Examining Deep Convective Cloud Evolution Using Total Lightning, WSR-88D, and GOES-14 Super Rapid Scan Datasets*

AbstractThe Geostationary Operational Environmental Satellite-14 (GOES-14) Imager operated in 1-min Super Rapid Scan Operations for GOES-R (SRSOR) mode during summer and fall of 2012 to emulate the high temporal resolution sampling of the GOES-R Advanced Baseline Imager (ABI). The current GOES operational scan interval is 15–30 min, which is too coarse to capture details important for severe convective storm forecasting including 1) when indicators of a severe storm such as rapid cloud-top cooling, overshooting tops, and above-anvil cirrus plumes first appear; 2) how satellite-observed cloud tops truly evolve over time; and 3) how satellite cloud-top observations compare with radar and lightning observations at high temporal resolution. In this paper, SRSOR data, radar, and lightning observations are used to analyze five convective storms, four of which were severe, to address these uncertainties. GOES cloud-top cooling, increased lightning flash rates, and peak precipitation echo tops often preceded seve...

[1]  Kenneth L. Cummins,et al.  A Combined TOA/MDF Technology Upgrade of the U.S. National Lightning Detection Network , 1998 .

[2]  Harold E. Brooks,et al.  An Objective High-Resolution Hail Climatology of the Contiguous United States , 2012 .

[3]  Richard E. Orville,et al.  Development of the National Lightning Detection Network , 2008 .

[4]  Timothy J. Schmit,et al.  Rapid Refresh Information of Significant Events: Preparing Users for the Next Generation of Geostationary Operational Satellites , 2015 .

[5]  K. Bedka,et al.  MATURE CONVECTIVE STORMS AND THEIR OVERSHOOTING TOPS OVER CENTRAL EUROPE – OVERSHOOTING TOP HEIGHT ANALYSIS FOR SUMMERS 2009-2011 , 2012 .

[6]  John L. Cintineo,et al.  Evolution of Severe and Nonsevere Convection Inferred from GOES-Derived Cloud Properties , 2013 .

[7]  Jeffrey C. Dobur.  A COMPARISON OF SEVERE THUNDERSTORM WARNING VERIFICATION STATISTICS AND POPULATION DENSITY WITHIN THE NWS ATLANTA COUNTY WARNING AREA , 2005 .

[8]  R. Dworak,et al.  Comparison between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports , 2010 .

[9]  K. Cummins,et al.  Combined Satellite- and Surface-Based Estimation of the Intracloud Cloud-to-Ground Lightning Ratio over the Continental United States , 2001 .

[10]  Eric C. Bruning,et al.  Theory and Observations of Controls on Lightning Flash Size Spectra , 2013 .

[11]  Christopher J. Schultz,et al.  Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather , 2009 .

[12]  Christopher J. Schultz,et al.  Lightning and Severe Weather: A Comparison between Total and Cloud-to-Ground Lightning Trends , 2011 .

[13]  Robert M. Rabin,et al.  A Quantitative Analysis of the Enhanced-V Feature in Relation to Severe Weather , 2007 .

[14]  Jeffrey C. Bailey,et al.  A Flash Clustering Algorithm for North Alabama Lightning Mapping Array Data , 2005 .

[15]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[16]  W. Paul Menzel,et al.  INTRODUCING THE NEXT-GENERATION ADVANCED BASELINE IMAGER ON GOES-R , 2005 .

[17]  A. F. Hasler,et al.  Automatic Analysis of Stereoscopic Satellite Image Pairs for Determination of Cloud-Top Height and Structure , 1991 .

[18]  William J. Koshak,et al.  The GOES-R GeoStationary Lightning Mapper (GLM) , 2012 .

[19]  Travis M. Smith,et al.  Data Mining Storm Attributes from Spatial Grids , 2009 .

[20]  Donald W. Hillger,et al.  First-Light Imagery from Suomi NPP VIIRS , 2013 .

[21]  Richard E. Orville,et al.  The relationship between lightning type and convective state of thunderclouds , 1989 .

[22]  David A. Santek,et al.  McIDAS-V: a powerful data analysis and visualization tool for multi and hyperspectral environmental satellite data , 2008, Optical Engineering + Applications.

[23]  A. Witt,et al.  An Enhanced Hail Detection Algorithm for the WSR-88D , 1998 .

[24]  J. Otkin,et al.  Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients , 2010 .

[25]  Vincenzo Levizzani,et al.  Multispectral, high-resolution satellite observations of plumes on top of convective storms , 1996 .

[26]  Lawrence D. Carey,et al.  A Comparison of Two Ground-Based Lightning Detection Networks against the Satellite-Based Lightning Imaging Sensor (LIS) , 2014 .

[27]  John T. Young,et al.  The Man computer Interactive Data Access System: 25 Years of Interactive Processing , 1999 .

[28]  Daniel J. Cecil,et al.  Passive Microwave Brightness Temperatures as Proxies for Hailstorms , 2009 .

[29]  S. Goodman,et al.  Forecasting Lightning Threat Using Cloud-Resolving Model Simulations , 2009 .

[30]  D. McCann.  The Enhanced-V: A Satellite Observable Severe Storm Signature , 1983 .

[31]  Richard J. Blakeslee,et al.  Lightning Imaging Sensor (LIS) for the Earth Observing System , 1992 .

[32]  Robert M. Rabin,et al.  Satellite-observed cold-ring-shaped features atop deep convective clouds , 2010 .

[33]  Donald W. Burgess,et al.  Lightning Rates Relative to Tornadic Storm Evolution on 22 May 1981 , 1989 .

[34]  John M. Hall,et al.  The North Alabama Lightning Mapping Array: Recent Severe Storm Observations and Future Prospects , 2005 .