This study examines the effects of temperature and precipitation on the mean and 7 variance of seasonal rice yield in Andhra Pradesh, India, over a period of 33 years 8 (1969-2002). For this purpose, two distinct approaches are employed: (i) panel data 9 analysis using Just and Pope stochastic production function and (ii) quantile regression 10 approach. The first approach suggests that, in general, an increase in temperature as 11 well as inter-annual variance of temperature and rainfall adversely affect the mean crop 12 yield, while the effect of increase in precipitation highly depends on the cropping season. 13 Furthermore, an increase in average temperature, rainfall and their respective inter- 14 annual variance are likely to increase inter-annual variability in crop yield. Second, 15 the quantile regression reveals that rice yield’s sensitivity to climate change differs 16 significantly across the quantiles of yield distribution. In particular, the adverse effect 17 of climate change is found to be more profound for the crop yields in lower quantiles. 18 In addition, evidences in support of heterogeneity in the impact of climate change 19 across the agro-climatic zones are also found. Overall, these findings call for a more 20 location specific adaptation policies to address heterogeneity and an integrated policy 21 framework covering the downside risk to build resilience in the food security system.