Data for: The start of frozen dates over northern permafrost regions with the changing climate

The soil freeze-thaw cycle in the permafrost regions has a significant impact on regional surface energy and water balance. Although increasing efforts have been made to understand the responses of spring thawing to climate change, the mechanisms controlling the global interannual variability of the...

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Main Author: Wu, Chaoyang
Format: Software
Language:unknown
Published: 2023
Subjects:
Online Access:https://zenodo.org/record/7874577
https://doi.org/10.5281/zenodo.7874577
id ftzenodo:oai:zenodo.org:7874577
record_format openpolar
spelling ftzenodo:oai:zenodo.org:7874577 2023-06-11T04:15:54+02:00 Data for: The start of frozen dates over northern permafrost regions with the changing climate Wu, Chaoyang 2023-05-08 https://zenodo.org/record/7874577 https://doi.org/10.5281/zenodo.7874577 unknown doi:10.5061/dryad.pzgmsbcrt doi:10.5281/zenodo.7874576 https://zenodo.org/communities/dryad https://zenodo.org/record/7874577 https://doi.org/10.5281/zenodo.7874577 oai:zenodo.org:7874577 info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT info:eu-repo/semantics/other software 2023 ftzenodo https://doi.org/10.5281/zenodo.787457710.5061/dryad.pzgmsbcrt10.5281/zenodo.7874576 2023-05-09T23:04:03Z The soil freeze-thaw cycle in the permafrost regions has a significant impact on regional surface energy and water balance. Although increasing efforts have been made to understand the responses of spring thawing to climate change, the mechanisms controlling the global interannual variability of the start date of permafrost frozen (SOF) remain unclear. Using long-term SOF from the combinations of multiple satellite microwave sensors between 1979–2020, and analytical techniques, including partial correlation, ridge regression, path analysis, and machine learning, we explored the responses of SOF to multiple climate change factors, including warming (surface and air temperature), start date of permafrost thawing (SOT), soil properties (soil temperature and volume of water), and the snow depth water equivalent (SDWE). Overall, climate warming exhibited the maximum control on SOF, but SOT in spring was also an important driver of SOF variability; among the 65.9% significant SOT and SOF correlations, 79.3% were positive, indicating an overall earlier thawing would contribute to an earlier frozen in winter. The machine learning analysis also suggested that apart from warming, SOT ranked as the second most important determinant of SOF. Therefore, we identified the mechanism responsible for the SOT-SOF relationship using the SEM analysis, which revealed that soil temperature change exhibited the maximum effect on this relationship, irrespective of the permafrost type. Finally, we analyzed the temporal changes in these responses using the moving window approach and found an increased effect of soil warming on SOF. Therefore, these results provide important insights into understanding and predicting SOF variations with future climate change. Funding provided by: Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 42125101 Software permafrost Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description The soil freeze-thaw cycle in the permafrost regions has a significant impact on regional surface energy and water balance. Although increasing efforts have been made to understand the responses of spring thawing to climate change, the mechanisms controlling the global interannual variability of the start date of permafrost frozen (SOF) remain unclear. Using long-term SOF from the combinations of multiple satellite microwave sensors between 1979–2020, and analytical techniques, including partial correlation, ridge regression, path analysis, and machine learning, we explored the responses of SOF to multiple climate change factors, including warming (surface and air temperature), start date of permafrost thawing (SOT), soil properties (soil temperature and volume of water), and the snow depth water equivalent (SDWE). Overall, climate warming exhibited the maximum control on SOF, but SOT in spring was also an important driver of SOF variability; among the 65.9% significant SOT and SOF correlations, 79.3% were positive, indicating an overall earlier thawing would contribute to an earlier frozen in winter. The machine learning analysis also suggested that apart from warming, SOT ranked as the second most important determinant of SOF. Therefore, we identified the mechanism responsible for the SOT-SOF relationship using the SEM analysis, which revealed that soil temperature change exhibited the maximum effect on this relationship, irrespective of the permafrost type. Finally, we analyzed the temporal changes in these responses using the moving window approach and found an increased effect of soil warming on SOF. Therefore, these results provide important insights into understanding and predicting SOF variations with future climate change. Funding provided by: Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 42125101
format Software
author Wu, Chaoyang
spellingShingle Wu, Chaoyang
Data for: The start of frozen dates over northern permafrost regions with the changing climate
author_facet Wu, Chaoyang
author_sort Wu, Chaoyang
title Data for: The start of frozen dates over northern permafrost regions with the changing climate
title_short Data for: The start of frozen dates over northern permafrost regions with the changing climate
title_full Data for: The start of frozen dates over northern permafrost regions with the changing climate
title_fullStr Data for: The start of frozen dates over northern permafrost regions with the changing climate
title_full_unstemmed Data for: The start of frozen dates over northern permafrost regions with the changing climate
title_sort data for: the start of frozen dates over northern permafrost regions with the changing climate
publishDate 2023
url https://zenodo.org/record/7874577
https://doi.org/10.5281/zenodo.7874577
genre permafrost
genre_facet permafrost
op_relation doi:10.5061/dryad.pzgmsbcrt
doi:10.5281/zenodo.7874576
https://zenodo.org/communities/dryad
https://zenodo.org/record/7874577
https://doi.org/10.5281/zenodo.7874577
oai:zenodo.org:7874577
op_rights info:eu-repo/semantics/openAccess
https://opensource.org/licenses/MIT
op_doi https://doi.org/10.5281/zenodo.787457710.5061/dryad.pzgmsbcrt10.5281/zenodo.7874576
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