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

• Published in: Global Change Biology
• Main Authors: Li, Jialing, Wu, Chaoyang, Peñuelas, Josep, Ran, Youhua, Zhang, Yongguang
• Other Authors: National Natural Science Foundation of China
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2023
• Subjects: permafrost
• Online Access: http://dx.doi.org/10.1111/gcb.16752; https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.16752

Abstract 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 and 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 increased effect of soil warming on SOF. In conclusion, these results provide important insights into understanding and predicting SOF variations with future climate change.