Abstract
This study investigates impacts on convection-permitting ensemble forecast performance of different methods of generating the ensemble IC perturbations in the context of simultaneous physics diversity among the ensemble members. A total of 10 convectively active cases are selected for a systematic comparison of different methods of perturbing IC perturbations in 10-member convection-permitting ensembles, both with and without physics diversity. These IC perturbation methods include simple downscaling of coarse perturbations from a global model (LARGE), perturbations generated with ensemble data assimilation directly on the multiscale domain (MULTI), and perturbations generated using each method with small scales filtered out as a control. MULTI was found to be significantly more skillful than LARGE at early lead times in all ensemble physics configurations, with the advantage of MULTI gradually decreasing with increasing forecast lead time. The advantage of MULTI, relative to LARGE, was reduced but not eliminated by the presence of physics diversity because of the extra ensemble spread that the physics diversity provided. The advantage of MULTI, relative to LARGE, was also reduced by filtering the IC perturbations to a commonly resolved spatial scale in both ensembles, which highlights the importance of flow-dependent small-scale (<~10 m) IC perturbations in the ensemble design. The importance of the physics diversity, relative to the IC perturbation method, depended on the spatial scale of interest, forecast lead time, and the meteorological characteristics of the forecast case. Such meteorological characteristics include the strength of synoptic-scale forcing, the role of cold pool interactions, and the occurrence of convective initiation or dissipation.
A cold pool perturbation scheme to improve convective initiation in convection‐permitting models
