Preprints
https://doi.org/10.5194/tc-2023-135
https://doi.org/10.5194/tc-2023-135
13 Oct 2023
 | 13 Oct 2023
Status: this preprint is currently under review for the journal TC.

Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2021

Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang

Abstract. A detailed understanding of snow cover and its possible feedback on climate change on the Tibetan Plateau (TP) is of great importance. However, spatiotemporal variability in snow phenology (SP) and its influencing factors on the TP remain unclear. Based on the daily gap-free snow cover product (HMRFS-TP) with 500 m resolution, this study investigated the spatiotemporal variation in snow cover days (SCD), snow onset date (SOD), and snow end date (SED) in the TP from 2002–2021. A Structural Equation Model was used to select the factors affecting SP as well as to quantify the direct and indirect effects of meteorological factors, geographical location, topography, vegetation greenness, and atmospheric pollution factors on SP. The results indicated that the spatial distribution of SP on the TP was extremely uneven and exhibited notable temporal heterogeneity. SP showed vertical zonality influenced by elevation (longer SCD, earlier SOD, and later SED at higher elevations). Meanwhile, their interannual variations tended to decrease, delay, and delay slightly from 2002 to 2021. In particular, the interannual variation in SP also had an elevation-dependent pattern below 5800 m. Meteorological factors had direct and indirect effects, vegetation greenness only had a direct impact, and geographical location, topography, and atmospheric pollution only indirectly affected SP. Undoubtedly, meteorological factors were the dominant factors in particular temperature. However, the influence of other factors cannot be ignored. As two important factors, the relative importance of temperature versus precipitation to SP shifted across elevation. This study contributes to the understanding of snow variation in response to global warming over the past two decades by providing a basis for predicting future environmental and climate changes and their impacts on the TP.

Jiahui Xu et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on tc-2023-135', Ning Ma, 29 Oct 2023 reply
  • RC1: 'Comment on tc-2023-135', Anonymous Referee #1, 12 Nov 2023 reply

Jiahui Xu et al.

Data sets

HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model Yan Huang, Jiahui Xu, Jingyi Xu, Yelei Zhao, Bailang Yu, Hongxing Liu, Shujie Wang, Wanjia Xu, Jianping Wu, and Zhaojun Zheng https://doi.org/10.5194/essd-14-4445-2022

Jiahui Xu et al.

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Short summary
Understanding snow phenology (SP) and its possible feedback are important. We reveal dynamic variability in SP and the mediating effects from meteorological, topographic, and environmental factors on the Tibetan Plateau (TP). SP is spatiotemporal heterogeneous and its interannual variation is elevation-dependent. The importance of temperature versus precipitation to SP shifted across elevation. This study contributes to understanding past global warming and predicting future trends on the TP.