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Southeastern U.S. Tornado Outbreak Likelihood Using Daily Climate Indices 15 APRIL 2020 B R O W N A N D N O W O T A R S K I 3229 Southeastern U.S. Tornado Outbreak Likelihood Using Daily Climate Indices MATTHEW C. BROWN AND CHRISTOPHER J. NOWOTARSKI Department of Atmospheric Sciences, Texas A&M University, College Station, Texas (Manuscript received 12 September 2019, in final form 9 January 2020) ABSTRACT This study investigates relationships between climate-scale patterns and seasonal tornado outbreaks across the southeastern United States. Time series of several daily climate indices—including Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific–North American (PNA) pattern, east/west Pacific Oscillation (EPO/WPO), and both raw and detrended Gulf of Mexico SST anomalies (SSTA/SSTAD)—are collected in advance of Southeast severe convective days and grouped using self-organizing maps (SOMs). Spatiotemporal distributions of storm reports within nodes are compared to seasonal climatology, and the evolution of the regional environment for nodes associated with outbreaks is analyzed to provide physical justification for such associations. This study confirms findings from several tornado-related climate studies in the literature, while also identifying a number of new patterns associated with Southeast tornado outbreaks. Both the AO and NAO are relevant across all seasons, especially on lead time scales of 1–2 months, while SSTA/SSTADs are relevant on smaller time scales. The physical connection between these patterns and the regional storm environment is largely related to alterations of upper-level circulation and jet stream patterns, which in turn influence deep- and low-level shear, inland transport of moisture and instability, and other regional characteristics pertinent to tornado outbreaks. These results suggest that climate-scale variability can modulate and potentially be used to predict regional storm environments and their likelihood to produce tornado outbreaks across the Southeast. 1. Introduction potential energy (CAPE), storm relative helicity (SRH), lifting condensation level (LCL), and both deep (0–6 km) A multitude of thermodynamic and kinematic factors and low-level (0–1 km) shear (e.g., Davies and Johns 1993; spanning multiple spatiotemporal scales influences the for- Rasmussen and Blanchard 1998; Markowski et al. 1998; mation of tornadoes, such that forecasting them remains Edwards and Thompson 2000; Thompson et al. 2003; challenging. Despite this complexity, numerous studies over Rasmussen 2003; Thompson et al. 2007). the preceding decades have identified storm environment Though questions still remain regarding how synoptic characteristics that favor tornadoes and tornado outbreaks. and mesoscale processes affect regional storm environ- These features range from the synoptic scale, including the ments, less is known about global-scale patterns that positioning of upper- and midlevel troughs, jet streaks, air- lead to conducive synoptic/regional patterns for torna- mass boundaries, regional moisture and instability, and low- does. A number of recent papers have probed the rela- level jet variability (e.g., Uccellini and Johnson 1979; Kloth tionships between various large-scale circulation and and Davies-Jones 1980; Maddox and Doswell 1982; Atkins pressure patterns and CONUS tornadoes. Perhaps et al. 1999; Thompson and Edwards 2000; Muñoz and the most thoroughly explored of these relationships is Enfield 2011), down to more localized characteristics of with El Niño–Southern Oscillation (ENSO), which has the near-storm environment, such as convective available been known to alter the latitudinal position of the jet stream (Miller 1972; Ropelewski and Halpert 1986; Supplemental information related to this paper is available at Smith et al. 1998; Nunn and DeGaetano 2004), thus the Journals Online website: https://doi.org/10.1175/JCLI-D-19- influencing synoptic weather patterns and the likelihood 0684.s1. of widespread tornadic activity (Schaefer 1986; Johns and Doswell 1992). Earlier attempts to constrain this Corresponding author: Matthew C. Brown, matthew_brown@ ENSO–CONUS tornado relationship yielded varying tamu.edu conclusions. Several such studies initially cast doubt on DOI: 10.1175/JCLI-D-19-0684.1 Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 09/29/21 12:35 AM UTC 3230 JOURNAL OF CLIMATE VOLUME 33 whether ENSO phase has any significant impact on the exact origin and length of these trajectories exhibit the frequency (Schaefer and Tatom 1999; Marzban and some seasonal dependence. Last, Allen et al. (2018) found Schaefer 2001) or strength (Agee and Zurn-Birkhimer that variations in ENSO intensity influence the seasonal 1998; Schaefer and