Using impact response surfaces to analyse the likelihood of impacts on crop yield under probabilistic climate change

摘要

Conventional methods of modelling impacts of future climate change on crop yields often rely on a limited selection of projections for representing uncertainties in future climate. However, large ensembles of climate projections offer an opportunity to estimate yield responses probabilistically. This study demonstrates an approach to probabilistic yield estimation using impact response surfaces (IRSs). These are constructed from a set of sensitivity simulations that explore yield responses to a wide range of changes in temperature and precipitation. Options for adaptation and different levels of future atmospheric carbon dioxide concentration [CO2] defined by representative concentration pathways (RCP4.5 and RCP8.5) were also considered. Model-based IRSs were combined with probabilistic climate projections to estimate impact likelihoods for yields of spring barley (Hordewn vulgare L.) in Finland during the 21st century. Probabilistic projections of climate for the same RCPs were overlaid on IRSs for corresponding [CO2] levels throughout the century and likelihoods of yield shortfall calculated with respect to a threshold mean yield for the baseline (1981-2010).