Diagnosing sensitivities to microphysics parameterizations in convection-allowing models using object-based time-domain diagnostics

Until recently, object-based verification approaches have been limited to diagnosing aspects of two-dimensional spatial objects. However, recent work using the Method for Object-based Diagnostic Evaluation (MODE) – a component of the Developmental Testbed Center's Model Evaluation Tools - has incorporated a third dimension: time. Thus, “time-domain objects” are considered contiguous regions of grid-points encompassing both space and time. Incorporating time makes MODE a much more powerful diagnostic tool that provides important information to forecasters and model developers on aspects of phenomena like timing, evolution, and translation speed, which would not be available by considering the spatial dimensions alone.

In this study, a beta version of MODE time-domain (MODE-TD) is used to diagnose sensitivities to microphysics parameterizations in 4-km grid-spacing, CONUS domain, WRF model simulations run by the Center for Analysis and Prediction of Storms and used for the 2010 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment. Additionally, the capabilities of another time-domain object-based algorithm independently developed by the lead author are tested. During the 2010 experiment, four WRF model runs with 30 hour forecast lengths were identically configured except for their microphysics parameterizations that included WDM6, WSM6, Morrison, and Thompson schemes. The time-domain object algorithms are applied to 1 hour accumulated forecast and observed precipitation with emphases placed on quantifying differences in translation speed, evolution, and timing of precipitation systems.