The system uses a computationally inexpensive Ensemble Transform (ET) method for generating high resolution initial perturbations for regional ensemble forecasts. The method provides initial perturbations that (a) have an initial variance consistent with the best available estimates of initial condition error variance, (b) are dynamically conditioned by a process similar to that used in the breeding technique, (c) add to zero at the initial time, (d) are quasi-orthogonal and equally likely, and (e) partially respect mesoscale balance constraints by ensuring that each initial perturbation is a linear sum of forecast perturbations from the preceding forecast. Results indicate that the ET technique dynamically selects growing perturbations that are consistent with user provided estimates of analysis error variance. In addition, ET ensembles show skillful means and useful spread-skill relationships. Results will be shown for ensemble forecasts over an extensive period (1-6 months) for two areas: (1) the JME domain (45- and 15-km resolution) centered over Korea, and (2) the RIMPAC domain (45-, 15-, and 5-km) centered over Hawaii.
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