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DOI	10.1016/j.jhydrol.2024.130706
	A 0.01° daily improved snow depth dataset for the Tibetan Plateau
	Yan, Dajiang; Zhang, Yinsheng
发表日期	2024
ISSN	0022-1694
EISSN	1879-2707
起始页码	631
卷号	631
英文摘要	Snowpack is highly sensitive to global warming, and an accurate understanding of the changes in snow depth (SD) is essential in analyzing the impacts of SD on both regional and global climate change. However, the application of SD datasets is limited owing to their coarse spatial resolution, especially at the basin scale. As a result, it is difficult to obtain high-quality, long-term gridded SD datasets at the kilometer scale, especially in cold and high-altitude regions. To address this issue, we combine an improved spatiotemporal downscaling algorithm and an efficient snow depletion curve method to develop a composite long-term daily 0.01 degrees SD dataset over the Tibetan Plateau (TP) by integrating an enhanced 0.05 degrees SD dataset and a cloud-gap-filled fractional snow cover (FSC) product. The new 0.01 degrees SD product is evaluated against the ground-observed SD data from 90 meteorological stations during 2001-2010, indicating that the new 0.01 degrees SD product (with a root mean square error of 1.27 cm d-1 and a mean absolute error of 0.31 cm d-1) performs better than its 0.05 degrees old version, as well as five other widely used SD products that cover the TP region. Thus, the new SD product is used to analyze the trends in the spatial SD pattern during 2000-2018. The results indicate that the annual SD is experiencing a decreasing trend over the inner and edge regions of the TP but an increasing trend over the areas between the inner and edge regions of the TP, e.g., the northern Himalayas, and upstream of the Yellow River, Yangtze River, and Mekong River. A negative correlation between the SD changes and the air temperature changes and a positive correlation between the SD changes and the snowfall changes are found in snow-dominated regions. Notably, the correlation between the SD changes and the air temperature changes is stronger than that between the SD changes and the snowfall changes, indicating that the SD is more sensitive to changes in air temperature. The new high-quality product will provide a more accurate means for understanding the SD changes in this region and a more accurate source of SD data for use in scientific studies that relate to hydrology, meteorology, and disaster evaluation.
英文关键词	Snow depth; Downscaling; Fractional snow cover; Tibetan Plateau
语种	英语
WOS研究方向	Engineering ; Geology ; Water Resources
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:001177196700001
来源期刊	JOURNAL OF HYDROLOGY
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/305895
作者单位	Chinese Academy of Sciences; Institute of Tibetan Plateau Research, CAS
推荐引用方式 GB/T 7714	Yan, Dajiang,Zhang, Yinsheng. A 0.01° daily improved snow depth dataset for the Tibetan Plateau[J]. 中国科学院青藏高原研究所,2024,631.
APA	Yan, Dajiang,&Zhang, Yinsheng.(2024).A 0.01° daily improved snow depth dataset for the Tibetan Plateau.JOURNAL OF HYDROLOGY,631.
MLA	Yan, Dajiang,et al."A 0.01° daily improved snow depth dataset for the Tibetan Plateau".JOURNAL OF HYDROLOGY 631(2024).