A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures

High‐latitude ecosystems where the mean annual ground surface temperature is around or below 0°C are highly sensitive to global warming. This is largely because these regions contain vast areas of permafrost, which begins to thaw when the mean annual temperature rises above freezing. The Geophysical...

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Published in:Permafrost and Periglacial Processes
Main Authors: T. S. Sazonova, V. E. Romanovsky
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:https://doi.org/10.1002/ppp.449
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spelling ftrepec:oai:RePEc:wly:perpro:v:14:y:2003:i:2:p:125-139 2023-05-15T13:03:05+02:00 A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures T. S. Sazonova V. E. Romanovsky https://doi.org/10.1002/ppp.449 unknown https://doi.org/10.1002/ppp.449 article ftrepec https://doi.org/10.1002/ppp.449 2020-12-04T13:31:25Z High‐latitude ecosystems where the mean annual ground surface temperature is around or below 0°C are highly sensitive to global warming. This is largely because these regions contain vast areas of permafrost, which begins to thaw when the mean annual temperature rises above freezing. The Geophysical Institute Permafrost Lab has developed a new interactive geographical information systems (GIS) model to estimate the long‐term response of permafrost to changes in climate. An analytical approach is used for calculating both active layer thickness (ALT) and mean annual ground temperatures (MAGTs). When applied to long‐term (decadal or longer time scale) averages, this approach shows an accuracy of ±0.2–0.4°C for MAGTs and ±0.1–0.3 m for ALT calculations. The relative errors do not exceed 32% for ALT calculations, but typically they are between 10 and 25%. A spatial statistical analysis of the data from 32 sites in Siberia indicated a confidence level of 75% to have a deviation between measured and calculated MAGTs of 0.2–0.4°C. A detailed analysis has been performed for two regional transects in Alaska and eastern Siberia that has validated the use of the model. The results obtained from this analysis show that a more economical (in terms of computational time) analytical approach could be successfully used instead of a full‐scale numerical model in the regional and global scale analysis of permafrost spatial and temporal dynamics. This project has been a successful contribution to the Arctic Climate Impact Assessment project. Copyright © 2003 John Wiley & Sons, Ltd. Article in Journal/Newspaper Active layer thickness Arctic Climate Impact Assessment Arctic Global warming permafrost Alaska Siberia RePEc (Research Papers in Economics) Arctic Permafrost and Periglacial Processes 14 2 125 139
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description High‐latitude ecosystems where the mean annual ground surface temperature is around or below 0°C are highly sensitive to global warming. This is largely because these regions contain vast areas of permafrost, which begins to thaw when the mean annual temperature rises above freezing. The Geophysical Institute Permafrost Lab has developed a new interactive geographical information systems (GIS) model to estimate the long‐term response of permafrost to changes in climate. An analytical approach is used for calculating both active layer thickness (ALT) and mean annual ground temperatures (MAGTs). When applied to long‐term (decadal or longer time scale) averages, this approach shows an accuracy of ±0.2–0.4°C for MAGTs and ±0.1–0.3 m for ALT calculations. The relative errors do not exceed 32% for ALT calculations, but typically they are between 10 and 25%. A spatial statistical analysis of the data from 32 sites in Siberia indicated a confidence level of 75% to have a deviation between measured and calculated MAGTs of 0.2–0.4°C. A detailed analysis has been performed for two regional transects in Alaska and eastern Siberia that has validated the use of the model. The results obtained from this analysis show that a more economical (in terms of computational time) analytical approach could be successfully used instead of a full‐scale numerical model in the regional and global scale analysis of permafrost spatial and temporal dynamics. This project has been a successful contribution to the Arctic Climate Impact Assessment project. Copyright © 2003 John Wiley & Sons, Ltd.
format Article in Journal/Newspaper
author T. S. Sazonova
V. E. Romanovsky
spellingShingle T. S. Sazonova
V. E. Romanovsky
A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
author_facet T. S. Sazonova
V. E. Romanovsky
author_sort T. S. Sazonova
title A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
title_short A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
title_full A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
title_fullStr A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
title_full_unstemmed A model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
title_sort model for regional‐scale estimation of temporal and spatial variability of active layer thickness and mean annual ground temperatures
url https://doi.org/10.1002/ppp.449
geographic Arctic
geographic_facet Arctic
genre Active layer thickness
Arctic Climate Impact Assessment
Arctic
Global warming
permafrost
Alaska
Siberia
genre_facet Active layer thickness
Arctic Climate Impact Assessment
Arctic
Global warming
permafrost
Alaska
Siberia
op_relation https://doi.org/10.1002/ppp.449
op_doi https://doi.org/10.1002/ppp.449
container_title Permafrost and Periglacial Processes
container_volume 14
container_issue 2
container_start_page 125
op_container_end_page 139
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