This paper uses time-vary ing smooth transition autoregressive (TV-STAR) model to investigate the asymmetric nature of ENSO (an exogenous climatic factor) with respect to the non-linear dynamics of food prices in sub-Saharan Africa (SSA). Curating food price series from more than 1100 markets from 36 SSA countries, the study finds that ENSO (linearly or nonlinearly) affects roughly half of food prices considered, with most nonlinear models exhibiting strong asymmetric properties with shock-inflicted persistence. Moreover, in terms of the location of the burden of ENSO impact, I find a geographical and food product divide. Specifically, ENSO appears to be more efficacious on maize prices in Southern, Eastern and some parts of Central Africa, while the effect is subdued in the Western African subregion. On the other hand, imported rice and processed foods such as bread appear to be the most affected, while local rice, cassava, millet and animal products like meat and milk are least affected. The policy implication of this dichotomy is that response to ENSO news should be subregion-specific rather than region-specific depending on how the subregions absorb the shock.