Crop-specic exposure to extreme temperature and wetness for the globe for the last half century

Abstract:

Climate shocks represent a major disruption to agricultural production, yet a consistent and comprehensive database of extreme weather events that explicitly takes crop physiology into account does not exist. To this end, we collate crop physiological thresholds from the agronomy literature and use these thresholds to define agriculturally-relevant weather shocks. We combine these crop-specific climate thresholds with estimates on the likely locations of specific crops and high-resolution climate information to quantify crop-specific exposure to extreme weather. Specifically, we quantify the annual exposure rate of crops to both thermal and hydrologic extreme events during the growing season using a 0.25-degree spatial grid and daily time scale from 1961-2014. Additionally, we integrate global gridded climate and crop calendar data with a time-varying and crop-specific land use dataset. We refer to this approach as the Agriculturally-Relevant Exposure to Shocks (ARES) model, and make all ARES model output accessible with this paper. We find on average (across all crops) a 47.5% reduction in exposure rate and a 27.9% reduction in affected pixels for extreme heat when accounting for crop-specific temperature thresholds. Crops generally did not experience an increase in exposure rate when accounting for crop-specific minimum temperature thresholds. Our results show that extreme wet events that do not account for crop-specific factors may underestimate exposure rate, while overestimating the spatial extent of the affected areas. Conversely, extreme dry events that do not account for crop factors could potentially result in an overestimate of both the exposure rate and spatial extent. Of the 17 crops included in this study, 13 had an increase in exposure to extreme heat, while 9 increased their exposure to extreme cold. All crops in this study show a statistically significant increase in exposure to both extreme wetness and dryness. We compare our refined model results with the more coarse EM-DAT disaster database. Our results provide improved understanding of the evolution of crop-specific weather shocks globally for the last half century.