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

Huang, Yan; Xu, Jiahui; Xu, Jingyi; Zhao, Yelei; Yu, Bailang; Liu, Hongxing; Wang, Shujie; Xu, Wanjia; Wu, Jianping; Zheng, Zhaojun

doi:https://doi.org/10.5194/essd-14-4445-2022

Articles | Volume 14, issue 9

https://doi.org/10.5194/essd-14-4445-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Extreme environment datasets for the three poles

https://doi.org/10.5194/essd-14-4445-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 9

Data description paper

|

29 Sep 2022

Data description paper |

| 29 Sep 2022

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

Data sets

Daily cloud-free snow cover products for Tibetan Plateau from 2002 to 2021 Yan Huang and Jiahui Xu https://doi.org/10.11888/Cryos.tpdc.272204

Short summary

Reliable snow cover information is important for understating climate change and hydrological cycling. We generate long-term daily gap-free snow products over the Tibetan Plateau (TP) at 500 m resolution from 2002 to 2021 based on the hidden Markov random field model. The accuracy is 91.36 %, and is especially improved during snow transitional period and over complex terrains. This dataset has great potential to study climate change and to facilitate water resource management in the TP.