Thursday, 26 January 2017: 2:30 PM
Conference Center: Tahoma 4 (Washington State Convention Center )
Logan C. Dawson, Purdue University, West Lafayette, IN; and
R. J. Trapp, G. S. Romine, and M. E. Baldwin
Two objectives from the Mesoscale Predictability Experiment (MPEX) were to observe and quantify upscale feedbacks from deep convection and assess the impact of these feedbacks on numerical model simulations. As expected, upper air soundings collected during MPEX indicated surface cold pools are an effect of deep convection on the mesoscale environment that may persist for extended time periods. Arguably, because of the potential for cold pools to persist and significantly contribute to inhibition of surface-based convection, appropriate representation of these cold pools is necessary for accurate prediction of severe convection occurring in multiday episodes.
Experiments utilizing the WRF-DART data assimilation system are conducted to examine this hypothesized relationship between cold pools and subsequent mesoscale-convective predictability. Ensembles for each data assimilation experiment are initialized at 15 UTC using NCAR ensemble data assimilation system analyses. Assimilation cycling occurs from 16 UTC to 03 UTC before launching forecasts. In these experiments, conventional observations and radar reflectivity data are assimilated onto a 3 km convection-permitting domain. Moreover, suppression of convection will be attempted by assimilating radar reflectivity data that have been edited to remove convective storms. Aspects of the mesoscale environment will be verified with a focus on the supplemental MPEX observations, and characteristics of severe convection will be verified using conventional observations and radar data.
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