WCD-32. Impact of ensemble design in the Rapid Refresh Forecast System using time lagging and stochastic perturbations

Abstract
As NOAA transitions to the Unified Forecast System (UFS), development has begun on a future convective-allowing Rapid Refresh Forecast System (RRFS) ensemble that uses a single dynamic core (dycore) and will eventually use a single physics suite. The intent is for this system to replace the High Resolution Ensemble Forecast (HREFv3), which is NOAA’s current operational convective-allowing, ensemble forecast system and is (unlike the RRFS) a multi-dycore and multi-physics ensemble. To account for model uncertainties, it is important that an ensemble system sample enough of the space of possible outcomes and thus provide adequate forecast spread. Although the HREFv3 provides enough spread, due to its multi-dycore and multi-physics nature its members tend to cluster by dycore/physics pairing, resulting in multi-modal statistics. An ensemble based on a single dycore and single physics suite can remedy this problem, but such ensembles tend to lack sufficient spread. In this work, we present the design of an ensemble system using time-lagging in addition to stochastic initial/boundary condition and physics perturbations to evaluate their potential to provide sufficient spread to account for all forecast error. Our analysis uses output from the RRFS prototype run during the 2021 Hazardous Weather Testbed (HWT) Spring Forecasting Experiment (SFE) in May and June 2021 and retrospective runs of the UFS Short Range Weather (SRW) App. We assess the impact of stochastic perturbations and time-lagging on selected cases, including comparisons of variability between members within the experiment, focusing on qualitative evaluations of storm mode, structure, intensity, and convective evolution, and on quantitative assessments of ensemble-based and neighborhood probabilistic metrics using the enhanced Model Evaluation Tools (METplus) verification framework.