IMPACT OF TEMPERATURE AND PRECIPITATION VARIABILITY ON CROP MODEL PREDICTIONS

Future climate changes, as well as differences in climates from one lo cation to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperatu re and precipitation (and therefore also the interannual variability), without altering long-term mean values. For precipitation, both the m agnitude and the qualitative nature of the variability are manipulated . The synthetic daily weather series serve as input to four crop simul ation models. Crop growth is simulated for two locations and three soi l types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures a re below the optimum specified in the crop model for photosynethsis or biomass accumulation. However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. Th e influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was grea test when precipitation amounts were altered while keeping occurrence patterns unchanged, When increasing variability of precipitation was a chieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected. This se cond difference is attributed to the manner in which plant water uptak e is simulated. Failure to account for within-season changes in temper ature and precipitation variability may cause serious errors in predic ting crop-yield responses to future climate change when air temperatur es deviate from crop optima and when soil water is likely to be deplet ed at depth.