Assessment of global crop yield volatility and its association with large scale climate, water and temperature variability

Abstract

In this study, anomalous spatial and temporal national-based yield values of maize, rice, sorghum and soybean from 1961 to 2013 are extracted using the multivariate statistical procedure of robust principal component analysis (RPCA). Sea surface temperature anomalies (SSTa), oceanic and atmospheric indices, air temperature anomalies (ATa) and the Palmer drought severity index (PDSI) are used to examine the association between crop yield variability in the most volatile years (MVY). Results show that warmer-than-normal winter time SSTa (El Niño) in the Pacific Ocean exerts the most dominating influence on global rice and sorghum yield volatility. In addition, extreme soybean and maize volatility are associated with mutual climatic teleconnection patterns. Since many large-scale climatic patterns are periodic and predictable seasons in advance, these findings can inform policy makers for global food security planning and management as well as global crop markets.