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

Hao, Xiaohua; Huang, Guanghui; Che, Tao; Ji, Wenzheng; Sun, Xingliang; Zhao, Qin; Zhao, Hongyu; Wang, Jian; Li, Hongyi; Yang, Qian

doi:https://doi.org/10.5194/essd-13-4711-2021

Articles | Volume 13, issue 10

https://doi.org/10.5194/essd-13-4711-2021

© Author(s) 2021. 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-13-4711-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 10

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, Guanghui Huang, Tao Che, Wenzheng Ji, Xingliang Sun, Qin Zhao, Hongyu Zhao, Jian Wang, Hongyi Li, and Qian Yang

Data sets

Daily 5-km Gap-free AVHRR snow cover extent product over China (1981-2019) Xiaohua Hao, Wenzheng Ji, Qin Zhao, Xingliang Sun, Jian Wang, Honyi Li, and Hongyu Zhao https://doi.org/10.11888/Snow.tpdc.271381

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.