Preliminary results from the 2010-2013 case set show an overall underprediction of linear convective modes during the initiation to 0600 UTC time period with both microphysical schemes in the 3 km runs, which agrees with the results of previous studies at similar resolutions. However, the 1 km runs simulate more linear modes, albeit without significant improvement in mean verification score. This score, which uses a weighted scale based on either exact classification match or cellular/linear/non-linear group matches, also showed no significant difference in mean score between the two microphysics schemes. However, scores for the runs utilizing Thompson microphysics varied much more among cases than those utilizing WSM6 microphysics. Additionally, the ensemble was used to generate probabilistic forecasts of convective morphology. Analysis of the Divergence Skill Score (which is based on the Kullback-Leibler Divergence) of these forecasts showed decreasing skill over time compared to the study climatology, with less skill overall compared to a previous study not restricted to nocturnal systems (Carlberg et. al., submitted to Wea. Forecasting, 2017).
Similarly configured WRF runs have begun for several PECAN mesoscale convective system cases. Preliminary results from these cases show similar deficiencies in predicting linear convective modes and a similar decrease of skill in probabilistic forecasts over time. The effects of finer grid spacing are also being explored for the PECAN case set. In the one case simulated with 1km grid spacing so far, a similar improvement has been noted in the depiction of linear modes.