CAREER: Understanding the Predictability and Dynamics of Spring Onset in North America

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The onset of Spring is a critical transition for agriculture and ecosystems, as plants leaf out and the growing season begins. The timing of onset can vary considerably from year to year, thus skillful onset predictions would be valuable for agricultural planning. But the predictability of Spring onset, and the processes that lead to year-to-year differences in onset date, are not well known. Research conducted here addresses both issues. The onset is clearly linked to local meteorological factors such as sunlight, warmth, and rainfall, but preliminary work by the PI and collaborators suggests that onset indicators such as the leaf-out of lilacs have greater predictability than the associated meteorological variables. The predictability of such phenological indicators based on the observational record is thus a focus of the research. The predictability of the associated meteorological conditions is also a target of the research, addressed using long-range forecasts from the National Multi-Model Ensemble (NMME) project. Onset predictability is further analyzed through 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. Further work on ensemble prediction compares ensemble forecast skill to a baseline provided by a simple empirical linear inverse model (LIM). The LIM comparison determines the advantage of using complex nonlinear forecast models over statistical methods based on past behavior, and tests the hypothesis that the predictable dynamics of the transition are essentially linear.The changes in local meteorology that control the timing of leaf-out and other phenology are in turn controlled by a reorganization of the large-scale atmospheric circulation that occurs rapidly in Spring. In particular, the splitting and northward migration of the jet stream over the central and eastern Pacific have been identified as a key factor. The dynamics of the jet transition are examined using a hierarchy of models of varying degrees of complexity, including a global atmospheric model with prescribed realistic sea surface temperatures (SSTs), the same model with the landmasses removed and simplified sea surface temperatures, and a linear baroclinic model.The educational component of this CAREER award involves the use of WRF as a tool for teaching weather and climate science to students in 20 regional high schools. The PI works with the Paleontological Research Institution's Museum of the Earth (MoE) to conduct training workshops for teachers on the use of the WRF model as a teaching tool. The workshops emphasizes learning by doing, interactively showing the teachers how their students can set up and run the model, make daily forecasts for nearby weather stations, and validate the forecasts the following day. In addition, the educational activities are an integral part of the research activity, as the WRF forecasts produced by the students are collected into ensembles used for research on spring onset predictability. Aside from the educational broader impacts, the research has broader impacts due to the potential value of skillful predictions of spring onset, which would benefit farmers and other decision makers in the agricultural sector. The project provides support and training to a graduate student and a postdoc and summer support for an undergraduate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.