00 A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges L. Boeckli A. Brenning S. Gruber J. Noetzli 2012-01-01T00:00:00Z https://doi.org/10.5194/tc-6-125-2012 https://doaj.org/article/99b9ba055d2b4e1a9113a013ab51c8fe EN eng Copernicus Publications http://www.the-cryosphere.net/6/125/2012/tc-6-125-2012.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-6-125-2012 1994-0416 1994-0424 https://doaj.org/article/99b9ba055d2b4e1a9113a013ab51c8fe The Cryosphere, Vol 6, Iss 1, Pp 125-140 (2012) Environmental sciences GE1-350 Geology QE1-996.5 article 2012 ftdoajarticles https://doi.org/10.5194/tc-6-125-2012 2022-12-30T22:57:40Z Estimates of permafrost distribution in mountain regions are important for the assessment of climate change effects on natural and human systems. In order to make permafrost analyses and the establishment of guidelines for e.g. construction or hazard assessment comparable and compatible between regions, one consistent and traceable model for the entire Alpine domain is required. For the calibration of statistical models, the scarcity of suitable and reliable information about the presence or absence of permafrost makes the use of large areas attractive due to the larger data base available. We present a strategy and method for modelling permafrost distribution of entire mountain regions and provide the results of statistical analyses and model calibration for the European Alps. Starting from an integrated model framework, two statistical sub-models are developed, one for debris-covered areas (debris model) and one for steep bedrock (rock model). They are calibrated using rock glacier inventories and rock surface temperatures. To support the later generalization to surface characteristics other than those available for calibration, so-called offset terms have been introduced into the model that allow doing this in a transparent and traceable manner. For the debris model a generalized linear mixed-effect model (GLMM) is used to predict the probability of a rock glacier being intact as opposed to relict. It is based on the explanatory variables mean annual air temperature (MAAT), potential incoming solar radiation (PISR) and the mean annual sum of precipitation (PRECIP), and achieves an excellent discrimination (area under the receiver-operating characteristic, AUROC = 0.91). Surprisingly, the probability of a rock glacier being intact is positively associated with increasing PRECIP for given MAAT and PISR conditions. The rock model is based on a linear regression and was calibrated with mean annual rock surface temperatures (MARST). The explanatory variables are MAAT and PISR. The linear regression achieves a root ... Article in Journal/Newspaper permafrost The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 6 1 125 140
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental sciences
GE1-350
Geology
QE1-996.5
L. Boeckli
A. Brenning
S. Gruber
J. Noetzli
A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description Estimates of permafrost distribution in mountain regions are important for the assessment of climate change effects on natural and human systems. In order to make permafrost analyses and the establishment of guidelines for e.g. construction or hazard assessment comparable and compatible between regions, one consistent and traceable model for the entire Alpine domain is required. For the calibration of statistical models, the scarcity of suitable and reliable information about the presence or absence of permafrost makes the use of large areas attractive due to the larger data base available. We present a strategy and method for modelling permafrost distribution of entire mountain regions and provide the results of statistical analyses and model calibration for the European Alps. Starting from an integrated model framework, two statistical sub-models are developed, one for debris-covered areas (debris model) and one for steep bedrock (rock model). They are calibrated using rock glacier inventories and rock surface temperatures. To support the later generalization to surface characteristics other than those available for calibration, so-called offset terms have been introduced into the model that allow doing this in a transparent and traceable manner. For the debris model a generalized linear mixed-effect model (GLMM) is used to predict the probability of a rock glacier being intact as opposed to relict. It is based on the explanatory variables mean annual air temperature (MAAT), potential incoming solar radiation (PISR) and the mean annual sum of precipitation (PRECIP), and achieves an excellent discrimination (area under the receiver-operating characteristic, AUROC = 0.91). Surprisingly, the probability of a rock glacier being intact is positively associated with increasing PRECIP for given MAAT and PISR conditions. The rock model is based on a linear regression and was calibrated with mean annual rock surface temperatures (MARST). The explanatory variables are MAAT and PISR. The linear regression achieves a root ...
format Article in Journal/Newspaper
author L. Boeckli
A. Brenning
S. Gruber
J. Noetzli
author_facet L. Boeckli
A. Brenning
S. Gruber
J. Noetzli
author_sort L. Boeckli
title A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
title_short A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
title_full A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
title_fullStr A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
title_full_unstemmed A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges
title_sort statistical approach to modelling permafrost distribution in the european alps or similar mountain ranges
publisher Copernicus Publications
publishDate 2012
url https://doi.org/10.5194/tc-6-125-2012
https://doaj.org/article/99b9ba055d2b4e1a9113a013ab51c8fe
genre permafrost
The Cryosphere
genre_facet permafrost
The Cryosphere
op_source The Cryosphere, Vol 6, Iss 1, Pp 125-140 (2012)
op_relation http://www.the-cryosphere.net/6/125/2012/tc-6-125-2012.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-6-125-2012
1994-0416
1994-0424
https://doaj.org/article/99b9ba055d2b4e1a9113a013ab51c8fe
op_doi https://doi.org/10.5194/tc-6-125-2012
container_title The Cryosphere
container_volume 6
container_issue 1
container_start_page 125
op_container_end_page 140
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