A Four-Decade Dataset of Cotton Phenological Dynamics from the Agrometeorological Network in Xinjiang, China

This study presents a comprehensive, four-decade dataset (1981–2024) of cotton phenological dynamics, derived from 37 agrometeorological stations across the Xinjiang Uygur Autonomous Region, China’s primary cotton production zone. The dataset comprises over 22274 records (589 MB (uncompressed); 364 MB (compressed)) documenting 9 key phenological periods—sowing, emergence, three-leaf, five-leaf, squaring, flowering, boll crack, open boll, and physiological maturity—and 5 derived growth phases. It integrates historical paper-based records with modern electronic archives, ensuring continuity and reliability through a multi-tiered quality control process. Advanced analytical methods, including kernel density estimation and univariate linear regression, were employed to characterize spatial distributions, interannual variability, and long-term trends in phenology. Preliminary analysis using these methods revealed a significant advancing trend in most phenological stages across the region, highlighting a clear response of cotton growth to climate change. This dataset offers an unprecedented resource for investigating crop-climate interactions, validating process-based models, and informing climate adaptation strategies in arid and semi-arid agricultural systems. Its high spatial and temporal resolution supports diverse applications in agronomy, ecology, climatology, and agricultural policymaking.