• Adlerman, E. J., , K. K. Droegemeier, , and R. Davies-Jones, 1999: A numerical simulation of cyclinc mesocyclogenesis. J. Atmos. Sci., 56, 20452069, doi:10.1175/1520-0469(1999)056<2045:ANSOCM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., , and M. St. Laurent, 2009a: Bow echo mesovortices. Part I: Processes that influence their damaging potential. Mon. Wea. Rev., 137, 14971513, doi:10.1175/2008MWR2649.1.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., , and M. St. Laurent, 2009b: Bow echo mesovortices. Part II: Their genesis. Mon. Wea. Rev., 137, 15141532, doi:10.1175/2008MWR2650.1.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., , and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, doi:10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Calianese, E. J., , J. K. Jordan, , E. B. Curran, , A. R. Moller, , and G. Woodall, 2002: The Mayfest high-precipitation supercell of 5 May 1995: A case study. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 105–108.

  • Dahl, J. M., , M. D. Parker, , and L. J. Wicker, 2012: Uncertainties in trajectory calculations with near-surface mesocyclones of simulated supercells. Mon. Wea. Rev., 140, 29592966, doi:10.1175/MWR-D-12-00131.1.

    • Search Google Scholar
    • Export Citation
  • Dial, G. L., , J. P. Racy, , and R. L. Thompson, 2010: Short-term convective mode evolution along synoptic boundaries. Wea. Forecasting, 25, 14301446, doi:10.1175/2010WAF2222315.1.

    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, , and J. S. Evans, 2003: Proximity sounding analysis for derechos and supercells: An assessment of similarities and differences. Atmos. Res., 67–68, 117–133, doi:10.1016/S0169-8095(03)00047-4.

    • Search Google Scholar
    • Export Citation
  • Evans, J. S., , and C. A. Doswell, 2001: Examination of derecho environments using proximity soundings. Wea. Forecasting, 16, 329342, doi:10.1175/1520-0434(2001)016<0329:EODEUP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Finley, C. A., , W. R. Cotton, , and R. A. Pielke, 2001: Numerical simulation of tornadogenesis in a high-precipitation supercell. Part I: Storm evolution and transition into a bow echo. J. Atmos. Sci., 58, 15971629, doi:10.1175/1520-0469(2001)058<1597:NSOTIA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., , and Y. Ogura, 1988: Numerical simulation of a midlatitude squall line in two dimensions. J. Atmos. Sci., 45, 38463879, doi:10.1175/1520-0469(1988)045<3846:NSOAMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2008: The initiation and evolution of multiple modes of convection within a meso-alpha-scale region. Wea. Forecasting, 23, 12211252, doi:10.1175/2008WAF2222136.1.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2010: The response of simulated nocturnal convective systems to a developing low-level jet. J. Atmos. Sci., 67, 33843408, doi:10.1175/2010JAS3329.1.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2012: Observations of mergers between squall lines and isolated supercell thunderstorms. Wea. Forecasting, 27, 255278, doi:10.1175/WAF-D-11-00058.1.

    • Search Google Scholar
    • Export Citation
  • Fujita, T. T., 1978: Manual of downburst identification for project NIMROD. SMRP Research Paper 117, University of Chicago, 104 pp. [NTIS N78-30771/1GI.]

  • Fujita, T. T., 1985: The downburst: Microburst and macroburst. SMRP Research Paper 210, University of Chicago, 122 pp. [NTIS PB-148880.]

  • Fujita, T. T., , and H. R. Byers, 1977: Spearhead echo and downbursts in the crash of an airliner. Mon. Wea. Rev., 105, 129146, doi:10.1175/1520-0493(1977)105<0129:SEADIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gallus, W. A., Jr., , N. A. Snook, , and E. V. Johnson, 2008: Spring and summer severe weather reports over the Midwest as a function of convective mode: A preliminary study. Wea. Forecasting, 23, 101113, doi:10.1175/2007WAF2006120.1.

    • Search Google Scholar
    • Export Citation
  • Goodman, S. J., , and K. R. Knupp, 1993: Tornadogenesis via squall line and supercell interaction: The November 15, 1989, Huntsville, Alabama, tornado. The Tornado: Its Structure, Dynamics, Prediction, and Hazards,Geophys. Monogr., Vol. 79, Amer. Geophys. Union, 183199, doi:10.1029/GM079p0183.

  • Grim, J. A., , R. A. Rauber, , G. M. McFarquhar, , B. F. Jewett, , and D. P. Jorgensen, 2009: Development and forcing of the rear inflow jet in a rapidly developing and decaying squall line during BAMEX. Mon. Wea. Rev., 137, 12061229, doi:10.1175/2008MWR2503.1.

    • Search Google Scholar
    • Export Citation
  • Houston, A. L., , and R. B. Wilhelmson, 2011: The dependence of storm longevity on the pattern of deep convection initiation in a low-shear environment. Mon. Wea. Rev., 139, 31253138, doi:10.1175/MWR-D-10-05036.1.

    • Search Google Scholar
    • Export Citation
  • Houston, A. L., , and R. B. Wilhelmson, 2012: The impact of airmass boundaries on the propagation of deep convection: A modeling-based study in a high-CAPE, low-shear environment. Mon. Wea. Rev., 140, 167183, doi:10.1175/MWR-D-10-05033.1.

    • Search Google Scholar
    • Export Citation
  • James, R. P., , J. M. Fritsch, , and P. M. Markowski, 2005: Environmental distinctions between cellular and slabular convective lines. Mon. Wea. Rev., 133, 26692691, doi:10.1175/MWR3002.1.

    • Search Google Scholar
    • Export Citation
  • James, R. P., , P. M. Markowski, , and J. M. Fritsch, 2006: Bow echo sensitivity to ambient moisture and cold pool strength. Mon. Wea. Rev., 134, 950964, doi:10.1175/MWR3109.1.

    • Search Google Scholar
    • Export Citation
  • Jewett, B. F., , and R. B. Wilhelmson, 2006: The role of forcing in cell morphology and evolution within midlatitude squall lines. Mon. Wea. Rev., 134, 37142734, doi:10.1175/MWR3164.1.

    • Search Google Scholar
    • Export Citation
  • Klimowski, B. A., , M. R. Hjelmfelt, , and M. J. Bunkers, 2004: Radar observations of the early evolution of bow echoes. Wea. Forecasting, 19, 727734, doi:10.1175/1520-0434(2004)019<0727:ROOTEE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kogan, Y. L., , and A. Shapiro, 1996: The simulation of a convective cloud in a 3D model with explicit microphysics. Part II: Dynamical and microphysical aspects of cloud merger. J. Atmos. Sci., 53, 25252545, doi:10.1175/1520-0469(1996)053<2525:TSOACC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lafore, J.-P., , and M. W. Moncrieff, 1989: A numerical investigation of the organization and interaction of the convective and stratiform regions of tropical squall lines. J. Atmos. Sci., 46, 521544.

    • Search Google Scholar
    • Export Citation
  • Letkewicz, C. E., , A. J. French, , and M. D. Parker, 2013: Base-state substitution: An idealized modeling technique for approximating environmental variability. Mon. Wea. Rev., 141, 30623086, doi:10.1175/MWR-D-12-00200.1.

    • Search Google Scholar
    • Export Citation
  • Mahoney, K. M., , and G. M. Lackmann, 2011: The sensitivity of momentum transport and severe surface winds to environmental moisture in idealized simulations of a mesoscale convective system. Mon. Wea. Rev., 139, 13521369, doi:10.1175/2010MWR3468.1.

    • Search Google Scholar
    • Export Citation
  • Markowski, P., , and Y. Richardson, 2010: Mesoscale Meteorology in Midlatitudes. Wiley, 430 pp.

  • Moller, A. R., , C. A. Doswell III, , and R. Przybylinski, 1990: High precipitation supercells: A conceptual model and documentation. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, Alberta, Canada, Amer. Meteor. Soc., 52–57.

  • Moller, A. R., , C. A. Doswell III, , M. P. Foster, , and G. R. Woodall, 1994: The operational recognition of supercell thunderstorm environments and storm structures. Wea. Forecasting, 9, 327347, doi:10.1175/1520-0434(1994)009<0327:TOROST>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Przybylinski, R. H., 1995: The bow echo: Observations, numerical simulations, and severe weather detection methods. Wea. Forecasting, 10, 203218, doi:10.1175/1520-0434(1995)010<0203:TBEONS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, E. N., , and D. O. Blanchard, 1998: A baseline climatology of sounding–derived supercell and tornado forecast parameters. Wea. Forecasting, 13, 11481164, doi:10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Richardson, Y. P., , K. K. Droegemeier, , and R. P. Davies-Jones, 2007: The influence of horizontal environmental variability on numerically simulated convective storms. Part I: Variations in vertical shear. Mon. Wea. Rev., 135, 34293455, doi:10.1175/MWR3463.1.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , J. B. Klemp, , and M. L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463485, doi:10.1175/1520-0469(1988)045<0463:ATFSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sabones, M., , E. M. Agee, , and M. Akridge, 1996: The Pulaski county and West Lafayette, Indiana, tornadoes, 26–27 April 1994: A case of supercell (mesocyclone) and squall line bow-echo interaction. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 746–750.

