Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) single-moment 6-class (WSM6) microphysics scheme in the Advanced Research WRF (WRF-ARW) produces less upper-level ice clouds within synthetic images compared to observations. Synthetic Geostationary Operational Environmental Satellite-13 (GOES-13) imagery at 10.7mm of simulated cloud fields from the 4-km National Severe Storms Laboratory (NSSL) WRFARW is compared to observed GOES-13 imagery. Histograms suggest that too few points contain upper-level simulated ice clouds. In particular, side-by-side examples are shown of synthetic and observed anvils. Such images illustrate the lack of anvil cloud associated with convection produced by the 4-km NSSL WRF-ARW. A vertical profile of simulated hydrometeors suggests that too much cloud water mass may be converted into graupel mass, effectively reducing the main source of ice mass in a simulated anvil. Further, excessive accretion of ice by snow removes ice from an anvil by precipitation settling. Idealized sensitivity tests reveal that a 50% reduction of the accretion rate of ice by snow results in a significant increase in anvil ice of a simulated storm. Such results provide guidance as to which conversions could be reformulated, in a more physical manner, to increase simulated ice mass in the upper troposphere. Results from initial tests received positive feedback from forecasters. In particular, forecasters were encouraged by the ability of simulations to depict reasonable convective-scale structures associated with phenomena like mesoscale convective systems and discrete supercells. Consequently, NSSL scientists were motivated to establish a more permanent experimental modeling framework that provided storm-scale guidance to SPC forecasters.
CITATION STYLE
Stano, G., Schultz, C., Carey, L., MacGorman, D., & Calhoun, K. (2014). Total lightning observations and tools for the 20 May 2013 Moore, Oklahoma, tornadic supercell. Journal of Operational Meteorology, 2(7), 71–88. https://doi.org/10.15191/nwajom.2014.0207
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