An Evaluation of Ensembles Available Within The Community Leveraged Unified Ensemble (CLUE) During The Hazardous Weather Testbed (HWT)

Abstract

Every year, the Hazardous Weather Testbed (HWT) is conducted at the National Severe Storms Laboratory (NSSL) in an effort to assess the latest convection-allowing models (CAMs) and ensembles. Recent coordination of the contributed model output from participating groups around a unified setup (e.g., WRF versions, domain size, vertical levels and spacing, etc.) has been undertaken to create a super-ensemble of over 60 members called the Community Leveraged Unified Ensemble (CLUE). The construction of the CLUE allows for meaningful comparisons among a variety of members to be performed. With a convection-allowing ensemble planned for operational implementation in the near future, it is critical to investigate key scientific questions related to informing the best configuration strategies for producing such an ensemble based on an evidence-driven approach. The Developmental Testbed Center (DTC) has been tasked with evaluating a member of CLUE subsets to answer critical questions related to ensemble design. For example, should model uncertainty be addressed through multiple dynamic cores, multiple physics parameterizations, stochastic physics, or some combination of these? A number of ensemble-based verification measures will be evaluated, including widely-used traditional metrics (spread, skill, error, reliability, etc.) and newer methods that provide additional diagnostic information, especially at higher resolution. These latter approaches will include the Method for Object-based Diagnostic Evaluation (MODE) and neighborhood methods applied to deterministic and probabilistic output (e.g., Fractions Skill Score). Along with standard meteorological fields to highlight overall model performance, an evaluation of severe weather storm-attribute fields readily available in model output or analysis fields (e.g., updraft helicity, radar reflectivity, convective initiation indicators) will also be conducted through a collaboration with NSSL researchers.