The Impact of Horizontal Grid Spacing on Convective Morphology and Propagation in Convection-Allowing Simulations of Severe Weather-Producing Convective Systems

Numerous prior studies have shown that certain types of convective morphologies are more likely to produce various types of severe weather, such as bow echoes having an enhanced threat of damaging winds. Because convection-allowing grid spacing is now often used in some operational numerical weather prediction models, realistic convective morphologies often appear in these forecasts. Although these convective morphologies on some occasions match what ends up being observed, some recent studies have found major shortcomings in forecasts of some modes, especially bow echoes and squall lines. The incorrect depiction of mode can complicate forecasts of severe weather.

In the present study, output from the Advanced Research WRF (WRF-ARW) model for severe weather-producing convective events from both a sample of 14 nocturnal convective system events from 2010 to 2013 where the low-level jet (LLJ) was present with weak synoptic forcing, and five additional cases from the 2015 Plains Elevated Convection At Night (PECAN) field experiment, is examined to understand the impact on predictability of convective morphology when horizontal grid spacing is changed from 3 km to 1 km. A 10-category morphology classification scheme is used. For the 14 cases, a six-member ensemble was run at 3 km horizontal grid spacing utilizing two different microphysical schemes (Thompson and WSM6) and three different planetary boundary layer schemes (YSU, MYJ, MYNN). A subset of 10 of these runs was conducted at 1 km horizontal grid spacing to allow for investigation into the effects of refined resolution.

Results for the full sample of cases show an overall underprediction of linear convective modes 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 although still not enough, albeit without significant improvement in the mean morphology verification score originally used in Snively and Gallus (Wea. Forecasting, 2014). 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. This result implies that perhaps better resolution of strong upward motion along the cold pool boundaries in the 1 km runs allowed for more continuous regions of intense convection, but timing errors, errors in depiction of stratiform rain regions, or inability to distinguish between cases where linear systems occurred or did not occur remained problems. Scores for the runs utilizing Thompson microphysics varied much more among cases than those utilizing WSM6 microphysics. In addition, the Thompson scheme resulted in more extensive stratiform regions.

In addition, for a different sample of 14 cases, special attention was focused on how propagation speed and cold pool characteristics change as grid spacing is refined from 3 to 1 km. For some of these cases, an additional run was performed using 0.33 km horizontal grid spacing to determine if trends present as resolution is refined from 3 km to 1 km continue down to 0.33 km. Preliminary results suggest a convergence in such features as reflectivity patterns and cold pool characteristics once grid spacing reaches 1 km (there is less change for a refinement down to 0.33 km), but features potentially important for severe weather in QLCS events such as strong mesovortices within the leading line of intense reflectivity become much more pronounced for 0.33 km grid spacing.