Characteristics of Diagnostics for Identifying Elevated Convection over the British Isles in a Convection-Allowing Model

Abstract

Abstract Identifying modes of convection can be useful in both forecasting and research. For example, it allows for potentially different impacts to be determined in forecasting contexts and stratification of model behavior in research contexts. One area where identification could be particularly beneficial is elevated convection. Elevated convection is not routinely examined (outside of an operational environment) within a physical-process perspective in operational numerical weather prediction model evaluation or verification. Using convection-allowing model (CAM) output the characteristics of four elevated convection diagnostics [based on boundary layer, convective available potential energy (CAPE) ratios, downdraft, and inflow layer properties] are examined in operational forecasts during the U.K. Testbed Summer 2021 run at the Met Office. A survey of the practical use of these diagnostics in a simulated operational environment revealed that diagnostics based on CAPE ratios and inflow layer properties were preferred. These diagnostics were the smoothest varying in both space and time. Treating the CAPE ratio and downdraft properties diagnostics as proxies for updrafts and downdrafts, respectively, showed that updrafts were slightly more likely to be resolved than downdrafts. However, a substantial proportion of both are unresolved in current CAMs. Filtering the CAPE ratios by the inflow layer properties led to improved spatial and temporal characteristics, and thus indicates a potentially useful diagnostic for both research and forecasting. Significance Statement Understanding diagnostics is important to be able to analyze model data. Four diagnostics to identify elevated convection are characterized from kilometer-scale operational forecasts. Diagnosing elevated convection from model data is important as these events are often associated with impactful forecast busts. Therefore, being able to identify how the model is representing these events could lead to model improvements. Two diagnostics were deemed to be of practical use based on current kilometer-scale forecasts: convective available potential energy ratios and inflow layer properties. These diagnostics varied smoothly in space and time. The two diagnostics were combined to produce a filtered diagnostic that could be useful in both research and operations.