Spatial co-occurring crop yield failures strongly affect crop productivity, resulting in profound socioeconomic consequences. Cotton (Gossypium hirsutum L.) cultivation in Xinjiang accounts for 91 % of China’s national cotton production, and play a critical role in the global textile industry. However, given the wide range of climatic niches for cotton cultivation in Xinjiang, the lack of a comprehensive understanding of the spatial links in cotton yield failures and their relations with climate attributes impedes the design of effective regional strategies to enhance cotton productivity synchronously. To address this, we quantified the spatial dependence of cotton yield failures and assessed how climate variations affect cotton yield anomalies across regions in Xinjiang by conducting a case study focused on cotton cultivation in North Xinjiang (NXJ) and South Xinjiang (SXJ). We employed statistical analysis combining copula theory and multiple linear regression to untangle the regional cotton yield failure and their anomalies attributed to climate normal and extremes. Our results demonstrated a significant spatial connection between cotton yield anomalies in these regions, with a recurring pattern of yield failures emerging approximately every 15 years. Moreover, yearly variations in climate attributes explained over 40 % of the observed cotton yield anomalies. Climate extremes exerted a fourfold greater impact on cotton yield anomalies compared to the weaker signals from climate normals. Nevertheless, the cumulative climate normals significantly contributed to regional disparities in cotton yield anomalies. These findings highlight the multifaceted contributions of climatic drivers to spatially compounded cotton yield failures. Measures aimed at accelerating breeding cycle against both normal and extreme climate changes, as well as implementing targeted field management practices, are essential for synchronously enhancing cotton productivity in China and addressing critical challenges within the cotton industry.