Global climate anomalies affect world economies and primary commodity prices. One of the more pronounced climate anomalies is El Niño Southern Oscillation (ENSO). In this study I examine the relationship between ENSO and world commodity prices using monthly time series of the sea-surface temperature anomalies in the Nino 3.4 region, and real prices of thirty primary agricultural commodities. I apply smooth transition auoregressive (STAR) modelling techniques to assess causal inferences that could potentially be camouflaged in the linear setting. I illustrate dynamics of ENSO and commodity price behavior using generalized impulse-response functions.