Climate variability and corn yield in Argentina: the role of El Niño–Southern Oscillation index and other climate drivers

Understanding how climate variability influences corn yield is essential for improving agricultural forecasting and resilience strategies. This study examines the role of four major climate indices—El Niño Southern Oscillation (ENSO) index related ONI, IOD, AAO and TSA—on corn yield variability across Argentina's diverse agro-ecological regions (22° to 39° S latitude). Using historical rainfed yield data at the county level and monthly climate records (1994–2024), we assessed the temporal and spatial relationships between these indices and detrended yield anomalies. ONI emerged as the dominant predictor, particularly in the core production region of the country, where its positive phase correlated strongly with increased rainfall during critical crop growth stages. IOD also exerted a significant influence, although it was more localized and seasonally dependent, primarily affecting mid-summer precipitation patterns at the core region. Conversely, the effects of AAO and TSA were weaker and even more regionally constrained (for Cordoba and coastal areas, respectively). A Principal Component Analysis (PCA) including all four indexes reinforced these findings, highlighting the combined and overlapping influence of climate indices rather than simple relationships. Notably, the absence of a clear regional differentiation in the PCA suggests that climate signals act broadly across Argentina, making it difficult to generalize yield predictions based on any single index. These results challenge the conventional assumption that ENSO alone can reliably forecast yield outcomes and underline the necessity of multi-index approaches for robust agricultural modeling. By integrating climate indices into predictive frameworks, this research could enhance yield forecasting accuracy, supporting adaptive management strategies in the face of increasing climate variability.