16B.6 Climatology of near-storm environments with convective modes for significant severe thunderstorms in the contiguous United States Richard L. Thompson*, Bryan T. Smith, Jeremy S. Grams, Andrew R. Dean, and Chris Broyles Storm Prediction Center Norman, OK 1. Introduction cataloged a larger number of convective mode cases than the prior proximity sounding work such Proximity soundings have a long history of use in as T07 and Davies and Fischer (2009), yet they identifying the characteristics of severe storm did not consider environmental information. environments, dating back to the 1940s Thompson et al. (2008) combined a simplified (Showalter and Fulks 1943) and 1950s (e.g., convective mode classification scheme with RUC Fawbush and Miller 1954; Beebe 1955, 1958). model and the Storm Prediction Center (SPC) This early work has continued into the past two mesoanalysis environmental information to decades when additional proximity sounding examine near-storm convective parameters in samples were constructed by Johns et al. (1993), comparison to established severe weather Rasmussen and Blanchard (1998; hereafter “checklist” variables dating back to the 1950s. RB98), Rasmussen (2003), and Craven and Brooks (2004; hereafter CB04). These studies In Part I of this study, Smith et al. (2010, this either relied on implicit assumptions (e.g., volume; hereafter S10) documents the supercells produced all ≥ 2 inch diameter hail in development of a large (17037) sample of RB98), or large sample sizes but no explicit convective mode cases associated with information regarding storm type (CB04). More tornadoes, ≥ 2 inch hail (hereafter sighail), and 65 recent work by Thompson et al. (2003; hereafter kt or greater convective wind gusts (hereafter T03), Thompson et al. (2007; hereafter T07), sigwind) across the continental United States. Davies (2004), and Davies and Fischer (2009) Please refer to S10 for additional details regarding used hourly Rapid Update Cycle (RUC) model the classification scheme. Building on the work of (Benjamin et al. 2004) analysis profiles to S10, we have included near-storm environmental represent the near-storm environment associated information associated with each severe storm with radar-identified supercells and other storm and convective mode case. The ultimate goal of types. These studies provided valuable this work is to provide a representative sample of information regarding storm environment, severe storm events and associated convective especially with respect to supercells and tornado modes and environmental information. production, yet they focused on specific events or Environmental information can be combined with storm modes, and the sample sizes were too small severe storm mode information to improve the to make any definitive statements regarding the diagnoses and short term forecasts of tornadoes frequency of occurrence of different storm modes. and other significant severe thunderstorm events. In the following section we detail our methodology Trapp et al. (2005) developed a relatively large and data collection, and in section 3 we present an sample of convective modes associated with analysis of convective modes and environmental tornadoes from 1999-2001 across the contiguous information focusing on tornadoes. Section 4 United States, using regional radar reflectivity summarizes our findings and outlines continuing mosaics of relatively coarse spatial and temporal and future work related to the SPC convective resolution. Somewhat more detailed convective database. mode categorizations were documented by Gallus et al. (2008) for a 10 state region in the summer, 2. Data and methodology and this was followed by Duda and Gallus (2010) for the same region, with the addition of an All tornado, sighail and sigwind reports for the estimate of supercell occurrence. These studies period 2003-2009 were filtered for the largest magnitude report per hour on a 40 x 40 km RUC *Corresponding author address: Richard L. Thompson, model analysis grid (Benjamin et al. 2004), and NOAA/NWS/NCEP/Storm Prediction Center, 120 David the time filtering assigns each report to the closest L. Boren Blvd., Suite 2300, Norman, OK 73072. prior analysis hour. This filtering procedure [email protected] produced a sample of 17037 severe thunderstorm 1 grid-hour events, including 8176 tornadoes, 3361 analysis of the actual surface observations using sighail, and 5500 sigwind events. The hourly RUC the RUC analysis as a first guess field. The result analysis grids form the foundation of the SPC is an hourly surface analysis that attempts to hourly mesoanalyses (Bothwell et al. 2002), where remove RUC biases at the surface. hundreds of sounding-derived parameters are calculated at each analysis grid point. The