Diurnal Soil Freeze-Thaw Cycles and the Factors Determining Their Changes in Warming Climate in the Upper Brahmaputra Basin of the Tibetan Plateau

Ning Li, Lan Cuo, Yongxin Zhang, Gerald N. Flerchinger

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Soil freeze-thaw cycles play a critical role in ecosystem, hydrological and biogeochemical processes, and climate. The Tibetan Plateau (TP) has the largest area of frozen soil that undergoes freeze-thaw cycles in the low-mid latitudes. Evidence suggests ongoing changes in seasonal freeze-thaw cycles during the past several decades on the TP. However, the status of diurnal freeze-thaw cycles (DFTC) of shallow soil and their response to climate change largely remain unknown. In this study, using in-situ observations, the latest reanalysis, machine learning, and physics-based modeling, we conducted a comprehensive assessment of the spatiotemporal variations of DFTC and their response to climate change in the upper Brahmaputra (UB) basin. About 24 ± 8% of the basin is subjected to DFTC with a mean frequency of 87 ± 55 days during 1980–2018. The area and frequency of DFTC show small long-term changes during 1980–2018. Air temperature impacts on the frequency of DFTC changes center mainly around the freezing point (0°C). The spatial variations in the response of DFTC to air temperature can primarily be explained by three factors: precipitation (30.4%), snow depth (22.6%) and seasonal warming/cooling rates (14.9%). Both rainfall and snow events reduce diurnal fluctuations of soil temperature, subsequently reducing DFTC frequency, primarily by decreasing daytime temperature through evaporation-cooling and albedo-cooling effects, respectively. These results provide an in-depth understanding of diurnal soil freeze-thaw status and its response to climate change.

Original languageEnglish
Article numbere2023JD040369
JournalJournal of Geophysical Research: Atmospheres
Volume129
Issue number20
DOIs
StatePublished - Oct 28 2024
Externally publishedYes

Keywords

  • diurnal freeze-thaw cycle
  • environmental factors
  • machine learning
  • physics-based modeling
  • the Tibetan plateau
  • the upper brahmaputra basin

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