Figure 1. Line-averaged vertical cross section showing graupel density in the simulated idealized squall line at hour 3 in the simulation using the new variable graupel density parameterization.
Continued investigation of the impact of model microphysics parameterization on short-term forecasts of convective initiation, evolution, and quantitative precipitation forecasts (QPF) was conducted with a squall line case study. The event studied was a squall line observed on 20 June 2007 in central Oklahoma. Idealized simulations of the case had previously shown the parameterization for raindrop breakup to have a strong influence on the evolution of organized convection via its impact on the cold pool (Morrison et al. 2012). Additionally, previous sensitivity tests varied the prescribed graupel density in the Thompson et al. (2008) bulk microphysics scheme, which showed that the cold pool strength and depth is impacted by prescribed graupel density. In FY16, modifications were made to the Thompson microphysics code to allow for a variable graupel density to be diagnosed at every grid point and time step, rather than having the prescribed graupel density remain constant throughout the simulation domain and time period. The variable density scheme was also tested in the squall line simulation and results were presented at the ICCP conference in Manchester, England. The new scheme diagnosed high (hail-like) graupel density in the convective core and low graupel density in the areas farther from the core (Figure 1). This altered the distribution of graupel/hail in the storm and impacted the cold pool.
In order to evaluate impacts on storm structure, QPF, and, in particular, storm evolution, due to changes made to the Thompson microphysics scheme, an object-based evaluation tool that tracks storms with time is needed. The Method for Object-based Diagnostic Evaluation (MODE)-Time Domain (TD) is a tool developed at NCAR for such analysis, however there are several parameters that can be set in order to evaluate storms of a certain spatial scale and intensity. In FY16, various parameter settings for MODE-TD were explored by running the tool on a few test cases from the FY15 STEP-Hydromet summer demonstration to determine the optimal parameter settings and sensitivity of the results to the chosen settings. A key result of this study indicated that the tracking capabilities of the tool need improvement, but that bulk properties of the observed and modeled storms can be compared. This project mentored a SOARS student who participated in the analysis in the summer of 2016.
