Articles | Volume 18, issue 4
https://doi.org/10.5194/tc-18-1817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-1817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
Jiahui Xu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
Yao Tang
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
Linxin Dong
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
Shujie Wang
Department of Geography, Earth and Environmental Systems Institute, Pennsylvania State University, University Park, PA, 16802, USA
Bailang Yu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
Jianping Wu
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
Zhaojun Zheng
National Satellite Meteorological Center, Beijing, 100081, China
Yan Huang
CORRESPONDING AUTHOR
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China
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30 citations as recorded by crossref.
- Power Spectra’s Perspective on Meteorological Drivers of Snow Depth Multiscale Behavior over the Tibetan Plateau Y. Cao & L. Jiang https://doi.org/10.3390/land14040790
- Linkage between the Tibetan Plateau and Global Extreme Heat in 2023 X. Sun et al. https://doi.org/10.1016/j.atmosres.2026.108976
- Duration of vegetation green-up response to snowmelt on the Tibetan Plateau J. Ni et al. https://doi.org/10.5194/bg-22-2637-2025
- Changes in lake surface temperature on the Tibetan Plateau from 2000 to 2022 and their driving factors Y. Qiu et al. https://doi.org/10.1007/s11430-024-1527-4
- A novel perspective on near-surface soil freeze states: Discontinuity of the freeze process X. Wang et al. https://doi.org/10.1016/j.geoderma.2025.117258
- Incorporating spatial heterogeneity into the analysis of snow cover variability and drivers in the High Mountain Asia region B. He et al. https://doi.org/10.1016/j.jhydrol.2025.134080
- A Novel Approach for Cloud-Free MODIS NDSI Reconstruction on the Tibetan Plateau Combining Spatiotemporal Cube and Environmental Features L. Dong et al. https://doi.org/10.1109/TGRS.2025.3542095
- Impacts of horizontal resolution on snow simulation and its relationship with temperature in CAS-ESM2 J. Zhou et al. https://doi.org/10.1007/s00382-026-08191-3
- Significant May-to-June persistence of precipitation in the western Tibetan Plateau: memory effect of local soil moisture H. Zhang et al. https://doi.org/10.1088/2515-7620/ae0910
- A Novel Survival Analysis Model for Quantifying Time-Lagged and Nonlinear Effects of Meteorological Conditions on Snow Phenology J. Xu et al. https://doi.org/10.1109/TGRS.2025.3588200
- Spatiotemporal evolution of vegetation phenology and its response to environmental factors in the upper and middle reaches of the Yellow River Basin X. Li et al. https://doi.org/10.1016/j.jenvman.2025.124970
- Spatiotemporal lag effects between vegetation dynamics and climate variability on the Tibetan Plateau during 2001–2024 Z. Satti et al. https://doi.org/10.1016/j.rsase.2026.101984
- Intensifying heatwave events affect snow phenology over the Tibetan Plateau G. Deng et al. https://doi.org/10.1016/j.jhydrol.2025.133293
- Increased sensitivity of snow phenology to temperature in unstable snow regions since 1990 Q. Li et al. https://doi.org/10.1016/j.jhydrol.2025.134121
- The Impact of Autumn Snowfall on Vegetation Indices and Autumn Phenology Estimation Y. Tang et al. https://doi.org/10.3390/rs16244783
- Study on the mechanism of subgrade deformation of the Qinghai-Tibet railway in permafrost regions based on multisource data Q. Wang et al. https://doi.org/10.1016/j.trgeo.2025.101678
- Spatiotemporal variation of snow cover over the Tibetan Plateau based on the MODIS fractional snow cover product: 2000–2023 Y. Zheng et al. https://doi.org/10.1016/j.jhydrol.2025.134474
- Dynamic identification of snow phenology in the Northern Hemisphere L. Wang et al. https://doi.org/10.5194/tc-19-2733-2025
- Seasonal transition in snow effects on vegetation growth across the Tibetan Plateau Z. Meng et al. https://doi.org/10.3389/fpls.2026.1855382
- Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change H. Peng et al. https://doi.org/10.3390/w17172579
- MAT-MS: A mask-aware transformer for constructing gap-free MODIS normalized difference snow index products J. Xu et al. https://doi.org/10.1016/j.isprsjprs.2025.07.004
- Multi-Decadal Vegetation Phenology Dynamics in China’s Arid Northwest: Unraveling Climate–Terrain Interactions via PLS-SEM J. Zhu et al. https://doi.org/10.3390/land15010061
- Water quality evaluation and characterization of its spatio-temporal variability in the Western Route of South-to-North Water Diversion Project in China A. Zhao et al. https://doi.org/10.1016/j.ecolind.2025.114439
- Extreme minimum temperature and precipitation indices drive the shortening of snow cover duration in China H. Wu et al. https://doi.org/10.1016/j.ejrh.2026.103663
- Assessing the Response of the Net Primary Productivity to Snow Phenology Changes in the Tibetan Plateau: Trends and Environmental Drivers J. Liu et al. https://doi.org/10.3390/rs16193566
- Dynamic monitoring of eco-environmental quality in the Greater Mekong Subregion: Evolutionary characteristics and country differences C. Liu et al. https://doi.org/10.1016/j.eiar.2024.107700
- Snow Cover Variability and Trends over Karakoram, Western Himalaya and Kunlun Mountains During the MODIS Era (2001–2024) C. Almagioni et al. https://doi.org/10.3390/rs17050914
- Urban green spaces enhanced human thermal comfort through dual pathways of cooling and humidifying X. Yu et al. https://doi.org/10.1016/j.scs.2024.106032
- Land surface heatwaves advance spring runoff timing in the Yangtze River headwaters Z. Tian et al. https://doi.org/10.1016/j.ejrh.2026.103582
- 2000~2022年青藏高原湖泊表面温度变化及其驱动因素 元. 邱 et al. https://doi.org/10.1360/SSTe-2024-0186
Saved (final revised paper)
Latest update: 24 Jul 2026
Short summary
Understanding snow phenology (SP) and its possible feedback are important. We reveal spatiotemporal heterogeneous SP on the Tibetan Plateau (TP) and the mediating effects from meteorological, topographic, and environmental factors on it. The direct effects of meteorology on SP are much greater than the indirect effects. Topography indirectly effects SP, while vegetation directly effects SP. This study contributes to understanding past global warming and predicting future trends on the TP.
Understanding snow phenology (SP) and its possible feedback are important. We reveal...