  • Sieveking, J. E., , and R. W. Przybylinski, 2004: The interaction of a HP supercell thunderstorm and bow echo to produce a prolonged severe wind event in east central Missouri. 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 7A.5. [Available online at https://ams.confex.com/ams/11aram22sls/webprogram/Paper81818.html.]

  • Skamarock, W. C., , M. L. Weisman, , and J. B. Klemp, 1994: Three-dimensional evolution of simulated long-lived squall lines. J. Atmos. Sci., 51, 25632584, doi:10.1175/1520-0469(1994)051<2563:TDEOSL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smith, B. T., , R. L. Thompson, , J. S. Grams, , C. Broyles, , and H. E. Brooks, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part I: Storm classification and climatology. Wea. Forecasting, 27, 11141135, doi:10.1175/WAF-D-11-00115.1.

    • Search Google Scholar
    • Export Citation
  • Smull, B. F., , and R. A. Houze Jr., 1987: Rear inflow in squall lines with trailing stratiform precipitation. Mon. Wea. Rev., 115, 28692889, doi:10.1175/1520-0493(1987)115<2869:RIISLW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., , B. T. Smith, , J. S. Grams, , A. R. Dean, , and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Storm supercell and QLCS tornado environments. Wea. Forecasting, 27, 11361154, doi:10.1175/WAF-D-11-00116.1.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., , and M. L. Weisman, 2003: Low-level mesovortices within squall lines and bow echoes. Part II: Their genesis and implications. Mon. Wea. Rev., 131, 28042823, doi:10.1175/1520-0493(2003)131<2804:LMWSLA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., , S. A. Tessendorf, , E. S. Godfrey, , and H. E. Brooks, 2005: Tornadoes from squall lines and bow echoes. Part I: Climatological distribution. Wea. Forecasting, 20, 2334, doi:10.1175/WAF-835.1.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., 2001: Convectively driven high wind events. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 255–298.

  • Wakimoto, R. M., , H. V. Murphey, , C. A. Davis, , and N. T. Atkins, 2006: High winds generated by bow echoes. Part II: The relationship between the mesovortices and damaging straight-line winds. Mon. Wea. Rev., 134, 28132829, doi:10.1175/MWR3216.1.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., 1993: The genesis of severe, long-lived bow echoes. J. Atmos. Sci., 50, 645670, doi:10.1175/1520-0469(1993)050<0645:TGOSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504520, doi:10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112, 24792498, doi:10.1175/1520-0493(1984)112<2479:TSACON>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and C. A. Davis, 1998: Mechanisms for the generation of mesoscale vortices within quasi-linear convective systems. J. Atmos. Sci., 55, 26032622, doi:10.1175/1520-0469(1998)055<2603:MFTGOM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , J. B. Klemp, , and R. Rotunno, 1988: Structure and evolution of numerically simulated squall lines. J. Atmos. Sci., 45, 19902013, doi:10.1175/1520-0469(1988)045<1990:SAEONS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Westcott, N. E., 1994: Merging of convective clouds: Cloud initiation, bridging, and subsequent growth. Mon. Wea. Rev., 122, 780790, doi:10.1175/1520-0493(1994)122<0780:MOCCCI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wheatley, D. M., , R. J. Trapp, , and N. T. Atkins, 2006: Radar and damage analysis of severe bow echoes observed during BAMEX. Mon. Wea. Rev., 134, 791806, doi:10.1175/MWR3100.1.

    • Search Google Scholar
    • Export Citation
  • Wicker, L. J., , and R. B. Wilhelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 26752703, doi:10.1175/1520-0469(1995)052<2675:SAAOTD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wolf, P. L., 1998: WSR-88D radar depiction of supercell–bow echo interaction: Unexpected evolution of a large, tornadic “comma-shaped” supercell over eastern Oklahoma. Wea. Forecasting, 13, 492504, doi:10.1175/1520-0434(1998)013<0492:WRDOSB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wolf, R., , R. Przybylinski, , and P. Berg, 1996: Observations of a merging bowing segment and supercell. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 740–745.

  • Xue, M., 2004: Tornadogenesis within a simulated supercell storm. 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 9.6. [Available online at https://ams.confex.com/ams/11aram22sls/techprogram/paper_81574.htm.]

  • Yang, M.-J., , and R. A. Houze Jr., 1995: Sensitivity of squall-line rear inflow to ice microphysics and environmental humidity. Mon. Wea. Rev., 123, 31753193, doi:10.1175/1520-0493(1995)123<3175:SOSLRI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
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    Skew T–logp diagrams and hodographs depicting (a) the horizontally homogeneous background environment for the initial 3 h of simulation time and (b) the far-field, pre-squall-line environment including the updated wind profile introduced by BSS and squall-line-induced perturbations to the environment 3 h into the simulation. Insets display values for CAPE, CIN, 0–3-km helicity, and storm-relative helicity, and 0–1, 0–3, and 0–6 km AGL bulk vector wind difference for each environment. Color scheme on the hodographs identifies the 0–1- (green), 1–3- (blue), 3–6- (red), and >6-km (black) layers.

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    Simulated radar reflectivity (dBZ, shaded), −2-K surface θ′ (black contour), and 1 km AGL wind vectors (m s−1, scale vector below color bar) for the (a)–(e) base-state simulation with no BSS and (f)–(j) NOMERGER simulation between (left to right) 120 and 240 min into the simulation. The new environment is applied 180 min into the simulation in (g)–(j).

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    Summary plot of 1 km AGL simulated radar reflectivity (dBZ, gray shading), −2-K surface θ′ (dashed purple contour), and 2.5 km AGL wind vectors and wind speed [contoured at 25 m s−1 (blue) and 30 m s−1 (red)] at (a) 240, (b) 250, (c) 265, (d) 280, (e) 295, and (f) 325 min into the NOMERGER simulation. Curved green arrows denote approximate locations of bookend vortices based on vertical vorticity magnitude > 5 × 10−3 s−1, Obuku–Weiss number < 0, and general cyclonic or anticyclonic pattern of the wind vectors.

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    As in Fig. 3, but for the MERGER simulation. The curved yellow and red arrows denote, respectively, the approximate locations of the supercell mesocyclone and postmerger cyclonic vortex described in the text. Criteria for identifying these are as in Fig. 3.

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    (a)–(e) As in Fig. 3, but for supercell-only simulation. (f) Maximum wind speed (m s−1, shaded) at the lowest model level accumulated over the duration of the supercell-only simulation. The black × in (f) denotes the point when the right-moving supercell splits from the initial storm and the dashed black oval indicates the region of enhanced wind associated with the right-moving supercell.

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    Swaths of (a),(b) maximum wind speed (m s−1, shaded) and (c),(d) vertical vorticity (s−1, shaded) at the lowest model level, and (e),(f) rainfall (mm, shaded) accumulated between 3 and 6 h into the (a),(c),(e) MERGER and (b),(d),(f) NOMERGER simulations. Dashed black ovals denote the regions of enhanced fields in the MERGER simulation. The black × in each panel denotes the relative location of the merger, defined as the onset of the permanent union of the 40-dBZ contour between the squall line and supercell, which occurred at t = 265 min into the MERGER simulation.

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    (a)–(e) Surface θ′ (K, shaded contours) and (f)–(j) 1 km AGL w (m s−1, shaded) and −2-K θ′ (black contour) between 225 and 265 min into the MERGER simulation. Dashed black ovals denote the weakened squall-line gust front in (c),(d),(h), and (i).

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    (a)–(d) Vertical cross section of θe (K, shaded), θ′ (K, colored contours), w (white contours every 5 m s−1 starting at 5 m s−1), and wind vectors [sample vector to the right of (c)] averaged from y = 150 to 175 km at t = (a) 225, (b) 245, (c) 255, and (d) 265 min into the MERGER simulation.

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    (a)–(c) Simulated radar reflectivity (shaded, dBZ), and w at 2.5 km AGL [colored contours, m s−1, color scheme shown on right side of (f)]. (d)–(f) Along-line averaged θ′ (K, shaded) and w [contours as in (a)–(c)] averaged between y = 145 and y = 155 km [horizontal black lines in (a)–(c)]. Plots are at (left to right) t = 255, 265, and 275 min into the MERGER simulation.

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    Surface θ′ (K, shaded), and 1 km AGL simulated radar reflectivity (black contours at 45 and 50 dBZ) at t = (a) 280, (c) 285, and (e) 290 min into the MERGER simulation and t = (b) 255, (d) 260, and (f) 265 min into the NOMERGER simulation.

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    Pressure perturbation (hPa, shaded) and wind vectors (m s−1, scale vector at lower right) at 2.5 km AGL, and 45- and 50-dBZ simulated radar reflectivity contours at 1 km AGL at t = (a) 270, (c) 285, and (e) 290 min into the MERGER simulation and t = (b) 245, (d) 260, and (f) 265 min into the NOMERGER simulation.

