Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Derek Hodges, Univ. of Utah, Salt Lake City, UT; and Z. Pu
This study investigates the complicated interactions among mesoscale convective systems (MCS), cold pools (CP), and the low-level jet (LLJ) for a case on 23-24 May 2011 over the Southern Great Plain Region using the mesoscale community Weather Research and Forecasting (WRF) model. The impact of the data assimilation on improving the representation of these interactions in the WRF model is also assessed with the NCAR Data Assimilation and Research Testbed (DART) system. It is found that the numerical simulations of the mesoscale convective case and its interactions with CP and LLJ are sensitive to the microphysics, planetary boundary layer, and land surface parameterizations as well as the grid spacing, initial time, and initial conditions of the model. However, the sensitivity and associated uncertainty are reduced through the data assimilation.
The LLJ modified the MCS and CP it interacted with. Meanwhile, its strength, position, and orientation were also affected by the MCS and CP. In this way, a dynamic feedback can result. Specifically, the LLJ strengthens the MCS through the transport of warm and moist air and convergence, after which the stronger MCS dynamically strengthens the LLJ through latent heat release and lowering pressure through two mechanisms on both the convective and mesoscale. The stronger MCS also strengthens its surface CP. This feedback allowed for a divergence in the simulations for this event based primarily on their strength of the initial dry line convection and associated CP. Data assimilation was used to reduce the uncertainties associated with this convective system that were determined to be the most influential in the model divergence observed. Assimilation of Oklahoma mesonet data improved the representation of surface CPs, while radar data has an influence on the MCS representation. Details will be presented at the conference.
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