We investigate the role of ENSO climate patterns on global economic conditions. The estimated model is based on a rich and novel monthly dataset for 20 economies, capturing 80.2% of global output (based on 2021 IMF data) over the period 1999:01 to 2022:03. The empirical evidence from an estimated global vector autoregression with local projections (GFAVLP) model links an El Niño (EN) shock with higher output and inflation, corresponding with lower global economic policy uncertainty (GEPU). While a shock to the world oil and food price is inflationary, a food price shock leads to elevated GEPU, more so during a LN shock. A main finding is that an increase of the food price can be a source of global vulnerability. The findings indicate that the weather shock impact on global economic conditions is dependent on the climate state. Our result undermines existing studies connecting climate change and economic damage via statistical approach.