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    Structure of pressure perturbations in MERGER simulation at t = 282 min. (a) Plan view of pressure perturbations (hPa, shaded) and winds at 2.5 km AGL. (b) Vertical cross section of buoyancy (m s−2, shaded), pressure perturbation (black contours every 1 hPa with 0 contour omitted and negative values dashed white), and winds. The dashed line in (a) denotes the plane of the cross sections in (b). In both panels, wind vectors >20, >25, and >30 m s−1 are colored black, blue, and red, respectively.

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    (bottom left) Plan view, (top) x–z cross section, and (bottom right) y–z cross section of 30-min-forward parcel trajectories ending at t = 285 min into the MERGER simulation that passed through regions of near-surface winds > 30 m s−1 between t = 280 and t = 285 min. The starting point for each trajectory is denoted by an open circle, with the trajectory colors signifying three parcel source regions of interest: green parcels originated to the rear of the squall line (RIJ), and orange and blue parcels originated in the low levels (0–2 km AGL) and midlevels (2–4 km AGL) in the vicinity of the remnant supercell, respectively. Total counts of each parcel type are shown (by color) in the top right. Shading in the plan view plot denotes maximum surface wind speed during the 280–285-min window (m s−1, shaded) and the 45-dBZ simulated radar reflectivity contour (purple). Only a subset of the parcels is plotted for clarity.

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    (a)–(c) As in Figs. 9a–c, but for w < 0 [m s−1 color scheme at right side of (c)], at t = (a) 260, (b) 275, and (c) 280 min into the MERGER simulation.

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    As in Fig. 13, but for 30-min trajectories ending at t = 315 min into the merger simulation.

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    Vertical cross sections of along-line-averaged hydrometeor mixing ratio (sum of rainwater, graupel, cloud water, cloud ice, and snow mixing ratios, kg kg−1, shaded), horizontal wind speed (m s−1, gray contours with 30 m s−1 contoured in red), and w < 1 m s−1 (vectors, scale vector at bottom right) at (left to right) t = 280, 305, and 315 min into the (a)–(c) NOMERGER and (d)–(f) MERGER simulations. Values are averaged between y = 165–175 km in the NOMERGER simulation and y = 145–155 km in the MERGER simulation to capture the regions of strongest bowing and rear inflow.

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    As in Fig. 16, but displaying θ′ (K) as the shaded field.

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    As in Fig. 4, but for the (a),(c) MERGER17.5 and (b),(d) MERGER25 simulations at t = 250 and 315 min into the simulations and the (e) NOMERGER17.5 and (f) NOMERGER25 simulations at t = 315 min into the simulations.

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    Maximum wind speed (m s−1, shaded) at the lowest model level accumulated between t = 3 and 7 h into the (a) MERGER17.5, (b) NOMERGER17.5, (c) MERGER25, and (d) NOMERGER25 simulations. The red × marks the merger location; regions of strong winds associated with the merger are highlighted by the dashed oval.

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    As in Fig. 17, but for the (a) NOMERGER17.5, (b) NOMERGER25, (c) MERGER17.5, and (d) MERGER25 simulations.

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    As in Fig. 4, but for the (a),(b) Y150; (c),(d) Y120; and (e),(f) Y90 simulations at the times indicated. The red × marks the merger location.

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    Maximum wind speed (colored shading, m s−1) at the lowest model level accumulated between t = 3 and 7 h into the (a) NOMERGER, (b) MERGER, (c) Y150, (d) Y120, (e) Y90, and (f) Y60 simulations. The red × marks the merger location in (b)–(f).

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    As in Figs. 9a–c, but for Y150 simulation at t = (a) 255, (b) 260, (c) 275, and (d) 295 min.

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    As in Fig. 10, but comparing the (a)–(c) MERGER and (d)–(f) Y150 simulations.

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    Schematic diagram illustrating the basic squall-line evolution following a merger with a supercell. White and dark gray shaded outlines represent radar reflectivity, blue contours represent cold pool potential temperature perturbations, heavy dark arrows represent the RIJ, red curved arrows represent vortices, and the light gray shaded area represents the swath of damaging surface winds. Adapted from Fig. 7 of FP12.

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Numerical Simulations of Bow Echo Formation Following a Squall Line–Supercell Merger

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  • 1 Atmospheric and Environmental Sciences, South Dakota School of Mines and Technology, Rapid City, South Dakota
  • | 2 Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina
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Abstract

Output from idealized numerical simulations is used to investigate the storm-scale processes responsible for squall-line evolution following a merger with an isolated supercell. A simulation including a squall line–supercell merger is compared to one using the same initial squall line and background environment without the merger. These simulations reveal that while bow echo formation is favored by the strongly sheared background environment, the merger produces a more compact bowing structure owing to a locally enhanced rear-inflow jet. The merger also represents a favored location for severe weather production relative to other portions of the squall line, with surface winds, vertical vorticity, and rainfall all being maximized in the vicinity of the merger.

An analysis of storm-scale processes reveals that the premerger squall line weakens as it encounters outflow from the preline supercell, and the supercell becomes the leading edge of the merged system. Subsequent localized strengthening of the cold pool and rear-inflow jet produce a compact, intense bow echo local to the merger, with a descending rear-inflow jet creating a broad swath of damaging surface winds. These features, common to severe bow echoes, are shown to be a direct result of the merger in the present simulations, and are diminished or absent in the no-merger simulation. Sensitivity tests reveal that mergers in a weaker vertical wind shear environment do not produce an enhanced bow echo structure, and only produce a localized region of marginally enhanced surface winds. Additional tests demonstrate that the details of postmerger evolution vary with merger location along the line.

Corresponding author address: Adam J. French, South Dakota School of Mines and Technology, 501 E. St. Joseph St., Rapid City, SD 57701. E-mail: adam.french@sdsmt.edu

Abstract

Output from idealized numerical simulations is used to investigate the storm-scale processes responsible for squall-line evolution following a merger with an isolated supercell. A simulation including a squall line–supercell merger is compared to one using the same initial squall line and background environment without the merger. These simulations reveal that while bow echo formation is favored by the strongly sheared background environment, the merger produces a more compact bowing structure owing to a locally enhanced rear-inflow jet. The merger also represents a favored location for severe weather production relative to other portions of the squall line, with surface winds, vertical vorticity, and rainfall all being maximized in the vicinity of the merger.

An analysis of storm-scale processes reveals that the premerger squall line weakens as it encounters outflow from the preline supercell, and the supercell becomes the leading edge of the merged system. Subsequent localized strengthening of the cold pool and rear-inflow jet produce a compact, intense bow echo local to the merger, with a descending rear-inflow jet creating a broad swath of damaging surface winds. These features, common to severe bow echoes, are shown to be a direct result of the merger in the present simulations, and are diminished or absent in the no-merger simulation. Sensitivity tests reveal that mergers in a weaker vertical wind shear environment do not produce an enhanced bow echo structure, and only produce a localized region of marginally enhanced surface winds. Additional tests demonstrate that the details of postmerger evolution vary with merger location along the line.

Corresponding author address: Adam J. French, South Dakota School of Mines and Technology, 501 E. St. Joseph St., Rapid City, SD 57701. E-mail: adam.french@sdsmt.edu

1. Introduction

One of the challenges faced by severe weather forecasters is anticipating how storms will organize, and how that organization will change over time, as different storm types tend to produce different types of severe weather hazards. Widespread straight-line damaging winds tend to be most prevalent in quasi-linear convective systems, particularly those that organize as bow echoes (Fujita 1978), while damaging hail is most often found in supercell thunderstorms (e.g., Gallus et al. 2008; Smith et al. 2012). Tornadoes have been documented with both types of storm organizations; however, most significant [(enhanced Fujita) EF-2 or greater], and long-lived tornadoes occur with supercells (Trapp et al. 2005; Smith et al. 2012).

The problem of forecasting convective mode has often been cast as a function of background environmental parameters (e.g., Weisman and Klemp 1982; Rasmussen and Blanchard 1998; Doswell and Evans 2003; Thompson et al. 2012) or forcing mechanisms (e.g., Jewett and Wilhelmson 2006; Dial et al. 2010; Houston and Wilhelmson 2012). The present work, however, seeks to better clarify the role that mergers between dissimilar storm types, specifically quasi-linear convective systems (“squall lines”) and isolated supercells, play in governing convective mode. Recent observational work by French and Parker (2012, hereafter FP12) has documented that these types of mergers frequently produce a spectrum of bow echoes (Fujita 1978) depending on the background environmental conditions (see Fig. 7 of FP12). These results are in line with past studies showing that storm mergers in general are a common avenue to bow echo formation (Klimowski et al. 2004).

