Tuesday, 9 January 2018: 10:45 AM
Room 6A (ACC) (Austin, Texas)
Aaron Johnson, Univ. of Oklahoma, Norman, OK; and X. Wang
Atmospheric bores can play a critical role in both the maintenance and the initiation of nocturnal convection. Furthermore, bores are very commonly observed in the nocturnal convective environment of the Great Plains of the United States. Therefore improving the understanding and predictions of bores was one of the main foci of the Plains Elevated Convection At Night (PECAN) field experiment. Observations were collected during PECAN from fixed and mobile observation platforms, including in situ surface and upper air observations, and surface and flight based remote sensing profilers of the kinematic and thermodynamic environment within and near bores. These data provide an unprecedented opportunity to understand the physical processes controlling bore behavior and determine optimal observing network strategies to improve predictions of bores in particular, and nocturnal convection in general.
In this study, the multi-scale GSI-based data assimilation system is used to study the systematic impact of assimilating the PECAN observations on predictions of explicitly resolved bores, using 10 bore-focused Intensive Observation Periods (IOPs). In general, predictions of both bore amplitude and bore speed are improved by assimilating the observations. The impact of each individual type of IOP observations is also evaluated through systematic data denial experiments, with a focus on determining optimal observation network strategies for bore prediction. In addition to statistical analysis of these forecast datasets, case studies will be presented to demonstrate qualitative impacts and provide physical reasoning for the results.
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