Abstract
Abstract. A long-term Advanced Very High Resolution Radiometer (AVHRR) snow cover extent (SCE) product from 1981 until 2019 over China has been generated by the snow research team in the Northwest Institute of Eco-Environment and Resources (NIEER), Chinese Academy of Sciences. The NIEER AVHRR SCE product has a spatial resolution of 5 km and a daily temporal resolution, and it is a completely gap-free product, which is produced through a series of processes such as the quality control, cloud detection, snow discrimination, and gap-filling (GF). A comprehensive validation with reference to ground snow-depth measurements during snow seasons in China revealed the overall accuracy is 87.4 %, the producer's accuracy was 81.0 %, the user's accuracy was 81.3 %, and the Cohen's kappa (CK) value was 0.717. Another validation with reference to higher-resolution snow maps derived from Landsat-5 Thematic Mapper (TM) images demonstrates an overall accuracy of 87.3 %, a producer's accuracy of 86.7 %, a user's accuracy of 95.7 %, and a Cohen's kappa value of 0.695. These accuracies were significantly higher than those of currently existing AVHRR products. For example, compared with the well-known JASMES AVHRR product, the overall accuracy increased approximately 15 %, the omission error dropped from 60.8 % to 19.7 %, the commission error dropped from 31.9 % to 21.3 %, and the CK value increased by more than 114 %. The new AVHRR product is already available at https://doi.org/10.11888/Snow.tpdc.271381 (Hao et al., 2021).
Highlights
Snow cover is closely bound up with our climate
The results showed that the overall accuracy (OA), user’s accuracy (UA), and Cohen’s kappa (CK) values of the product decreased with increasing SD thresholds, while the producer’s accuracy (PA) values of the product increased with the increase in SD threshold
Relative to the JASMES snow cover extent (SCE) product, the Northwest Institute of Eco-Environment and Resources (NIEER) Advanced Very High Resolution Radiometer (AVHRR) OA increased approximately 15 %, the omission error dropped from 60.8 % to 19.7 %, the commission error dropped from 31.9 % to 21.3 %, and the CK value increased by more than 114 %
Summary
Snow cover is closely bound up with our climate. On the one hand, owing to snow’s unique optical properties (high albedo) it can affect the surface radiation budget severely and thereby our climate systems significantly (Warren, 1982; Huang et al, 2019). Changes in climate in turn affect global and regional snow covers. With the continuous warming of the global climate, snow cover on the Earth has been clearly shrinking over the past several decades (Barnett et al, 2005; Bormann et al, 2018). Long-term snow cover data are important for climate research and an indispensable indicator of climate change. Remote sensing is a widely used tool for monitoring snow cover extent (SCE) globally and regionally at various spa-
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