As reviewed by FP12, several past studies have examined individual cases of squall line–supercell mergers (e.g., Fujita 1978; Goodman and Knupp 1993; Sabones et al. 1996; Wolf et al. 1996; Wolf 1998; Calianese et al. 2002; Sieveking and Przybylinski 2004). These studies have documented a number of features common to these events, including tornado development proximal to the merger time (e.g., Goodman and Knupp 1993; Sabones et al. 1996; Wolf et al. 1996; Wolf 1998), evolution toward bow echoes (Fujita 1978; Calianese et al. 2002; Sieveking and Przybylinski 2004), and an overall sustenance of the supercell postmerger (Sabones et al. 1996; Wolf et al. 1996; Wolf 1998). However, for the most part, these works, as with FP12, were unable to fully determine the storm-scale processes at work in these merger events. Goodman and Knupp (1993) observed distortions to the squall line’s gust front during the merger case that they investigated. They hypothesized that the mesohigh associated with the supercell’s outflow may have locally blocked the advance of the squall line’s cold pool, slowing its forward progress in the vicinity of the merger. However, their analysis focused on tornado development associated with the merger rather than bow echo formation so it is unclear what role this process may play in the bow echo evolution observed by FP12. In short, it remains unclear how the supercell merger may influence the development of important bow echo structures such as rear-inflow jets and bookend vortices.

With this in mind, the present study has used a series of idealized model simulations to investigate the storm-scale dynamics at work in cases of squall line–supercell mergers. While these simulations focused on the specific situation of mergers between squall lines and supercells, the results are also broadly applicable to the role that mergers play in bow echo genesis more generally. In particular, the simulations and the subsequent analysis were designed to address four main questions:

  1. How does the initial squall line’s cold pool evolve during the merger, and how does this impact the subsequent morphology of the merged system?
  2. Given a favorable background environment, what role does the merger play in forming the bow echo, particularly in terms of modulating the formation of key bow echo features such as rear-inflow jets, bookend vortices, and strong cold pools?
  3. In light of the severe storm report data analyzed by FP12, does the merger location represent a region of particularly severe weather compared to the rest of the squall line?
  4. Finally, what impact does the specific location of the merger along the squall line play on subsequent morphology and in producing the range of bow echo modes observed by FP12?

By focusing on the bow echo aspect of these merger cases this study examines the merger from the “squall-line perspective” (i.e., how the squall line changes in response to the merger with the supercell). A subsequent paper will discuss the storm-scale evolution of the vertical vorticity field in these cases, evaluating the merger from the “supercell perspective.” Section 2 details the experimental setup for our simulations, including a novel means of introducing two distinct modes of convection into an idealized cloud model simulation with a homogeneous base state. This is followed in section 3 by an overview of the basic simulations, and a comparison between simulations with and without a merger. In section 4 we provide a detailed analysis of the evolution of the cold pool, the development of the bow echo, and the severe wind generation mechanisms associated with our simulated squall line–supercell merger. The sensitivity of the postmerger evolution to the background wind profile and merger location are explored in section 5. Finally, in section 6, we conclude by summarizing our results in relation to the observations presented by FP12 and other past works, and set the stage for a companion paper that will focus on the evolution of the supercell during these types of events.

2. Idealized simulation setup

This work utilized 3D idealized numerical model simulations using version 1.16 of the Bryan cloud model (CM1) described by Bryan and Fritsch (2002). We used a horizontal grid spacing of 500 m in order to sufficiently resolve convective-scale processes while also keeping computing costs manageable given the 300 km × 400 km × 20 km grid necessary to simulate a squall line, supercell, and merged system. The vertical grid spacing was stretched from 100 m at the surface to 250 m above z = 2500 m. We employed open x and y lateral boundary conditions, free-slip upper and lower boundary conditions, and a Rayleigh damping layer above 14 km.

In the interest of keeping the simulations as simple as possible, radiative effects, surface friction and surface fluxes were all neglected. The simulations include Coriolis forcing, applied to perturbation winds only at a constant value of f = 1 × 10−4 s−1 across the entire domain (i.e., an f plane). This was included because initial tests revealed that it was necessary in order to produce the asymmetric structures (i.e., a dominant cyclonic line-end vortex at the north end of the squall line) observed following real-world mergers. This is not surprising as the convergence of planetary vorticity has been shown by a number of studies to be important to the development of cyclonic mesoscale vortices over a wide range of scales (i.e., Weisman 1993; Skamarock et al. 1994; Trapp and Weisman 2003; Atkins and St. Laurent 2009b).

The present simulations used a horizontally homogeneous background environment (Fig. 1a), based on the idealized environment of Weisman and Klemp (1982) that has been widely used in the simulation of convective storms. The squall line was triggered using a 200-km-long (y dimension), 20-km-wide (x dimension), and 2.8-km-deep (z dimension) linear warm bubble with a potential temperature perturbation of +2 K. The potential temperature excess was maximized along the bubble’s center line and decreased to 0 following a cosine function over a 10 km (1.4 km) horizontal (vertical) radius. Random noise of ±0.1 K was added to the thermal to help develop three-dimensional structures along the line.

Fig. 1.
Fig. 1.

Skew T–logp diagrams and hodographs depicting (a) the horizontally homogeneous background environment for the initial 3 h of simulation time and (b) the far-field, pre-squall-line environment including the updated wind profile introduced by BSS and squall-line-induced perturbations to the environment 3 h into the simulation. Insets display values for CAPE, CIN, 0–3-km helicity, and storm-relative helicity, and 0–1, 0–3, and 0–6 km AGL bulk vector wind difference for each environment. Color scheme on the hodographs identifies the 0–1- (green), 1–3- (blue), 3–6- (red), and >6-km (black) layers.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Trial and error revealed that the main challenge in simulating a squall line–supercell merger in the desired idealized setting lies with producing both convective modes simultaneously within a single simulation: in many cases a simulation that produced a reasonable supercell storm would not produce a persistent squall line, and vice versa. This stems from the long-understood concept that convective organization is strongly tied to the background environment, particularly the wind profile (e.g., Weisman and Klemp 1982, 1984; Rotunno et al. 1988). In nature, the presence of environmental heterogeneity and strong linear forcing are often important to producing multiple modes in a localized region (e.g., Richardson et al. 2007; French and Parker 2008). However, trying to include such heterogeneity in our idealized model would limit our ability to run controlled tests focused on the role that the storm merger is playing in convective evolution.

To address this issue, we employed the base-state substitution (BSS) technique of Letkewicz et al. (2013) to utilize two different wind profiles during the simulation. First, we initiated a squall line in an environment characterized by a favorable, unidirectional wind profile (Fig. 1a) and let it mature for 3 hours, essentially the time necessary for the line to mature to a quasi-steady intensity. At this point, the BSS technique was employed to replace the background wind profile with one more representative of a supercell environment [i.e., strong (25 m s−1) deep-layer (0–6 km AGL) bulk layer vector wind difference and a low-level shear vector that veers with height (Fig. 1b)]. As detailed by Letkewicz et al. (2013), this was done by separating the original base-state wind profile from the perturbations that had developed in the course of running the 3-h squall-line simulation, introducing the new base-state wind profile, and then adding the original storm-induced perturbations back on to the new wind profile. In doing this we were able to create an environment that would support an isolated supercell, while still maintaining the physical perturbations to the wind and thermodynamic fields embodied by the squall line.

This change in environment was completed over a single model time step (e.g., the “instant BSS” of Letkewicz et al. 2013) in order to limit the amount of time necessary for the new wind profile to take effect. Only the wind profile was changed in this manner; the base-state thermodynamic profile was left untouched.1 Once the modifications were complete, the simulation was restarted using the new background environment and the supercell was triggered 60 km ahead of the squall line at y = 140 km using a +1-K spheroid warm bubble with horizontal and vertical radii of 10 km and 1.4 km, respectively. The y position of the bubble was chosen to simulate a merger near the northern end of the squall line, similar to the “system-scale bowing” paradigm of FP12, which was their most common post-merger evolution in cases of weak synoptic forcing.

Care was taken to ensure that there were no lingering effects of the BSS on our analysis of the simulated squall line–supercell merger. Aside from small, discrete changes to the domain-total mass, energy, and cloud water fields at the time of the BSS, as documented by Letkewicz et al. (2013) there was little detrimental impact of the BSS on the simulated squall line (Fig. 2). The line gradually intensified and grew more organized over the 30–60 min following the introduction of the new environment, consistent with the expected behavior of a squall line encountering stronger vertical wind shear (e.g., Weisman et al. 1988; Weisman 1993). More importantly, the simulation was configured so that the merger occurred approximately 90 min after the application of the BSS, so any adjustments to the new environment would not impact the analysis of the merger itself.

Fig. 2.
Fig. 2.

Simulated radar reflectivity (dBZ, shaded), −2-K surface θ′ (black contour), and 1 km AGL wind vectors (m s−1, scale vector below color bar) for the (a)–(e) base-state simulation with no BSS and (f)–(j) NOMERGER simulation between (left to right) 120 and 240 min into the simulation. The new environment is applied 180 min into the simulation in (g)–(j).

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

It should be emphasized that the purpose of the unidirectional shear pre-BSS environment was to facilitate the development of a well-organized squall line that could then be introduced to an environment that supported supercells. Our analysis will focus on the impact of the merger within the highly sheared, post-BSS environment, rather than the effects of change in environment. A sensitivity test simulating a squall line with the environmental modifications applied gradually over an hour (e.g., the “gradual BSS” of Letkewicz et al. 2013) was not substantially different from that run with the instant BSS once the environmental modification was complete. The gradual method did, however, require an additional hour of simulation time, so the instant method was chosen in favor of computational efficiency.

