Spatiotemporal Behavior of the TIGGE Medium-Range Ensemble Forecasts

Abstract

sing the recently developed mean?variance of logarithms (MVL) diagram, together with The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive of medium-range ensemble forecasts from nine different centers, an analysis is presented of the spatiotemporal dynamics of their perturbations, showing how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. In particular, a divide is seen between ensembles based on singular vectors or empirical orthogonal functions, and those based on bred vector, ensemble transform with rescaling, or ensemble Kalman filter techniques.Consideration is also given to the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. Finally, the use of the MVL technique to assist in selecting models for inclusion in a multimodel ensemble is discussed, and an experiment suggested to test its potential in this context.