Exploring the Impact of Climate Variability Estimates on Crop Models Predictions in CC Impact Assessment Studies.

Future climate projections, beyond the estimate of changes in mean values of weather variables, are characterized by large uncertainty in terms of estimates of weather variability.  Impact assessment studies are mostly run using simulation models which use as weather input post-processed time series originated via global circulation models. The uncertainty related to estimates of weather variability represents an unknown in impact assessments. This study aimed at exploring to what extent crop models outputs are affected by estimates of climate variability. The problem was approached by expanding variability of climate projections and exploring the effect on model responses of wheat and maize simulations. The crop growth models used were CropSyst and WOFOST, as re-implemented for the crop module in the platform BioMA, using the same water balance model for both. Further, the two crop modules were also linked to a model component specifically developed to simulate the impact of extreme weather events, as developed in the project MODEXTREME. Two different realizations of the AB1 emission scenario were used for time series centered on 2000, 2030, 2050, sampling nine Western-Europe sites. The ClimGen and Climak weather generators were used to generate time series of 30 years of daily data. The parameters corresponding to “unaltered” time series were the base to generate two further sets of parameters per WG and time horizon, broadening the variability of both air temperature and precipitation, while keeping the same monthly means. Progressively increasing climate variability via Climak mainly resulted in a slight reduction of both aboveground biomass (AGB) and yield of wheat, and larger on maize. Broadening climate variability via ClimGen caused a smaller effect on mean crop AGB production and yield, but expanded the variability across years. The increased variability caused a larger impact on time series related to 2050. Differences across crop models are still under evaluation.