We ran two primary simulations using the instant BSS method. The first simulation includes the wind profile modification after 3 h, but does not trigger the supercell. It is intended to serve as a baseline for how the squall line evolves in the absence of the merger and will be referred to as the NOMERGER simulation. In the second simulation, the modified wind profile and initiating bubble for the supercell are added 3 h into the simulation in order to simulate the squall line–supercell merger. This will be referred to as the MERGER simulation. An additional simulation was run that included the supercell in isolation in the higher shear environment in order to compare its evolution with the supercell in the MERGER case. Finally, we ran a series of sensitivity tests using different wind profiles and merger locations. The details of these simulations will be discussed when they are introduced in section 5.

3. Overview and comparison of the basic simulations

We begin our analysis with an overview of the NOMERGER simulation as a baseline example of how a squall line evolves in the simulated environment. Following the introduction of the stronger vertical wind shear environment (t = 180 min into the simulation), the NOMERGER squall line gradually strengthens and organizes into a broad bow echo characterized by counter-rotating bookend vortices and a well-organized rear-inflow jet between y = 140 and y = 180 km (Figs. 3a–f). This is the expected result, as bow echo structures are favored in environments characterized by strong deep-layer wind shear (e.g., Weisman 1993; Evans and Doswell 2001). The bow echo becomes increasingly asymmetric over the duration of the simulation, with the northern, cyclonic, bookend vortex eventually becoming dominant (Figs. 3d–f). All told, the bowing and asymmetric structure of the simulated squall line are in line with what is expected given the environment and presence of Coriolis accelerations.

Fig. 3.
Fig. 3.

Summary plot of 1 km AGL simulated radar reflectivity (dBZ, gray shading), −2-K surface θ′ (dashed purple contour), and 2.5 km AGL wind vectors and wind speed [contoured at 25 m s−1 (blue) and 30 m s−1 (red)] at (a) 240, (b) 250, (c) 265, (d) 280, (e) 295, and (f) 325 min into the NOMERGER simulation. Curved green arrows denote approximate locations of bookend vortices based on vertical vorticity magnitude > 5 × 10−3 s−1, Obuku–Weiss number < 0, and general cyclonic or anticyclonic pattern of the wind vectors.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The evolution of the squall line in the MERGER simulation parallels that of the NOMERGER simulation through approximately t = 240 min into the simulation (Fig. 4a). At this point, the northern end of the line begins to decline in intensity as it interacts with outflow from the supercell ahead of the line. By t = 250 min the supercell is located just ahead of the north end of the line (Fig. 4b), and the structure of the squall line differs considerably from the NOMERGER simulation. The convective line west of the supercell has weakened, and the rear-inflow jet is weaker and much smaller in areal extent than that produced by the NOMERGER squall line (c.f., Figs. 3b and 4b). As the supercell begins to merge with the line, simulated reflectivity associated with the northern end of the squall line weakens further (Fig. 4c), and eventually the supercell becomes the dominant feature. A strong rear-inflow jet develops just south of the merged supercell by approximately t = 280 min (Fig. 4d), leading to a bow echo developing between y = 120 and y = 160 km (Figs. 4e,f). This rear-inflow jet is generally narrower (in along-line extent) and is displaced farther south than that in the NOMERGER squall line.

Fig. 4.
Fig. 4.

As in Fig. 3, but for the MERGER simulation. The curved yellow and red arrows denote, respectively, the approximate locations of the supercell mesocyclone and postmerger cyclonic vortex described in the text. Criteria for identifying these are as in Fig. 3.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Throughout the NOMERGER simulation a cyclic pattern of line-end vortex development, occlusion and redevelopment is observed near the north end of the line (Figs. 3a–f). In the MERGER run, however, the initial line-end vortex moves rearward and occludes as the merger begins (Figs. 4a–c), and a new vortex does not take its place until after the merger (Figs. 4c–f). This cyclonic vortex is farther to the south and stronger than those seen in the NOMERGER simulation (cf. curved arrows in Figs. 3c–f and Figs. 4c–f). It initially represents the remnants of the supercell mesocyclone; however, additional vorticity production within the merged system contributes to its growth and intensification, the details of which will be presented in a future manuscript. The rear-inflow jet, strong cyclonic line-end vortex, and bow echo structure remain for the duration of the MERGER simulation (Figs. 4e,f).

The simulated reflectivity structures evident during and following the supercell merger are very reminiscent of those observed for cases exhibiting the “system-scale bowing” evolution identified by FP12. This gives us confidence that the simulation is capturing the salient details of this squall line–supercell merger archetype. If the supercell is simulated in this environment without the squall line, it remains isolated through t = 300 min (Fig. 5), and does not develop into a bow echo on its own, as is sometimes observed for high precipitation supercells (e.g., Moller et al. 1990; Finley et al. 2001).

Fig. 5.
Fig. 5.

(a)–(e) As in Fig. 3, but for supercell-only simulation. (f) Maximum wind speed (m s−1, shaded) at the lowest model level accumulated over the duration of the supercell-only simulation. The black × in (f) denotes the point when the right-moving supercell splits from the initial storm and the dashed black oval indicates the region of enhanced wind associated with the right-moving supercell.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The differences in convective evolution between the MERGER and NOMERGER simulations correspond to differences in model proxies for severe weather in the respective squall lines (Fig. 6). The MERGER simulation produces a swath of strong winds, enhanced near-surface vertical vorticity, and enhanced rainfall along the portion of the squall line influenced by the MERGER, all of which are absent in this region in the NOMERGER simulation (Fig. 6). However, the two simulations appear quite similar for all three fields south of approximately y = 140 km. The supercell-only simulation also produced enhanced surface winds along its path (Fig. 5f); however, the values are not as intense as those that developed within the MERGER simulation. Simply put, the merger with a supercell appears to promote a locally more severe, damaging squall line; however, the impact is limited to the vicinity of the merger. This is in line with observations of severe weather (particularly damaging wind and tornado) reports associated with merged systems (FP12), and suggests that the merger may in fact be a preferred location for severe weather production. To better understand why this may be the case, the next section will explore the processes responsible for the evolution of the MERGER simulation.

Fig. 6.
Fig. 6.

Swaths of (a),(b) maximum wind speed (m s−1, shaded) and (c),(d) vertical vorticity (s−1, shaded) at the lowest model level, and (e),(f) rainfall (mm, shaded) accumulated between 3 and 6 h into the (a),(c),(e) MERGER and (b),(d),(f) NOMERGER simulations. Dashed black ovals denote the regions of enhanced fields in the MERGER simulation. The black × in each panel denotes the relative location of the merger, defined as the onset of the permanent union of the 40-dBZ contour between the squall line and supercell, which occurred at t = 265 min into the MERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

4. Storm-scale processes

a. Cold pool evolution

In their observations of squall line–supercell mergers, FP12 repeatedly observed a weakening of the squall line near the onset of the merger, and the key features of the supercell remained identifiable well after the completion of the merger. This is in line with mesonet data analyzed by Goodman and Knupp (1993) that revealed an apparent “distortion” of the squall line’s gust front during a merger with a nearby supercell. These observations suggest that the supercell in some way alters the characteristics of the squall line’s gust front; however, the details of this evolution are not clear. To better understand these interactions, we will explore the evolution of the squall line’s cold pool in the present simulations.

The evolution of the cold pool in the MERGER simulation is summarized in Figs. 7 and 8. By t = 225 min the squall line is characterized by a largely homogeneous cold pool with an average potential temperature perturbation of −9 K (Fig. 7a), and depth of 2000 m (Fig. 8a) that is producing an unbroken region of “slabular” (James et al. 2005) gust front lifting (e.g., w > 5 m s−1 at 1 km AGL; Fig. 7f). As the supercell develops and matures, it produces a shallow (average depth of 500 m; Fig. 8b) cold pool in its wake, characterized by an average potential temperature perturbation of −4 K (Fig. 7a). As this cold pool expands, it begins to interact with the squall line’s gust front by approximately t = 235 min (Fig. 7b), leading to a rapid removal of the low-level potential temperature gradient along the squall line’s gust front (Figs. 7c–e). Additionally, prior to disappearing completely, the strongest potential temperature gradient appears to lag to the west slightly (dashed oval in Fig. 7c) compared to the more continuous arc present at earlier times (e.g., Fig. 7b). This would appear to be similar to the distortion of the squall line’s gust front observed in the merger case studied by Goodman and Knupp (1993).

Fig. 7.
Fig. 7.

(a)–(e) Surface θ′ (K, shaded contours) and (f)–(j) 1 km AGL w (m s−1, shaded) and −2-K θ′ (black contour) between 225 and 265 min into the MERGER simulation. Dashed black ovals denote the weakened squall-line gust front in (c),(d),(h), and (i).

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Fig. 8.
Fig. 8.

