  This paper presents an approach to phenology, one based on the use of a
method developed by the authors for event history data. Of specific interest is
the prediction of the so-called "bloom--date" of fruit trees in the agriculture
industry and it is this application which we consider, although the method is
much more broadly applicable. Our approach provides sensible estimate for a
parameter that interests phenologists -- Tbase, the thresholding parameter in
the definition of the growing degree days (GDD). Our analysis supports
scientists' empirical finding: the timing of a phenological event of a prenniel
crop is related the cumulative sum of GDDs. Our prediction of future
bloom--dates are quite accurate, but the predictive uncertainty is high,
possibly due to our crude climate model for predicting future temperature, the
time-dependent covariate in our regression model for phenological events. We
found that if we can manage to get accurate prediction of future temperature,
our prediction of bloom--date is more accurate and the predictive uncertainty
is much lower.
