An ensemble of runs is being performed using two types of mesoscale adjustment to the initialization and two different convective parameterizations, the operational Betts-Miller Janjic scheme, and the Kain-Fritsch scheme. A cold pool initialization procedure developed by David Stensrud is used for some of the ensemble members, with variations in the assumed cold pool layer humidity. For other ensemble members, the model's vertical diffusion is used to adjust lower tropospheric temperature and moisture values input from mesonetwork surface observations.
Preliminary results suggest that no single technique consistently improves the QPF for these heavy rain events. Both techniques, however, do improve the forecasts over short time periods within some cases. Some evidence suggests that the mesoscale modifications have the greatest ability to improve the forecast when low-level flow is relatively weak. The cold pool adjustment may offer the greatest benefit when the Kain-Fritsch scheme is used, since that scheme includes a convective downdraft which can sustain the cold pool over a longer period in the simulation.
The mixed results obtained with the various initialization improvements suggest that ensemble guidance may be of more value to forecasters in these situations. Some discussion will be given on probability forecasts derived from the ensembles.
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