(a)–(d) Vertical cross section of θe (K, shaded), θ′ (K, colored contours), w (white contours every 5 m s−1 starting at 5 m s−1), and wind vectors [sample vector to the right of (c)] averaged from y = 150 to 175 km at t = (a) 225, (b) 245, (c) 255, and (d) 265 min into the MERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The removal of the low-level gust front potential temperature gradient brings about a concurrent decline in near-surface lifting along the squall line’s gust front in this region as well (Figs. 7h–j). Farther aloft (between approximately 500 and 2000 m AGL), the squall line initially continues to ingest high-θe air (Figs. 8b,c) from a layer above the supercell’s cold pool. However, despite the presence of an elevated layer of favorable inflow, the squall line continues to decline in intensity (e.g., Fig. 4b). This appears to be due to a decline in the strength of the line-normal vertical wind shear over the depth of the gust front as a result of the supercell perturbing the local environment. This can be seen through a visual examination of the wind vectors immediately ahead of the squall line (e.g., at approximately x = 190, 210, and 215 in Figs. 8a, 8b, and 8c, respectively) and is quantified in Table 1. Vertical wind shear is reduced by nearly half over the depth of the initial squall-line cold pool (0–2 km AGL; Table 1) as the squall line encounters the supercell, and even more substantially if just the elevated inflow layers are considered (0.5–2 and 1–2 km AGL; Table 1). These layers likely become increasingly important as the near-surface layer stabilizes in response to the supercell’s cold pool (French and Parker 2010).

Table 1.

Squall-line-normal, low-level bulk wind difference (ΔU) between t = 225 and t = 225 min into the MERGER simulation. Values represent averages between y = 150 and y = 175 km taken at the x positions indicated.

Table 1.

Over time the squall-line updraft tilts more dramatically rearward over its cold pool (e.g., Fig. 8c). This is consistent with the cold pool overwhelming the low-level shear, which is detrimental to low-level lifting and squall-line maintenance (Rotunno et al. 1988). Thus, the weakening low-level shear ahead of the squall line likely contributes to an overall decline in the gust front updraft associated with the premerger squall line, leading to the observed weakening.

In short, the interaction between the squall line and the low-level outflow and local wind perturbations associated with the supercell lead to a decline in convective intensity along the northern part of the line (e.g., Fig. 4b). This is consistent with FP12’s frequent observations of the squall-line weakening or “breaking” prior to the merger. During this same period, a new unbroken region of low-level ascent becomes established farther east, extending south from the supercell and connecting with the squall line’s gust front south of y = 140 km (Figs. 7h–j). In other words, the supercell becomes the new leading edge of the northern portion of the squall line. Thus, instead of the supercell merely being overtaken by the squall line with little change in overall system structure (as will be shown for mergers in a weaker wind shear environment in section 5), it instead promotes a considerable change in squall-line intensity and organization, as was observed repeatedly by FP12.

b. Bow echo development

The development of the bow echo in the present simulations is a result of processes common to bow echo formation; what is unique is that these processes occur in direct response to the supercell merger. Following the merger, the subsequent development of the bow echo bears many similarities to the well-documented evolution from high-precipitation (HP) supercells to bow echoes (e.g., Moller et al. 1994; Finley et al. 2001; Klimowski et al. 2004). As the weakening squall line approaches the rear flank of the supercell there is a rapid increase in convective intensity and upward vertical velocity along the rear-flank gust front extending southwestward from the supercell (often referred to as the “flanking line”; Figs. 9a–c). This intensification occurs as the cold pool initially associated with the squall line overtakes the supercell’s cold pool and deepens to approximately 3 km deep (Figs. 9d–f). This is deeper than the initial squall line (2-km depth; Fig. 9d) and supercell (1.5-km depth; Fig. 9d) cold pools, and it is also deeper than the cold pool farther south along the squall line (e.g., y = 135 km, approximately 1.5 km deep, not shown). This deeper cold pool facilitates strong low-level lifting (Houston and Wilhelmson 2011) as it encounters favorable low-level wind shear and high θe air ahead of the now merged system (e.g., Fig. 8d), leading to the rapid intensification of deep convection.

Fig. 9.
Fig. 9.

(a)–(c) Simulated radar reflectivity (shaded, dBZ), and w at 2.5 km AGL [colored contours, m s−1, color scheme shown on right side of (f)]. (d)–(f) Along-line averaged θ′ (K, shaded) and w [contours as in (a)–(c)] averaged between y = 145 and y = 155 km [horizontal black lines in (a)–(c)]. Plots are at (left to right) t = 255, 265, and 275 min into the MERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The heavy precipitation associated with this increase in convection locally enhances the cold pool even further (surface potential temperature perturbation 4 K colder than surrounding portions of the system’s cold pool) by t = 285 min (Figs. 10a,c,e). As discussed by James et al. (2006), such a localized intensification of the cold pool is favorable for bow echo development, as it causes a portion of the squall line to locally overwhelm the ambient wind shear and accelerate, producing the bow shape in the system’s gust front. Indeed, in the present simulations the region of colder outflow south of the supercell’s updraft begins to accelerate eastward, signaling the onset of bow echo formation (Fig. 10e). This locally intense cold pool is also colder than the cold pool produced in the NOMERGER simulation during its period of bow echo development, which occurred earlier in the simulation (Figs. 10b,d,f).

Fig. 10.
Fig. 10.

Surface θ′ (K, shaded), and 1 km AGL simulated radar reflectivity (black contours at 45 and 50 dBZ) at t = (a) 280, (c) 285, and (e) 290 min into the MERGER simulation and t = (b) 255, (d) 260, and (f) 265 min into the NOMERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Another key feature in the development of the bow echo is the rapid acceleration of a narrow rear-inflow jet [RIJ; a common feature in bow echoes; e.g., Fujita (1978); Przybylinski (1995); Wakimoto (2001)] in the vicinity of the merger (Figs. 4d–f). This RIJ is more localized in the along-line direction than the broad jet that characterizes the NOMERGER squall line and forms in response to a localized region of strongly depressed pressure that develops aloft (approximately 2.5 km AGL) following the merger, extending south from the merged supercell (Figs. 11a,c,e). This negative pressure perturbation develops in response to the vertical buoyancy gradient2 between the strong cold pool and the strong convective heating aloft associated with enhanced convection in the vicinity of the merger (Fig. 12b). This is a common mechanism for RIJ development in squall lines (e.g., Lafore and Moncrieff 1989; Fovell and Ogura 1988; Weisman 1993; Grim et al. 2009); however, in the MERGER simulation the location and magnitude of the buoyancy gradient are directly related to the merger itself, as this drives the strengthening cold pool and deep convection. If we compare these results to the NOMERGER simulation, we find that the NOMERGER squall line maintains a broad RIJ (Fig. 3), which reflects a system-scale region of lower pressure near the leading edge of the line (Figs. 11b,d,f). Furthermore, while the perturbation pressure values are similar between the MERGER and NOMERGER simulations, there is a much stronger gradient in the MERGER case, resulting in a larger acceleration and stronger RIJ (Fig. 11).

Fig. 11.
Fig. 11.

Pressure perturbation (hPa, shaded) and wind vectors (m s−1, scale vector at lower right) at 2.5 km AGL, and 45- and 50-dBZ simulated radar reflectivity contours at 1 km AGL at t = (a) 270, (c) 285, and (e) 290 min into the MERGER simulation and t = (b) 245, (d) 260, and (f) 265 min into the NOMERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Fig. 12.
Fig. 12.

Structure of pressure perturbations in MERGER simulation at t = 282 min. (a) Plan view of pressure perturbations (hPa, shaded) and winds at 2.5 km AGL. (b) Vertical cross section of buoyancy (m s−2, shaded), pressure perturbation (black contours every 1 hPa with 0 contour omitted and negative values dashed white), and winds. The dashed line in (a) denotes the plane of the cross sections in (b). In both panels, wind vectors >20, >25, and >30 m s−1 are colored black, blue, and red, respectively.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

As the bow echo matures, it is further enhanced by a pair of counter-rotating vortices at the north and south ends of the bow (Figs. 4d–f). The northern, cyclonic vortex appears collocated with the merged supercell, while the southern, anticyclonic vortex has persisted from the premerger squall line. The vortices serve to further enhance the RIJ as it expands and intensifies (e.g., Weisman 1993). As with the buoyant pressure perturbations, the bookend vortices in the MERGER simulation are stronger than those observed in the NOMERGER run, and are located closer together, implying that they would have a larger positive effect on the RIJ.

To summarize the development of the bow echo post-merger, the role of the merger is to locally strengthen the cold pool of the merged system by increased precipitation. The strengthened cold pool causes the gust front to locally bow eastward and promotes the development of a strong RIJ via buoyant pressure perturbations associated with latent heat release in the convective line. This jet is further enhanced by a pair of counter-rotating vortices that intensify following the merger. The localized nature of the strengthened cold pool and RIJ produce a more compact bow echo than seen in the absence of the merger. These processes are common to bow echoes; however, in this case the merger instigates and amplifies the processes to produce a locally stronger bow echo.

c. Damaging wind production

In addition to the pronounced bowing that evolves, another key feature of the MERGER simulation is the production of a broad swath of very strong surface winds associated with the merged system (Fig. 6a). This finding compares well with the observations of FP12, who found that severe wind reports were maximized postmerger in squall line–supercell merger cases.