Tatom 1999) of tornadic activity. peak and temporal onset on CONUS tornadoes. Knowles and Pielke (2005) noted increases in the prev- Other studies have turned to different global patterns to alence of strong tornadoes and ‘‘large number out- explain variability in CONUS tornadic activity. Lee et al. breaks’’ corresponding to La Niña conditions (i.e., the (2013) found that warm tropical Pacific SSTs that develop cool phase of ENSO). Cook and Schaefer (2008) asserted during the transition between dominant ENSO phases (trans- that winters with neutral ENSO conditions in tropical Niño) are more conducive to spring tornado outbreaks, Pacific SSTs were associated with larger and more fre- though the authors themselves note the weak statistical quent tornado outbreaks, particularly in contrast with strength of this relationship. Both Thompson and Roundy El Niño (warm phase) conditions. These and other (2013) and Barrett and Gensini (2013) suggested that certain related studies (e.g., Bove 1998; Sankovich et al. 2004) phases of the Madden–Julian oscillation (MJO) modulate were somewhat limited, however. Limitations include large-scale circulations in ways that favor or impede torna- large variability and the presence of nonmeteorological dogenesis during the spring, though the phases they deem biases within the tornado report database and limited favorable vary depending on the month chosen for analysis. sample size—both in relation to tornadoes themselves, Tippett (2018) agreed that tornado likelihood seems to vary and methodological characterization of tornado/outbreak by MJO phase, but also noted that the exact connection is days—potentially limiting the robustness of these results. sensitive to how one defines their MJO and tornado day More recent papers have sufficiently addressed these metrics. Muñoz and Enfield (2011) related the negative limitations and provided more agreement on this subject. Pacific–North American (PNA) phase to a strengthening of Allen et al. (2015) identified robust increases in tornado the intra-Americas low-level jet, which subsequently en- and hail reports across portions of the central plains and hances moisture flux into the Mississippi and Ohio River Southeast in association with La Niña conditions, and basins. Elsner et al. (2016) tangentially noted a decrease in noted a latitudinal shift in these reports in response to mean tornadic activity across the Southeast during the positive seasonal positioning of the jet stream, surface cyclogenesis, North Atlantic Oscillation (NAO) phase. Last, some recent and its associated instability axes. Furthermore, this study studies (Trapp and Hoogewind 2018; Childs et al. 2018)have demonstrated that the influence of ENSO on CONUS se- suggested that Arctic conditions may influence the frequency vere convection extends well into spring months, in contrast of CONUS tornadoes via modifications of North American to much of the earlier literature, which suggested that any jet stream patterns, albeit in opposite seasons—July for the potential ENSO impacts would be isolated to winter former study, winter for the latter. months. Cook et al. (2017) came to similar conclusions Though these studies have provided valuable insights regarding the favorability of La Niña conditions for severe regarding global-scale influence on severe weather var- convection, but instead through the lens of tornado out- iability, the methodology adopted often limits the ap- breaks. The most recent additions to the literature have plicability of their results. While several of the papers further contextualized this relationship by considering mentioned above have begun to investigate cool-season ENSO interactions with other parts of the climate system tornadoes, the focus of this literature remains skewed and in terms of its intrinsic variability. Molina et al. (2018) toward warm-season storm environments and their as- considered the interplay between ENSO and Gulf of sociated tornadoes. Though the warm season coincides Mexico (GOM) SSTs—a key source of moist instability with a peak in tornadic activity across much of the associated with increased hail and tornado counts across CONUS, a secondary peak in the winter months has portions of the United States during both the warm season been documented within the southeastern United States (Molina et al. 2016; Jung and Kirtman 2016) and cool (Fike 1993; Guyer et al. 2006). Many of these cool- season (Thompson et al. 1994; Edwards and Weiss 1996). In season storms form in environments that deviate sub- particular, this study found that both the frequency and stantially from the prototypical high-shear, high-CAPE location of significant tornadoes (EF21 on the enhanced storm environment (Guyer and Dean
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