Predicting When Spring Will Come

The onset of Spring is a critical transition for agriculture and ecosystems, a time when plants leaf out and the growing season begins. The timing of onset, however, can vary considerably from year to year. The predictability, and the processes that lead to year-to-year differences in onset date, is not well known. Spring onset is clearly linked to local meteorological factors, such as sunlight, warmth, and rainfall.

Toby R. Ault, Earth and Atmospheric Sciences, and collaborators have done preliminary work, suggesting that onset indicators such as the leaf-out of lilacs have greater predictability than the associated meteorological variables. The project focuses on the predictability of these phenological indicators.

The researchers also look at long-range forecasts from the National Multi-Model Ensemble (NMME) project. They explore information from a new crowdsourced retrospective forecasting project, in which the Weather Research and Forecasting (WRF) model is configured for personal computers and disseminated to local high school students. Students create WRF forecasts using different versions of the model physics, thereby accounting for uncertainties inherent in the forecast model. They also examine large-scale atmospheric circulation, using various models. These efforts combine toward a better understanding of the factors and dynamics that will lead to Spring onset predictability.

Cornell Researchers

Funding Received

$940 Thousand spanning 5 years