An analysis of the trajectories of parcels3 launched during the MERGER simulation reveals two primary source regions for air parcels that end up in the regions of strong winds at the lowest model level as the merger commences (Fig. 13). These include low- and midlevel parcels (Fig. 13, orange and blue trajectories, respectively) that descend while curving cyclonically into the system from the north, and midlevel parcels (Fig. 13, green trajectories) that descend toward the surface from the rear of the squall line. The first region represents parcels that are moving through the remnant supercell and descending through the remnant rear-flank downdraft (RFD), as the trajectories resemble the RFD parcels from past studies of simulated supercells (e.g., Wicker and Wilhelmson 1995; Adlerman et al. 1999; Xue 2004; Dahl et al. 2012). Early in the merger process, the majority of parcels originate in this region, and terminate either in a localized region of strong winds that is associated with a downburst (e.g., Fujita 1985) within the RFD of the merged supercell or in the broader swath of severe wind farther south (Fig. 13).

Fig. 13.
Fig. 13.

(bottom left) Plan view, (top) x–z cross section, and (bottom right) y–z cross section of 30-min-forward parcel trajectories ending at t = 285 min into the MERGER simulation that passed through regions of near-surface winds > 30 m s−1 between t = 280 and t = 285 min. The starting point for each trajectory is denoted by an open circle, with the trajectory colors signifying three parcel source regions of interest: green parcels originated to the rear of the squall line (RIJ), and orange and blue parcels originated in the low levels (0–2 km AGL) and midlevels (2–4 km AGL) in the vicinity of the remnant supercell, respectively. Total counts of each parcel type are shown (by color) in the top right. Shading in the plan view plot denotes maximum surface wind speed during the 280–285-min window (m s−1, shaded) and the 45-dBZ simulated radar reflectivity contour (purple). Only a subset of the parcels is plotted for clarity.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The second region (green trajectories) is consistent with air parcels within the squall line’s rear-inflow jet descending to the surface, and is a common feature in squall-line and bow echo flow fields. Early in the merger process (e.g., the trajectory window from 255–285 min into the simulation), these parcels are primarily associated with a broad region of less intense strong winds generally south of the merger location (Fig. 13). What is significant during this time is that the trajectories are spread out over a comparatively broad region with minimal overlap, particularly between the orange and green trajectories. This implies that there are initially two mechanisms producing severe winds during the early evolution of the merger—the remnant RFD within the supercell and a descending RIJ from the squall line—both of which are producing strong near-surface winds in different portions of the merged system.

The onset of severe wind production within the remnant RFD appears to be a result of an intensification of the downdraft during the merger. The remnant RFD intensifies in response to heavy precipitation developing along the rear flank of the supercell as it merges with the squall line, and there also appears to be some phasing of the RFD with preexisting downdrafts associated with the initial squall line (Figs. 14a–c). The link to the merger is apparent as the RFD observed at a similar time in the supercell-only simulation was weaker in intensity and smaller in areal extent (not shown). The severe winds associated with the RIJ during this period appear as a result of an intense, expansive downdraft (Fig. 14c) associated with the leading convective line transporting the high-momentum RIJ air to the surface. The severity is likely due to the RIJ itself intensifying during this period, as discussed in the previous section.

Fig. 14.
Fig. 14.

(a)–(c) As in Figs. 9a–c, but for w < 0 [m s−1 color scheme at right side of (c)], at t = (a) 260, (b) 275, and (c) 280 min into the MERGER simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Over time, as the bow echo structure takes shape, the strongest near-surface winds become concentrated into a narrow swath as shown in Fig. 6a. The air parcels within this swath originate in the same two source regions discussed above; however, the details of the trajectory paths have changed (Fig. 15). First of all, there is considerable overlap between the trajectories from both regions (i.e., they are both contributing to the same swath of surface winds; Fig. 15). Second, a considerably larger fraction of the parcels at this point are sourced in the descending rear inflow, suggesting that the main mechanism for the elongated swath of surface winds is the descending rear-inflow jet. Finally, the path of the northern (orange and blue) parcels appears consistent with parcels wrapping around the developing line-end vortex and ascending the northern flank of the merged system’s cold pool prior to descending in a system-scale downdraft toward the surface. This implies that the remnant RFD associated with the supercell is no longer a distinct feature as the supercell and squall line have merged into a coherent system.

Fig. 15.
Fig. 15.

As in Fig. 13, but for 30-min trajectories ending at t = 315 min into the merger simulation.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Since most of the parcels during this period are sourced from the RIJ region, this likely represents the primary mechanism responsible for the severe surface winds. The additional air wrapping into the system from the line-end vortex then serves to further accelerate the low-level winds owing to the additive effect of the rotational flow on the RIJ. This is akin to the enhancement of an RIJ by bookend vortices described by Weisman (1993) or the acceleration of near-surface winds by mesovortices (e.g., Trapp and Weisman 2003; Wakimoto et al. 2006; Atkins and St. Laurent 2009a). The result is a localized swath of very strong surface winds that follows the track of the descended RIJ and the southern flank of the line-end vortex associated with the merged system.

The importance of the merger in creating the above conditions is underscored by the lack of a similar region of severe winds within the NOMERGER simulation (cf. dashed ovals in Figs. 6a,b), which is due to the RIJ remaining elevated in that run (Figs. 16a–c). The descending RIJ in the MERGER simulation is located within a broad (across-line dimension), persistent region of heavy precipitation (Figs. 16d–f) that develops in response to the storm merger. This heavy precipitation produces a persistent region of downward vertical velocity that penetrates nearly to the surface in the same region, facilitating the descent of the RIJ (Figs. 16d–f). During this same time, the region of maximum bowing in the NOMERGER simulation is characterized by a much narrower (across line) region of heaviest precipitation, and it is less intense than that in the MERGER run (Figs. 16a–c). Most of the downdraft activity remains above 1 km AGL, which results in the RIJ remaining elevated as well (Figs. 16a–c).

Fig. 16.
Fig. 16.

Vertical cross sections of along-line-averaged hydrometeor mixing ratio (sum of rainwater, graupel, cloud water, cloud ice, and snow mixing ratios, kg kg−1, shaded), horizontal wind speed (m s−1, gray contours with 30 m s−1 contoured in red), and w < 1 m s−1 (vectors, scale vector at bottom right) at (left to right) t = 280, 305, and 315 min into the (a)–(c) NOMERGER and (d)–(f) MERGER simulations. Values are averaged between y = 165–175 km in the NOMERGER simulation and y = 145–155 km in the MERGER simulation to capture the regions of strongest bowing and rear inflow.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Differences in the static stability of the cold pool in the two simulations may also contribute to the differences in RIJ behavior (e.g., Weisman 1993). In the NOMERGER simulation, the cold pool is deeper on average, with the coldest potential temperature perturbations (θ′ < −10 K) extending well to the rear of the leading line (Figs. 17a–c). The cold pool in the MERGER simulation, on the other hand, contains a localized region of deep, cold air near the leading line, with a shallow layer of comparatively warm air (θ′ > −6 K) extending toward the rear (Figs. 17d–f). The warmer and shallower cold pool represents a less stable environment where there is less resistance to the descent of the RIJ. As a result, the increased precipitation forces the descent of the high-momentum RIJ air to the surface. This could also be thought of in terms of the buoyancy force opposing the downdraft within the squall line. In the absence of a deep, strong cold pool, the descending parcels remain cooler than their surrounding environment, resulting in less positive buoyancy to decelerate the downdraft, which allows the RIJ to descend. The difference in cold pool characteristics is a remnant of the initial weakening of the squall line discussed in section 4a even though the cold pool was locally stronger near the leading edge of the line (Fig. 10).

Fig. 17.
Fig. 17.

As in Fig. 16, but displaying θ′ (K) as the shaded field.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

To summarize, the descent of the RIJ in the MERGER simulation is driven by enhanced precipitation associated with the merger, occurring in the presence of a weakly stable cold pool. This is a common mechanism and condition for descending rear inflow in squall lines (e.g., Smull and Houze 1987; Yang and Houze 1995; Mahoney and Lackmann 2011). The unique element in this case is that the merger with the supercell produces the increase in precipitation that drives this process while also creating the condition leading to diminished cold pool stability. Without the merger, the RIJ does not descend in the same manner, and the resultant swath of severe surface winds does not occur.

