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 when they open up windows of opportunity. 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.
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). For example, both polar stratospheric sudden warmings and the Madden-Julian Oscillation have been shown to influence European and Mediterranean weather, but it is unclear (1) what mechanism(s) underlie these connections, (2) how far in advance the impacts can be predicted, (3) what governs the magnitude of the surface impact, and (4) how well models capture these connections. This talk will review progress made towards addressing these issues over the past several years in my group.
