368 Combining GOES Super Rapid Scan Satellite Data, Radar Fields and Total Lightning Observations to Gain Understanding of In-cloud Processes Related to the Occurrence of Lightning in a Thunderstorm

Monday, 11 January 2016
Jason Apke, University of Alabama, Huntsville, AL; and J. R. Mecikalski, C. P. Jewett, X. Li, and L. D. Carey

A main unknown in the analysis of convective clouds in various observational datasets is gaining an understanding for processes occurring in regions of the clouds that cannot be observed routinely. Specifically, geostationary satellites observe cloud tops, while radar and lightning sensors collect information where precipitation and lightning exist, respectively. Cloud-top derived flows, such as cloud-top divergence, vorticity and growth rates, provide indirect indicators for processes occurring below about ~100 m of cloud top. A key science question is how does one use existing datasets such that merged algorithms can be developed, in this case, to increase our understanding on processes leading to the first occurrence of lightning (and near-term lightning trends) in convective storms.

Application of derived wind and storm kinematic information from super rapid scan operations (SRSOR) for the geostationary satellite (GOES)-R series data are explored in this study in the context of total lightning network fields. New algorithms, such as SRSOR derived flow fields and 1-minute initial cloud updraft buoyancy analyses, are combined with total lightning data and examined for potential data fusion capabilities toward addressing the stated questions. Data are collected from the 2014 and 2015 SRSOR collection periods in May and August.

For this research convective storm case studies have and will be selected given proximity to ground based very high frequency total lightning mapping arrays, such as the networks available in northern Colorado (COLMA), western Texas (WTLMA), northern Alabama (NALMA) and Washington DC (DCLMA). In addition to total lightning data, next generation dual-polarization radar (NEXRAD-DP) fields are analyzed for concurrent hydrometeor characteristics within the storms of interest. Use of lightning data provides different means of tracking convection through flash extent density. When combined with variables such as SRSOR cloud top divergence (CTD), we find evidence that increases in lightning flash rates, also termed lightning “jumps”, and updraft intensification (surges in CTD maximum values), are correlated. Furthermore, it has been found that locations of maximum CTD values occur downstream of lightning flash initiation point cluster centroids during weak updraft periods. When the updraft strength increases, CTD maximum locations are closer to flash density centroids, suggesting a more vertical structure to storms examined. Lightning holes, which are commonly associated with the updraft location, are also located close to the CTD maxima when the phenomena are apparent. Values of both are compared to reports of severe weather on the ground. Results of initial flash height will also be shown for specific case events with respect to a 1-minute brightness temperature buoyancy change analysis at the cloud top upon initial ascent. Lastly, the broader operational aspect of this research will involve combining total lightning and values of SRSOR divergence, which will likely translate to new products developed with the GLM instrument on GOES-R with an effort towards an improved microphysical understanding of the dynamics of deep convection, and improving forecast warning capability.

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