Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau
Abstract Climate warming causes changes in permafrost distribution, which affects the surface energy balance, hydrologic cycle and carbon flux in cold regions. In this study, the Surface Frost Number model was applied to examine permafrost distribution on the Qinghai–Tibet Plateau (QTP) under the fo...
Published in: | Scientific Reports |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Nature Portfolio
2017
|
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-017-04140-7 https://doaj.org/article/23c813809e9b476e9da85439296809fe |
id |
ftdoajarticles:oai:doaj.org/article:23c813809e9b476e9da85439296809fe |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:23c813809e9b476e9da85439296809fe 2023-05-15T17:55:23+02:00 Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau Qing Lu Dongsheng Zhao Shaohong Wu 2017-06-01T00:00:00Z https://doi.org/10.1038/s41598-017-04140-7 https://doaj.org/article/23c813809e9b476e9da85439296809fe EN eng Nature Portfolio https://doi.org/10.1038/s41598-017-04140-7 https://doaj.org/toc/2045-2322 doi:10.1038/s41598-017-04140-7 2045-2322 https://doaj.org/article/23c813809e9b476e9da85439296809fe Scientific Reports, Vol 7, Iss 1, Pp 1-13 (2017) Medicine R Science Q article 2017 ftdoajarticles https://doi.org/10.1038/s41598-017-04140-7 2022-12-31T13:02:32Z Abstract Climate warming causes changes in permafrost distribution, which affects the surface energy balance, hydrologic cycle and carbon flux in cold regions. In this study, the Surface Frost Number model was applied to examine permafrost distribution on the Qinghai–Tibet Plateau (QTP) under the four RCPs (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). The Kappa statistic was used to evaluate model results by comparing simulations of baseline permafrost distribution (1981–2010) with the existing frozen soil maps. The comparison shows that the Surface Frost Number model is suitable for simulating the general characteristics of permafrost distribution on the QTP. Simulated results suggest that areas of permafrost degradation would be the smallest in the near-term (2011‒2040) with the rates of 17.17%, 18.07%, 12.95% and 15.66% under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively. The rate of permafrost degradation would be faster in the mid-term (2041‒2070), especially under the RCP8.5 scenario (about 41.42%). Areas of permafrost degradation would be the largest in the long-term (2071‒2099) relative to baseline conditions, with a modelled 64.31% decrease in permafrost distribution using the RCP8.5 scenario. Our results would help the decision‒making for engineering construction program on the QTP, and support local units in their efforts to adapt climate change. Article in Journal/Newspaper permafrost Directory of Open Access Journals: DOAJ Articles Scientific Reports 7 1 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Medicine R Science Q |
spellingShingle |
Medicine R Science Q Qing Lu Dongsheng Zhao Shaohong Wu Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
topic_facet |
Medicine R Science Q |
description |
Abstract Climate warming causes changes in permafrost distribution, which affects the surface energy balance, hydrologic cycle and carbon flux in cold regions. In this study, the Surface Frost Number model was applied to examine permafrost distribution on the Qinghai–Tibet Plateau (QTP) under the four RCPs (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). The Kappa statistic was used to evaluate model results by comparing simulations of baseline permafrost distribution (1981–2010) with the existing frozen soil maps. The comparison shows that the Surface Frost Number model is suitable for simulating the general characteristics of permafrost distribution on the QTP. Simulated results suggest that areas of permafrost degradation would be the smallest in the near-term (2011‒2040) with the rates of 17.17%, 18.07%, 12.95% and 15.66% under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively. The rate of permafrost degradation would be faster in the mid-term (2041‒2070), especially under the RCP8.5 scenario (about 41.42%). Areas of permafrost degradation would be the largest in the long-term (2071‒2099) relative to baseline conditions, with a modelled 64.31% decrease in permafrost distribution using the RCP8.5 scenario. Our results would help the decision‒making for engineering construction program on the QTP, and support local units in their efforts to adapt climate change. |
format |
Article in Journal/Newspaper |
author |
Qing Lu Dongsheng Zhao Shaohong Wu |
author_facet |
Qing Lu Dongsheng Zhao Shaohong Wu |
author_sort |
Qing Lu |
title |
Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
title_short |
Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
title_full |
Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
title_fullStr |
Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
title_full_unstemmed |
Simulated responses of permafrost distribution to climate change on the Qinghai–Tibet Plateau |
title_sort |
simulated responses of permafrost distribution to climate change on the qinghai–tibet plateau |
publisher |
Nature Portfolio |
publishDate |
2017 |
url |
https://doi.org/10.1038/s41598-017-04140-7 https://doaj.org/article/23c813809e9b476e9da85439296809fe |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Scientific Reports, Vol 7, Iss 1, Pp 1-13 (2017) |
op_relation |
https://doi.org/10.1038/s41598-017-04140-7 https://doaj.org/toc/2045-2322 doi:10.1038/s41598-017-04140-7 2045-2322 https://doaj.org/article/23c813809e9b476e9da85439296809fe |
op_doi |
https://doi.org/10.1038/s41598-017-04140-7 |
container_title |
Scientific Reports |
container_volume |
7 |
container_issue |
1 |
_version_ |
1766163309026869248 |