J1.7
Towards nonlinear probabilistic prediction
Joseph Tribbia, NCAR, Boulder, CO; and D. Baumhefner and R. Errico
Over the past several years, operational weather centers have initiated ensemble prediction techniques to estimate the skill of forecasts at the medium range. The ensemble techniques used are based on linear methods. The theory behind this method is developed and this technique is shown to be a useful indicator of skill in the linear range where forecast errors are small relative to climatological variance. While this advance has been impressive, to be of utility in the nonlinear range an ensemble prediction method must be capable of giving probabilistic information for the situation where a probability density forecast becomes multi-modal. Two prototypical examples of prediction problems where nonlinearity and the resultant multi-modality is likely to be of paramount import are medium range prediction of planetary-wave regime transitions and short range prediction of precipitation. The current skill in forecasting regime transitions and wintertime precipitation and the prospects for the development of refined ensemble methods for future probabilistic forecasting of these ubiquitous features of atmospheric variability will be examined.
Joint Session 1, Ensemble forecasting and predicability (Joint with the Symposium on Observations, Data Assimilation, and Probabilistic Prediction and 16th Conference on Probability and Statistics in the Atmospheric Science)
Tuesday, 15 January 2002, 8:30 AM-2:00 PM
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