9.6 NONSUPERCELL TROPICAL CYCLONE TORNADOES: DOCUMENTATION, CLASSIFICATION AND UNCERTAINTIES Roger Edwards*, Andrew R. Dean, Richard L. Thompson and Bryan T. Smith Storm Prediction Center, Norman, OK 1. INTRODUCTION and BACKGROUND expands upon E12 findings via analyses specific to NSTC tornadoes. Section 2 discusses the An ingredients-based approach (e.g., Johns and compilation of NSTC tornado records and potential Doswell 1992) is used in the operational prediction of sources for error, their occurrence tornado threat, regardless of whether the favorable relative to supercell tornadoes, and various measures environment results from midlatitude or tropical of the spatial and temporal distribution of NSTC perturbations. Since the majority of tropical cyclone events. Section 3 offers distributive and (TC) tornadoes are associated with supercells environmental analyses of NSTC tornado events. (Edwards et al. 2012a; hereafter E12), the forecaster Section 4 encapsulates our findings and presents typically can focus on the same ingredients known to discussion and recommendations. favor midlatitude supercells—moisture, instability, (sources for) lift, and vertical wind shear. As in 2. DATA and CLASSIFICATIONS midlatitude settings (e.g., Markowski et al. 1998; Garner 2012), supercellular tornado potential may be a. Tornado data and filtering focused further by the presence of baroclinic and/or kinematic boundaries within the TC envelope For E12 and herein, all TC tornado events (Edwards and Pietrycha 2006). examined were taken from the Storm Prediction Center’s tropical cyclone tornado dataset (TCTOR; Still, TCs present a unique forecast setting for Edwards 2010). Although TCTOR spans the era of supercell tornadoes, in that they represent a full WSR-88D deployment within ~500 km of the physically distinct, spiral form of mesoscale Atlantic and Gulf coasts (1995–2011 as of this convective system (MCS) with specific environmental writing), gridded mesoscale environmental information characteristics (Edwards 2012). In a TC, the relative used in Thompson et al. (2012), E12 and in section 3 prevalence of the favorable ingredients for supercells is available only from 2003 onward. As such, TC is weighted heavily toward moisture and low-level tornado data came from that subset of TCTOR vertical shear, each of which are usually abundant but spanning 2003–2011. still can be nonuniform (e.g., McCaul 1991; Curtis 2004; E12). In contrast, indicators of instability (lapse The TCTOR data then were filtered on a gridded rates) and buoyancy (CAPE) may be either weak basis, as described in detail in Smith et al. (2012; throughout or distributed with pronounced asymmetry hereafter S12). To summarize, it is not whole-tornado away from center—typically downshear with respect data. Instead, the 826 TCTOR records from 2003– to ambient midlatitude flow aloft (McCaul 1991; 2011 were segmented by county. Each filtered Verbout et al. 2007; Molinari and Vollaro 2010; E12). tornado record consists of the county-segment rated Boundaries can be well-defined or relatively subtle highest on the Fujita or enhanced Fujita (EF) damage (Edwards and Pietrycha 2006; Green et al. 2011). scale (Doswell et al. 2009; Edwards et al. 2012b), in a Cumulative juxtaposition of those favorable foci yields 40-km grid square, within a whole environmental- a pronounced climatological tendency for TC analysis hour (section 2c). For example, if a tornado tornadoes to occur generally north through southeast occurred over portions of two counties inside one grid of center (e.g., Schultz and Cecil 2009, Edwards box—one segment rated EF0, the other EF1—the 2012). start time and location of the EF1 segment were used. Any less-damaging tornado segments in the same Some TC tornadoes, however, are not associated hour and grid box were removed, even if occurring with identifiable supercells, even in mesoscale with separate whole-tornado paths. This process environments that favor storm-scale rotation (E12 and distilled 730 filtered tornado records, hereafter section 3). Those are classified herein as non- deemed “tornadoes” or “events” for brevity. supercell TC (NSTC) tornadoes, as in E12. Nonsupercell tornadoes in non-TC settings have been b. Convective mode via radar studied for over two decades (e.g., Wakimoto and Wilson 1989), but not explicitly examined in TCs until Further segregation of tornadic convection into E12 and this more detailed work. We summarize and supercell, marginal supercell and nonsupercell bins _________________________ was accomplished via examination of archived, * Corresponding author address: Roger Edwards, volumetric radar reflectivity and velocity imagery for Storm Prediction Center, National Weather Center, each event, based on the convective-mode