RUC The SPC mesoanalysis approach does not correct analyses at the lowest model level are used as a for all potential errors. Given the propensity for first-guess field in an objective analysis of the severe thunderstorms to occur in the vicinity of hourly surface observations, but no further baroclinic zones with strong horizontal gradients of modification of the model profiles is attempted. An temperature, moisture, and wind, small phase archive of a subset of these convective errors can result in somewhat misleading parameters (e.g., Schneider and Dean 2008) is information for a particular storm case (i.e., a maintained at the SPC, and these data provide the tornado occurs at 00:45 after an hour, but a warm basis for the analyses herein. front does not reach the same grid point until shortly after the top of the next hour). In other The basic convective modes identified were cases, the background RUC analyses aloft may be supercells (both right-moving (RM) and left-moving questionable. The Greensburg, KS EF5 tornado (LM) supercells), quasi-linear convective systems case provides a specific example of this type of (QLCS), and disorganized cells or clusters. Two problem. The nearest RUC grid point profiles additional subsets included storms with marginal were apparently too dry just above the surface, supercell characteristics (after T03), and a linear and this strongly impacted parameters such as the hybrid mode with mixed characteristics of both RM lowest 100 mb mean-layer CAPE (MLCAPE) in a line and QLCS (see S10 for a more detailed compared to the surface-based (SB) parcel discussion regarding the practical difficulties of counterpart (e.g., MLCAPE of 883 J kg-1 versus convective mode categorization). The derived SBCAPE of 3487 J kg-1). Though we have made parameters from the SPC mesoanalysis system no attempt to correct any individual errors, the were determined for each severe weather report operational experience of the authors and the prior and convective mode, forming the equivalent of a work by T03 suggests that a large sample size large close proximity sounding relational database should minimize the impact of outliers within the for known storm types and severe weather events. sample. a. Data accuracy and representativeness 3. Results and discussion As with any attempt at assigning single point All of the tornado cases were sorted initially by variables to represent a storm environment, convective mode in order to provide an overview concerns regarding the accuracy and of environmental conditions related to each representativeness of the data must be convective mode type. While a full spectrum of considered. Brooks et al. (1994) discussed many convective modes was documented, a majority of of the concerns with arriving at “proximity” for a the Schneider and Dean (2008) data are related storm environment, while Potvin et al. (2010) primarily to supercells and tornadoes. Thus, our considered the impacts of varying proximity main focus concerns tornado and significant criteria. Compared to rawinsonde observations, tornado (e.g., ≥ F2 damage; hereafter sigtor) the SPC mesoanalysis system has the advantage production with RM, and a comparison of the of producing hourly environmental information on supercell-related parameters to other convective a 40 x 40 km grid, which provides much greater mode environments. spatial and temporal resolution than the observed sounding network. The background RUC We employed an ingredients-based approach analyses incorporate a wide range of synoptic (Johns and Doswell 1992) in our evaluation of the (e.g., standard 00/12 UTC rawinsonde storm environments, but it is important to observations) and asynoptic data (e.g., surface understand the limitations of convective mesonet data, aircraft observations, etc.) to parameters and indices (Doswell and Schultz provide a reasonably accurate depiction of the 2006) since they comprise the majority of our synoptic and mesoscale environment. The most database. The individual parameters can be consistent biases noted by T03 in the RUC profiles grouped into measures of vertical wind shear, were near the ground, where the SPC such as 0-1 km storm-relative helicity (SRH, mesoanalysis system performs an objective Davies-Jones et al. 1990; using the storm motion 2 estimate described by Bunkers et al. 2000) and 0- (e.g., EBWD > 30-40 kt per Fig. 3 and T07), while 6 km bulk wind difference (e.g., RB98 and T03 a gradual transition to weaker vertical shear among others), as well as thermodynamic occurs from the QLCS to marginal RM and parameters such as MLCAPE using the virtual disorganized storms. Combining the ingredients temperature correction described in Doswell and into the SCP reveals a similar decrease in values Rasmussen (1994), and