Planned intervention: On Thursday 19/09 between 05:30-06:30 (UTC), Zenodo will be unavailable because of a scheduled upgrade in our storage cluster.
Published May 8, 2023 | Version v1
Dataset Open

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

  • 1. Chinese Academy of Sciences

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.

Notes

Funding provided by: Natural Science Foundation of China
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809
Award Number: 42125101

Files

README.md

Files (45.5 MB)

Name Size Download all
md5:7b8820812fa43069ff892b3ddddf5085
45.5 MB Download
md5:1924d62020d588147c92c07658fc6e31
1.7 kB Preview Download

Additional details

Related works

Is derived from
10.5281/zenodo.7874577 (DOI)