grouping 120 Boren Blvd #2300, Norman, OK 73072; E-mail: scheme of S12. Those primary categories were [email protected] defined as follows, with sample sizes and percentages of the TC tornado total: • Supercell: Containing a deep, persistent were diffuse and/or undistinguished with regard to mesocyclone with ≥10 m s-1 rotational velocity at most others nearby (section 3b). Figure 1e–f offers a ranges (maximum during tornado lifespan)—no QLCS exception. anticyclonic supercells found in TCs; 576 events The QLCS mode included spiral bands meeting (79%). aforementioned aspect–ratio and length criteria, as • Marginal supercell: Exhibiting some evidence well as those convective bands on the outer reaches of transient rotation at one or more volumetric beam of TC circulations moving with some component tilts, but not meeting supercell criteria; 63 events outward from center. Meng and Zhang (2012) found (9%). that 40% of Chinese TCs in 3 y contained QLCS • Nonsupercell: All other velocity and reflectivity modes, using somewhat similar Parker and Johnson signatures associated with tornadoes, non-rotational (2000) criteria (conterminous reflectivities ≥40 dBZ or exhibiting weak, non-rotational, horizontal shear; over ≥100 km but for 3-h duration). 85 events (12%). c. Environmental data Six events out of 730 (<1%) were unclassified. In those cases, the tornadic storm was out of radar Gridded, hourly environmental data, as described range or radar data were missing, but environmental in detail by Schneider and Dean (2008), were analyses were performed for E12. These are not associated with each tornado in our analysis. If the included in our analyses, yielding 724 total events. time of the tornado record was 2155 UTC, it was assigned to the 2100 UTC analysis hour. In Ten specific convective modes encompassing the summary, the environmental dataset consists of above three bins were associated with TC tornadoes objectively analyzed surface observations applied to a in E12. The following four were entirely first-guess field composed of the hourly Rapid Update nonsupercellular. Of these, 85 cases are examined Cycle (RUC2, after Benjamin et al. 2004) analysis. herein, with sample sizes and percentages of the The surface field then is combined with RUC gridded NSTC event total: data aloft, as with the hourly SPC mesoanalyses (Bothwell et al. 2002). The resulting three- • Discrete: Separated from other cells at ≥35 dimensional data can be passed through a modern dBZ; 13 events (15%), e.g., Fig. 1a–c. Linux version of the Skew-T Analysis and Hodograph • Quasi-linear convective system (QLCS): Research Program (Hart and Korotky 1991) to yield Conterminous reflectivities ≥35 dBZ over ≥100 km numerous derived environmental parameters. long-axis length, with ≥3 to 1 axial aspect ratio; included embedded cells; 21 events (25%), e.g., Fig. d. Possible causes of data error 1d–f. • Cluster: Conterminous reflectivities ≥35 dBZ Potential sources for error in the TC tornado, radar using < 3 to 1 axial aspect ratio; included diffuse and environmental data are offered in E12. To and/or disorganized reflectivity patterns, eyewalls and summarize, these include: eyewall remnants; 25 events (29%), e.g., Fig. 1g–i. Time errors of reports not attributable to any Also known as “disorganized” (S12). collocated echo. Five NSTC events were • Cell in cluster: ≥35 dBZ echo connected to corrected to the nearest echo time of passage others but with distinctive, persistent higher-reflectivity over the report location. Two other reports maxima; 26 events (31%), e.g., Fig. 1j–l. could not be associated with a specific echo. A few other events may have been associated Some relatively straightforward examples of each with a different, stronger echo than the spatially of these NSTC tornadic convective modes are shown closest one at radar time, but in absence of in Fig. 1. Most cases in each modal bin were not as substantial velocity signatures characteristic of well-defined in reflectivity as those, whether at 0.5º or supercells, a definite time change could not be in higher beam elevations (not shown). In fact, made. subjectively evaluated modal definition tended to As described in S12, convective mode become more difficult with greater elevation above sometimes could not be categorized cleanly, 1 radar level (ARL), typically because of the shallow especially between cell-in-cluster, QLCS and nature of the most intense portions of the echoes. clustered modes. Diffuse or amorphous NSTC Furthermore, because of the great variation in radar reflectivity patterns not meeting cell-in-cluster, appearance and echo morphology within each QLCS or discrete criteria specified above were mode—especially for those that are clustered—the assigned to the “cluster” bin, making