J4.3 Analysis of Relationships in Deep Convection between Super Rapid Scan Geostationary Satellite Derived Cloud Top Outflow, Updrafts and Total Lightning

Tuesday, 24 January 2017: 11:00 AM
612 (Washington State Convention Center )
Jason Apke, University of Alabama, Huntsville, AL; and J. R. Mecikalski, C. P. Jewett, E. W. McCaul Jr., and L. D. Carey

Recent tests with for the geostationary environmental operational satellite (GOES) R series using GOES-14 over the United States have shown that deep convection cloud top flow features unique to supercells can be identified with objective analysis of super rapid scan (1-min; SRS) derived mesoscale atmospheric motion vector (mAMV) algorithms (Apke et al. 2016).  Objective analyses of high-spatial density point-source mAMVs to gridded flow fields allows for the derivation of storm-scale cloud top vertical vorticity (CTV) and horizontal divergence (CTD) over deep convection at a 1-min time scale.   However, non-uniform mAMV fields with transient target detectability can make gridded flow derivation approaches with traditional objective analysis techniques challenging.  Smooth cloud top cirrus and multi-deck cloud scenarios cause target detection problems for traditional mAMV derivation methods, leading to non-uniform, spatially coarse mAMV fields.  Simple Barnes analyses can “Balloon” in areas with low mAMV spatial density, causing large magnitude errors in the derivation of gridded CTD and CTV values.  Since values of CTD over deep convection, through principles of mass conservation, can be related back to updraft strength, better mAMV objective analysis techniques could yield the possibility of identifying updraft strength and size changes occurring within the storm at a 30-sec time scale.  Knowing characteristics of the updraft with a fine temporal resolution in deep convection can be useful when testing relationships between total lightning changes and severe weather formation at the ground (e.g. Schultz et al. 2011).

                Thus, to properly study the relationships between CTD and updraft strength, the mAMV targeting approach is modified to identify targets in smooth cirrus regions.  Furthermore, steps are taken to apply a recursive analysis approach instead of the original Barnes (1973) objective analysis approach used by Apke et al. (2016) to better handle non-uniform point-source mAMVs.  Multiple case studies of supercell and nonsupercell storms will be shown.  Values of the new recursive analysis approach are compared to locations of visible and infrared derived overshooting tops, ground based radar reflectivity, differential reflectivity columns and ground based total lightning data values measured by very high frequency lightning mapping arrays. 

                Preliminary results suggest that SRS derived CTD and total lightning changes are related as values of total lightning changes are theoretically related to changes in updraft volume and strength (Schultz et al. 2015).  Using a recursive analysis with improved target spatial density removes ballooning problems present in the Barnes analysis, and background tropopause level flow from numerical weather prediction data can be effectively combined with measured mAMV products.  Also, CTD can now be used for a number of cases to identify the location of the strongest updraft in a region at a 1-min time scale.  Further exploration into ground based radar data shows that total lightning changes that occur without changes in CTD or vice versa may be due to the microphysics of the storm itself, hence use of combined products from the new Global Lightning Mapper on-board the GOES-R with SRS mAMVs may yield new insights on the internal dynamics (i.e. updraft intensification, broadening, and wet hail growth) and microphysics of mature deep convection with as high as 30-second update rates.   CTD and CTV can also be explored for severe weather forecasting value, such as trends near the occurrence of strong winds, large hail and tornadoes at the ground.

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