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Agricultural droughts in China present considerable challenges for food security and water management but their spatiotemporal variability and links to global climate drivers remain incompletely understood. There has been no systematic analysis of the lagged teleconnections between large-scale atmospheric-oceanic indices (e.g. Southern Oscillation Index (SOI), Arctic Oscillation (AO), North Atlantic Oscillation (NAO)) and region-specific drought factors, limiting predictive capabilities for drought management. Hence, the key drought-causing factors for major agricultural regions in China and their lagged correlations with global climate indices were determined. Significant lagged relationships were identified: 2-month lagged positive correlation (r = 0.55) between the SOI and droughts in Southern China; 5-month lagged negative correlation (r = −0.72) between the AO and droughts in the Huang-HuaiHai Plain; and 12-month (r = −0.61) and 9-month (r = −0.66) lagged negative correlations with the Pacific North American Index (PNA) in the Northeast China Plain and Middle-lower Yangtze Plain, respectively. Additionally, the NAO exhibited an 11-month lagged positive correlation (r = 0.75) in the Loess Plateau and a 1-month lagged negative correlation (r = −0.70) in the Yunnan-Guizhou Plateau. These findings will improve drought prediction lead times, enabling targeted water resource planning and climate adaptation strategies.
Chen et al. (2025) studied this question.