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JULES-crop is a parametrisation of crops in the Joint UK Land EnvironmentSimulator (JULES). We investigate the sources of the interannual variabilityin the modelled maize yield, using global runs driven by reanalysis data,with a view to understanding the impact of various approximations in thedriving data and initialisation. The standard forcing data set for JULESconsists of a combination of meteorological variables describingprecipitation, radiation, temperature, pressure, specific humidity and wind,at subdaily time resolution. We find that the main characteristics of themodelled yield can be reproduced with a subset of these variables and usingdaily forcing, with internal disaggregation to the model time step. This hasimplications in particular for the use of the model with seasonal forcingdata, which may not have been provided at subdaily resolution for allrequired driving variables. We also investigate the effect on annual yield ofinitialising the model with climatology on the sowing date. Thisapproximation has the potential to considerably simplify the use of the modelwith seasonal forecasts, since obtaining observations or reanalysis outputfor all the initialisation variables required by JULES for the start date ofthe seasonal forecast would present significant practical challenges

Sources of interannual yield variability in JULES-crop and implications for forcing with seasonal weather forecasts