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author:

Chen, H. (Chen, H..) [1] | Qiu, H. (Qiu, H..) [2] | Bento, V.A. (Bento, V.A..) [3] | Wang, Q. (Wang, Q..) [4]

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Scopus

Abstract:

Extreme weather events are occurring more frequently and becoming increasingly unpredictable amid climate change. Low-temperature events (LTEs), in particular, exhibit dynamic variations across different regions and environments. Using a single threshold to define LTEs can be limiting, so this study considered nine distinct LTE types, characterized by varying consecutive day counts and percentile thresholds, to uncover their spatiotemporal patterns and dynamics. Furthermore, the correlation between LTEs and climate factors is assessed across distinct climatic regions in China. The results reveal that: the spatial distribution and overall dynamics of different LTEs are largely consistent, with higher frequency and longer duration observed in the Xinjiang region; the frequency and duration of various LTEs exhibit a declining trend across most regions, and minimum temperatures during LTEs demonstrate a decreasing trend in arid regions, juxtaposed with an increasing trend observed in cold zones. The threshold definition method using minimum temperatures below the 10th percentile for at least three consecutive days best characterizes LTEs in China. Additionally, LTEs show a strong correlation with longwave radiation. This study offers valuable quantitative insights for managing and responding to extreme weather events in the context of climate change. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

Keyword:

Climate change Climate factors Longwave radiation Low temperature events Minimum temperature

Community:

  • [ 1 ] [Chen H.]College of Environmental and Safety Engineering/The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Qiu H.]Department of Sustainable Earth Systems Sciences, University of Texas-Dallas, Richardson, 75080, TX, United States
  • [ 3 ] [Bento V.A.]Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
  • [ 4 ] [Wang Q.]College of Environmental and Safety Engineering/The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, 350116, China
  • [ 5 ] [Wang Q.]Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education of China, Fuzhou, 350116, China

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Source :

Climate Dynamics

ISSN: 0930-7575

Year: 2025

Issue: 2

Volume: 63

3 . 8 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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