Articles | Volume 13, issue 10
Earth Syst. Sci. Data, 13, 4711–4726, 2021
https://doi.org/10.5194/essd-13-4711-2021

Special issue: Extreme environment datasets for the three poles

Earth Syst. Sci. Data, 13, 4711–4726, 2021
https://doi.org/10.5194/essd-13-4711-2021
Data description paper
15 Oct 2021
Data description paper | 15 Oct 2021

The NIEER AVHRR snow cover extent product over China – a long-term daily snow record for regional climate research

Xiaohua Hao et al.

Related authors

The Capability of high spatial-temporal remote sensing imagery for monitoring surface morphology of lake ice in Chagan Lake of Northeast China
Qian Yang, Xiaoguang Shi, Weibang Li, Kaishan Song, Zhijun Li, Xiaohua Hao, Fei Xie, Nan Lin, Zhidan Wen, Chong Fang, and Ge Liu
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-175,https://doi.org/10.5194/tc-2022-175, 2022
Preprint under review for TC
Short summary
Development and validation of a new MODIS snow-cover-extent product over China
Xiaohua Hao, Guanghui Huang, Zhaojun Zheng, Xingliang Sun, Wenzheng Ji, Hongyu Zhao, Jian Wang, Hongyi Li, and Xiaoyan Wang
Hydrol. Earth Syst. Sci., 26, 1937–1952, https://doi.org/10.5194/hess-26-1937-2022,https://doi.org/10.5194/hess-26-1937-2022, 2022
Short summary
Reconstruction of a daily gridded snow water equivalent product for the land region above 45° N based on a ridge regression machine learning approach
Donghang Shao, Hongyi Li, Jian Wang, Xiaohua Hao, Tao Che, and Wenzheng Ji
Earth Syst. Sci. Data, 14, 795–809, https://doi.org/10.5194/essd-14-795-2022,https://doi.org/10.5194/essd-14-795-2022, 2022
Short summary
Investigation of spatial and temporal variability of river ice phenology and thickness across Songhua River Basin, northeast China
Qian Yang, Kaishan Song, Xiaohua Hao, Zhidan Wen, Yue Tan, and Weibang Li
The Cryosphere, 14, 3581–3593, https://doi.org/10.5194/tc-14-3581-2020,https://doi.org/10.5194/tc-14-3581-2020, 2020
Short summary

Related subject area

Snow and Sea Ice
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
Earth Syst. Sci. Data, 14, 4445–4462, https://doi.org/10.5194/essd-14-4445-2022,https://doi.org/10.5194/essd-14-4445-2022, 2022
Short summary
Large ensemble of downscaled historical daily snowfall from an earth system model to 5.5 km resolution over Dronning Maud Land, Antarctica
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022,https://doi.org/10.5194/essd-14-1901-2022, 2022
Short summary
The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958–2021)
Matthieu Vernay, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, and Samuel Morin
Earth Syst. Sci. Data, 14, 1707–1733, https://doi.org/10.5194/essd-14-1707-2022,https://doi.org/10.5194/essd-14-1707-2022, 2022
Short summary
A new Greenland digital elevation model derived from ICESat-2 during 2018–2019
Yubin Fan, Chang-Qing Ke, and Xiaoyi Shen
Earth Syst. Sci. Data, 14, 781–794, https://doi.org/10.5194/essd-14-781-2022,https://doi.org/10.5194/essd-14-781-2022, 2022
Short summary
Reconstruction of a daily gridded snow water equivalent product for the land region above 45° N based on a ridge regression machine learning approach
Donghang Shao, Hongyi Li, Jian Wang, Xiaohua Hao, Tao Che, and Wenzheng Ji
Earth Syst. Sci. Data, 14, 795–809, https://doi.org/10.5194/essd-14-795-2022,https://doi.org/10.5194/essd-14-795-2022, 2022
Short summary

Cited articles

Arsenault, K. R., Houser, P. R., and De Lannoy, G. J. M.: Evaluation of the MODIS snow cover fraction product, Hydrol. Process., 28, 980–998, https://doi.org/10.1002/hyp.9636, 2014. 
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005. 
Bormann, K. J., Brown, R. D., Derksen, C., and Painter, T. H.: Estimating snow-cover trends from space, Nat. Clim. Change, 8, 924–928, https://doi.org/10.1038/s41558-018-0318-3, 2018. 
Che, T., Li, X., Jin, R., Armstrong, R., and Zhang, T.: Snow depth derived from passive microwave remote-sensing data in China, Ann. Glaciol., 49, 145–154, https://doi.org/10.3189/172756408787814690, 2008. 
Chen, S., Wang, X., Guo, H., Xie, P., Wang, J., and Hao, X.: A Conditional Probability Interpolation Method Based on a Space-Time Cube for MODIS Snow Cover Products Gap Filling, Remote Sens.-Basel, 12, 3577, https://doi.org/10.3390/rs12213577, 2020. 
Download
Short summary
Long-term snow cover data are not only of importance for climate research. Currently China still lacks a high-quality snow cover extent (SCE) product for climate research. This study develops a multi-level decision tree algorithm for cloud and snow discrimination and gap-filled technique based on AVHRR surface reflectance data. We generate a daily 5 km SCE product across China from 1981 to 2019. It has high accuracy and will serve as baseline data for climate and other applications.