Tuesday, 9 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Accurately simulating cold pool structure and intensity could improve MCS forecasts as an MCS’s forward motion is driven primarily by the leading near-ground buoyancy gradient caused by the cold pool (especially in cases with weak synoptic environmental forcing). Two MCS-driven cold pools were simulated at 3-, 1-, and .333-km horizontal grid spacing, with cold pool intensity and depth error analyses performed using METAR data, PECAN upper-air soundings and surface mesonet observations as verification. Compositing techniques were employed to mitigate the impact of simulation displacement errors, while time-to-space conversion was applied to METAR observations to best resolve fine-scale features within and near the MCS and cold pool evolution. Contour frequency by altitude and distance diagrams were employed to simplify and display the 3D spatial statistical characteristics of simulated cold pool structures between the model output at varying horizontal grid-spacings. Finally, microphysical analyses were conducted to explain the differences in MCS forward propagation speed, magnitude, and structure, via an evaluation of water vapor, rain water, cloud water, and graupel mixing ratio evolutions, with associated hydrometeor phase change and diabatic heating/cooling tendencies.
Very preliminary results show that finer grid spacing better resolves microphysical processes, allowing for the development of narrower, but stronger updrafts and downdrafts and in turn, higher amounts of rain water and graupel mixing ratios. MCS cold pools in finer grid spaced simulations become deeper, colder in magnitude, and more expansive in association with a faster forward propagation speed due to the better resolving of a narrower, but stronger buoyancy gradient not present in coarser simulations. This finer, stronger buoyancy gradient generated at the leading edge of the stronger cold pools in finer simulations originate from greater microphysical cooling associated with more evaporation of rainwater and sublimation of graupel. The higher rain water mixing ratios are generated in finer simulations by greater amounts of melting graupel and better efficiency in cloud water and graupel collection processes.
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