Current Projects

Atmospheric dynamicists try to understand why the atmosphere moves in the way it does. Because of the inherently chaotic nature of the atmosphere, and because the atmosphere is strongly linked to the oceans, land-surface, biosphere, the types of interactions that occur are very complex. However, a wide range of tools, ranging from observational data to simplified models, can help atmospheric dynamicists understand (and even predict) atmospheric motions.

More specifically, my research aims at extending the duration of reliable weather forecasts, and to then explore how the dynamical processes that are important on these short timescales may manifest on longer, climate-change timescales. The traditional approach to weather forecasting on one- to two-week timescales utilizes weather forecasting models, but on timescales longer than two weeks, the value of deterministic (or ensemble-based probabilistic) forecasts weakens. This is due to the presence of chaotic variability in the atmosphere. Yet certain modes of variability in the climate system have timescales longer than this two-week threshold, and the key to longer-scale prediction is to take advantage of these modes. By understanding the impacts of these modes of variability on surface weather, the potential for improved forecasts on a monthly timescale can be demonstrated and eventually realized. As many of these processes may be modified under climate change (or alternately, climate change may project onto these climate modes), a better understanding of these modes can also help improve the quality of climate change projections.

Two such classes of modes of variability are stratospheric variability (both in the tropical and polar stratosphere) and tropical tropospheric variability (e.g. the Madden-Julian Oscillation and El Nino), and most of my ongoing research focuses on these phenomena. For example, both polar stratospheric sudden warmings and the Madden-Julian Oscillation have been shown to influence European and Mediterannean weather, but it is unclear (1) what mechanism(s) underlie these connections, (2) how far in advance the impacts can be predicted, and (3) what governs the magnitude of the surface impact. As these processes must be represented by climate and weather models in order to actualize the potential improvement in predictability, and because the observational record of key meteorological quantities is relatively short, I also run models (both idealized and comprehensive) in order to test model fidelity and to isolate key processes. The ultimate goal is to improve the predictions and projections of surface weather and climate.

Exciting, funded opportunities for further research exist in these areas. For more information, please see Opportunities.