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productivity declines in the Punjab, Pakistan resulted in an increase in vulnerable households and poverty rate (Rosenzweig et al. 2018a). Empirical statistical models have been applied widely to different cropping systems, at multiple scales. Analyses using statistical models for maize and wheat tested with global climate model scenarios found that the RCP4.5 scenario reduced the size of average yield impacts, risk of major slowdowns, and exposure to critical heat extremes compared to RCP8.5 in the latter decades of the 21st century . Impacts on crops grown in the tropics are projected to be more negative than in mid – to high-latitudes as stated in AR5 and confirmed by recent studies The hottest mandala version all over printed slippers(e.g., Levis et al. ). These projected negative effects in the tropics are especially pronounced under conditions of explicit nitrogen stress (Rosenzweig et al. ) (Figure 5.4). Climate change effects have been studied on a global scale following a variety of methodologies that have recently been compared (Lobell and Asseng ; Zhao et al. 2017a233 and Liu et al. ). Approaches to study global and local changes include global gridded crop model simulations (e.g., Deryng et al. ), point-based crop model simulations (e.g., Asseng et al. ), analysis of point-based observations in the field (e.g., Zhao et al. ), and temperature-yield regression models (e.g., Auffhammer and Schlenker ). For an evaluation of model skills see example used in AgMIP (Müller et al. 2017b239). There

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