Abstract
A method was developed for scaling-up the AFRCWHEAT2 model of phenological development from the site to the continental scale. Four issues were addressed in this methodology: (i) the estimation of daily climatic data from monthly values, (ii) the estimation of spatially variable sowing dates, (iii) the simulation of multiple cultivars, and (iv) the validation of broad-scale models. Three methods for estimating daily minimum and maximum temperatures from monthly values were compared using AFRCWHEAT2: a sine curve interpolation, a sine curve interpolation with random daily variability, and two stochastic weather generators (WGEN and LARS-WG). The sine curve interpolation was selected for the continental scale application of AFRCWHEAT2 because computational time was short and errors were acceptably small. The average root mean square errors (RMSEs) for the dates of double ridges, anthesis and maturity were 6.4, 2.2 and 2.1 days, respectively. The spatial variability of European sowing dates was reproduced using a simple climatic criterion derived from the AFRCWHEAT2 vernalization curve. The use of several cultivar calibrations enabled the broad-scale model to capture current responses and compare responses to future climate change. Results from the continental scale model were validated using a geographically-referenced database of observed phenological dates, output from other site-based models and sensitivity analysis. The spatial model was able to emulate a similar spatial and temporal variability in phenological dates to these sources under the present climate. The predominant effect of an increase in mean temperature was a reduction in the emergence to double ridges phase. The shift in the timing of subsequent development stages to earlier in the season meant that changes in their duration were relatively minor. Changes in inter-annual temperature variability resulted in only small changes in the mean date of development stages, but their standard deviation altered significantly.
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