Maintaining Realistic Uncertainty in Model and Forecast

Our long term goal is to better understand ensemble forecasting in general and the dynamics of initial uncertainty given only imperfect models in particular; we are most interested in the practical application to a real physical system, rather than toy examples where the model error is known a priori. Of particular interest to us are methods which aim to evaluate predictions of high dimensional systems like the atmosphere, methods to best combine different models, and determination of aims which are both achievable by the forecaster and useful for the user.