Introduction to a 45-year (1979–2023) global daily snow cover fraction product from multiple AVHRR satellites with accuracy assessment

Accurate monitoring of seasonal to decadal snow cover dynamics is essential for climate change attribution and sustainable water resource management. As part of the European Space Agency (ESA) Snow Climate Change Initiative (CCI+) Phase-2 project, this study introduces an Advanced Very High Resolution Radiometer (AVHRR) snow cover fraction (SCF) product portfolio, with a particular emphasis on the development of AVHRR10C1. V4—the first 45-year (1979–2023), global, daily SCF product. This dataset achieves unprecedented temporal consistency by addressing long-standing challenges such as orbital drift, inter-sensor inconsistencies, reduced cloud contamination, and enhanced SCF retrieval accuracy. The AVHRR10C1.V4 product was generated by integrating newly calibrated EUMETSAT AVHRR Fundamental Data Record (FDR) data from 16 AVHRR sensors on a 0.05◦ grid through a calibration method, modified cloud masking, an updated SCF retrieval method, refined post-processing, and a novel consolidation framework. Comprehensive validation against 66 high-resolution Landsat/Sentinel-2 SCF maps and extensive ground-based snow measurements confirms the robust accuracy of the AVHRR10C1.V4 product: root mean square errors of 16–19% for viewable snow cover fraction (SCFV) and 18–28% for ground snow cover fraction (SCFG), with overall accuracy (OA) ranging from 0.80 to 0.92. The consolidation approach remarkably reduces RMSEs by 7%–48% and lowers missing data rates by ~30% compared to single-sensor products. The product maintains strong temporal consistency with ERA5-Land SCF product (R > 0.8) and in situ snow measurements. Statistical analysis over the 45-year record and multiple separate periods confirms minimal sensor-drift biases, revealing no statistically significant breakpoints or drift trends (Mann-Kendall p > 0.05). While the SCFV product proves robust to variations in viewing geometry and vegetation conditions, SCFG accuracy is more sensitive to forest cover density—exhibiting substantially increased estimation uncertainties in dense forest canopies (forest cover density > 50%) due to canopy radiative effects and the use of static land cover assumptions. This open-access, climate data record–quality AVHRR10C1. V4 product establishes a critical benchmark for studying snow-climate interactions and long-term cryospheric monitoring. It supports the development of next-generation global SCF products, enabling reliable detection of snow trends, improved hydrological modeling, and informed climate adaptation in a warming climate.