UMD AOSC Seminar

*** Special Day, Time, Location ***

On Initial Perturbations for Ensemble Prediction

Professor Earland Källén
Department of Meteorology, Stockholm University, Sweden

To create initial perturbations independent of the current flow situation of the atmosphere, random perturbations are introduced by using the difference between two randomly chosen atmospheric states (i.e. analyses). The method produces dynamically balanced perturbations and we call them Random Field perturbations (RF). These perturbations have the same characteristic spatial structures as the variability of the atmosphere. The RF method is compared with the operational singular vector based ensemble at ECMWF and the Ensemble Transform (ET) method used operationally at NECP. All three perturbation methods have been compared using the ECMWF IFS-model with resolution TL255L40. The properties of the different perturbation methods have been investigated both by comparing the dynamical properties and the quality of the ensembles in terms of different skill scores. The results show that the RF perturbations initially have the same dynamical properties as the variability of the atmosphere. After a day of integration the perturbations from all three methods converge. The skill scores indicate a statistically significant advantage for the RF method for the first 2-3 days for most of the evaluated parameters. For the medium range (3-8 days) the differences are very small. We also discuss the influence of the asymptotic variability of the forecasting model on the ensemble properties.

April 22, 2009, Wedensday
Computer and Space Sciences (CSS) Building, Room 2324

[Contact: Kayo Ide]
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