1.1 IMPACT OF A STOCHASTIC PERTURBATION SCHEME ON NCEP GLOBAL ENSEMBLE FORECAST SYSTEM Dingchen Hou*, Zoltan Toth, Yuejian Zhu and Weiyu Yang Environmental Modeling Center/NCEP/NOAA, Camp Springs, Maryland 1. INTRODUCTION Effort has been made to represent model uncertainties since 1990s. Toth and Kalnay (1995) deliberately inflate the ensemble perturbations during the integration to increase the ensemble spread. Multi-model and multi-model version approaches are employed in both operational systems (e.g. Houtekamer et al., 1996) and experimental tests (e.g. Stensrud et al. 2000 and Hou et al. 2001). On the other hand, the use of stochastic noise to represent unpredictable small- scale variability, in the form of stochastic physics with the ECMWF ensemble forecast system (Buizza, et al, 1999) and the stochastic backscatter applied to the UK Met Office model (Frederiksen and Davies 1997), appear to have beneficial effect on forecast skills and synoptic variability. Based on these considerations, research is being conducted at EMC/NCEP to develop a practical and effective stochastic parameterization scheme within NCEP’s Global Ensemble Forecasting System (GEFS). The scheme is based on random combinations of the tendencies of the ensemble perturbations and referred as a Stochastic Perturbation Scheme (SPS). The experiments with a simplified version of SPS (Hou, Toth and Zhu 2006, HTZ hereafter) show encouraging results. Since 2006, GEFS has been running under the Earth System Modeling System (ESMF) environment and this makes it possible to employ the scheme in the operations with a more realistic version. This paper presents the results of experiments with SPS at operational environment and discuss the impact of the scheme on the GEFS model output. 2. FORMULATION OF THE SCHEME The general framework with stochastic presentation of model related uncertainties is to add a stochastic forcing term S to the conventional tendency T, for each member i of the ensemble system, i.e., * Corresponding author address: Dingchen Hou, Environmental Modeling Center/NCEP/NOAA,W/NP2 NOAA WWB #207, 5200 Auth Road, Camp Springs MD 20746; email: dingchen.hou@noaa.gov . The stochastic formulation of the ECMWF ensemble system (Buizza et al. 1999) links stochastic forcing S to regions in the atmosphere where conventional subgrid parameterization is active (Palmer, 2001). A different approach is adopted in the current scheme by linking the stochastic forcing term S to the total conventional forcing T (including the grid scale and subgrid scale parameterizations). It is assumed that the conventional tendencies of the ensemble perturbations provide a sample of realizations of the stochastic forcing. Therefore, the S terms are formulated by various combinations of the P vectors, i.e., where i and j are the index denoting the ensemble members and the summation is taken over all N ensemble members j=1, N. With the simplified version of the scheme (HTZ), two approximations are made. Firstly, the scheme is applied every 6 hours and the conventional tendency Ti is approximated by 6h finite differences. Secondly, the combination of the P vectors for a particular member i, is replaced by a single Pj vector randomly selected from the P vectors excluding j=i. While keeping the first approximation, the scheme is improved by randomly combine all of the P vectors. This is realized by a procedure similar to Ensemble Transform (ET) technique but applied to ensemble perturbation tendencies (instead of the ensemble Fig.1 Examples of the temporal variation of the combination coefficients wi,j. N=14 is assumed and shown are the 14 curves for i=14 and j=1 to 14. 0 T T P i i - = j j i j i P w S , ~ Σ X i = T i + S i (1)