Influence of climate forecasts, data assimilation, and uncertainty propagation on the performance of near-term phenology forecasts

Abstract

Evaluation of ecological forecasts is a vital step in the continuous improvement of near-term ecological forecasts. Here we performed a thorough evaluation of a near-term phenological forecast system which has been operating for several years. We evaluated point forecast accuracy and the reliability of the prediction intervals. We also tested the contribution of upstream climate forecasts on phenology forecast proficiency. We found that 9 month climate forecasts contributed little skill overall, though some species did benefit from them. The assimilation of observed winter and spring temperature provided the largest improvement of forecast skill throughout the spring. We also found that phenology forecast prediction intervals were most robust when uncertainty was propagated from climate, phenological model, and model parameters as opposed to using climate uncertainty alone. Our analysis points the way toward several potential improvements to the forecasting system, which can be re-evaluated at a future date in a continuous cycle of forecast refinement.