5. Sensitivity tests

Based on the above analysis, we have shown one basic pathway to bow echo development in cases of squall line–supercell mergers. However, given the complexity of this scenario, it is worth exploring how sensitive these results are to our choices in model configuration. This section will explore the sensitivity of our results to 1) the background wind profile and 2) the location of the merger along the squall line.

a. Sensitivity to background wind profile

To explore the importance of having a background wind profile that favors right-moving supercells in promoting the development of the bow echo in the MERGER simulation, a set of additional simulations were run using unidirectional wind profiles with the vertical shear confined to the lowest 2.5 km. The first of these used a 0–2.5 km AGL bulk wind differential of 17.5 m s−1 (hereafter, the MERGER17.5 and NOMERGER17.5 simulations), sufficient to maintain the organization of the squall line while limiting the preline convection to a multicellular mode. The second set used a 0–2.5 km AGL bulk wind differential 25 m s−1 in order to organize the initial squall line into a bow echo, while producing splitting supercells ahead of the line that were much weaker and smaller than the well-organized right-moving supercell in the MERGER simulation. For both wind profiles, the squall lines weakened as they interacted with the preline convection’s outflow, and the preline storms became the new leading edge of the merged system, similar to the original MERGER simulation. However, there was no enhancement to any bowing structures. In short, following the merger, the MERGER17.5 and MERGER25 systems maintained a strong resemblance to their nonmerger counterparts (cf. Figs. 18c,d and 18e,f).

Fig. 18.
Fig. 18.

As in Fig. 4, but for the (a),(c) MERGER17.5 and (b),(d) MERGER25 simulations at t = 250 and 315 min into the simulations and the (e) NOMERGER17.5 and (f) NOMERGER25 simulations at t = 315 min into the simulations.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

While these mergers had little impact on storm organization, both merged systems did produce an increase in severe winds compared to the non-merger systems. The MERGER17.5 produced a localized region of enhanced surface winds in the vicinity of the merger (Fig. 19a), and the MERGER25 produced a similar behavior, although it was shorter lived (Fig. 19c). As in the original MERGER simulation, these intense winds are caused by an RIJ that descends in response to the increased precipitation associated with the merger (Figs. 20c,d). The shorter-lived nature of this descent in the MERGER25 case is due to the presence of a deeper and stronger cold pool that resists the descent of the rear inflow as the deep layer of cold air is more stable (Fig. 20d). In the MERGER17.5 case, the cold pool is shallower and comparatively warmer, which allows the RIJ to penetrate to the surface (Fig. 20c). Notably, the difference in cold pools is also evident in the NOMERGER17.5 and NOMERGER25 simulations as well (Figs. 20a,b). This is likely due to the differences in system intensity that result from the different wind profiles (the 25 m s −1 simulations produce stronger squall lines with and without the merger).

Fig. 19.
Fig. 19.

Maximum wind speed (m s−1, shaded) at the lowest model level accumulated between t = 3 and 7 h into the (a) MERGER17.5, (b) NOMERGER17.5, (c) MERGER25, and (d) NOMERGER25 simulations. The red × marks the merger location; regions of strong winds associated with the merger are highlighted by the dashed oval.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Fig. 20.
Fig. 20.

As in Fig. 17, but for the (a) NOMERGER17.5, (b) NOMERGER25, (c) MERGER17.5, and (d) MERGER25 simulations.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

b. Sensitivity to merger location

To investigate how storm evolution is impacted by mergers at different locations along the squall line, a series of experiments were run where the y position of the initial bubble used to trigger the supercell was varied between y = 60 and y = 210 km in increments of 30 km. This resulted in six additional simulations. To save on computational resources, these simulations were run with a horizontal grid spacing of 750 m, but were otherwise identical to the aforementioned MERGER simulation, save for the changed bubble location. The MERGER and NOMERGER simulations were rerun at the coarser grid spacing as well, and all of the salient features discussed in the previous sections were maintained. In this section the MERGER and NOMERGER labels will refer to the 750-m grid spacing runs, and the sensitivity tests will be labeled based on the y location of the bubble to trigger the supercell: Y60, Y90, Y120, Y150, Y180, and Y210. For reference, the bubble in the original MERGER simulation was located at y = 140 km.

The impact of the merger varies with its position along the line, both in terms of its impact on storm evolution (Fig. 21) and its role in producing potentially severe weather (Fig. 22). When the supercell was positioned to the extreme north end of the line (Y180, Y210), the effects on squall-line structure were minimal, and severe weather production was comparable to the NOMERGER simulation (not shown). In these cases, while the supercell interacted with the initial squall line, it was much more of a “glancing blow” compared to the MERGER simulation and the other tests listed below.

Fig. 21.
Fig. 21.

As in Fig. 4, but for the (a),(b) Y150; (c),(d) Y120; and (e),(f) Y90 simulations at the times indicated. The red × marks the merger location.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

Fig. 22.
Fig. 22.

Maximum wind speed (colored shading, m s−1) at the lowest model level accumulated between t = 3 and 7 h into the (a) NOMERGER, (b) MERGER, (c) Y150, (d) Y120, (e) Y90, and (f) Y60 simulations. The red × marks the merger location in (b)–(f).

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The Y150 simulation initially proceeded in a very similar fashion to the MERGER run (the MERGER supercell was triggered at y = 140 km). The merged system evolves into a pronounced bow echo south of the merger location with a well-defined line-end vortex (Figs. 21a,b). The primary difference from the MERGER simulation is that the evolution to the bow echo proceeds faster and the merged system fails to produce a large swath of enhanced surface winds (Fig. 22c). This difference is the result of less disruption to the squall line in the Y150 simulation compared to the MERGER run (as discussed in section 4a). With the supercell shifted farther north, the squall line maintains a strong low-level updraft, and with it, intense convection as the supercell merges (Figs. 23a–d). The merger promotes an increase in vertical motion to the south of the merged supercell, as seen in the MERGER simulation; however, the change in cold pool depth is less pronounced (not shown). Rather, it appears that the increase in updraft strength is due to the merging of the supercell and squall-line gust front updrafts (Fig. 23c) as described in past studies of cell mergers (e.g., Westcott 1994; Kogan and Shapiro 1996). The large latent heat release associated with the strong updraft helps to further enhance the developing RIJ and promote bowing.

Fig. 23.
Fig. 23.

As in Figs. 9a–c, but for Y150 simulation at t = (a) 255, (b) 260, (c) 275, and (d) 295 min.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

A crucial difference between the MERGER and Y150 runs is that in the Y150 simulation the merger occurs north of the coldest portion of the squall line’s premerger cold pool (e.g., Fig. 24b), minimizing the disruption to the cold pool lifting and forward motion. As a result, the cold pool in the Y150 simulation remains colder and deeper during the merger (Fig. 24d), and the merger only serves to strengthen this cold pool further (Fig. 24f). This strong cold pool inhibits the descent of the RIJ, as the Y150 cold pool is deeper and more stable than that in the MERGER simulation (not shown). By way of comparison, in the MERGER simulation the supercell merges near the coldest portion of the premerger cold pool (Fig. 24a), leading to a more significant weakening of the existing cold pool and disruption of bow echo formation (Fig. 24c). The resultant cold pool is comparatively weaker and shallower (Fig. 24e), permitting the RIJ to descend.

Fig. 24.
Fig. 24.

As in Fig. 10, but comparing the (a)–(c) MERGER and (d)–(f) Y150 simulations.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The Y120 simulation departs more significantly from the MERGER run (Figs. 21c,d). Outflow from the preline supercell leads to a decline in intensity along the central portion of the squall line (between y = 140 and y = 180 km) similar to what was discussed in section 4a for the MERGER run (not shown). This diminishes the initial RIJ associated with the squall line and limits any bowing as the merger begins (Fig. 21c). As the merger progresses however, a new RIJ develops farther south associated with intense convection produced by the merger (Fig. 21d). This new RIJ creates a pronounced spearhead echo (e.g., Fujita and Byers 1977; Fujita 1978) immediately south of the merger location (Fig. 21d), which later expands to produce a strong bow echo, south of where the bow echo was observed in the MERGER simulation. Given the absence of a strong pre-existing RIJ in the vicinity of the merger—the pre-existing RIJ was north of the supercell and decayed as the merger took place—the development of rear inflow and subsequent bowing appear to be entirely merger generated. The postmerger morphology in this case bears a strong resemblance to the “embedded bowing” structure observed by FP12, lending credence to their speculation that merger location may be an important determinant of the different modes of postmerger evolution.

When the merger occurs near the southern end of the squall line (the Y90 and Y60 simulations), the subsequent storm evolution changes yet again. In both simulations, the merger is preceded by a “break” in reflectivity along the squall line (Fig. 21e), similar to what was observed in the embedded bowing cases of FP12. This break creates two line segments. The southern segment is associated with the merged supercell, which evolves into an embedded HP supercell structure as it merges with the line and later produces localized bowing (Figs. 21e,f). The postmerger bowing in the vicinity of the merger is less pronounced in these cases, owing to a lack of organized rear inflow (Fig. 21f). The northern segment evolves into an intense, nearly symmetric bow echo in the Y90 simulation (Fig. 21f), and a similar but slightly more asymmetric structure in the Y60 simulation (not shown). The bowing of the northern segment is tied to the development of an anticyclonic line-end vortex just north of the break in the premerger squall line. Essentially, the break creates a new “line end” at the southern flank of the northern line segment. This results in a gradient in vertical velocity that promotes line-end vortex formation through the tilting of system-generated horizontal vorticity as shown by Weisman and Davis (1998).

The addition of this anticyclonic vortex works in concert with a pre-existing cyclonic northern line-end vortex to create the more dramatic, nearly symmetric bowing structure as shown by Weisman (1993). This bowing is more pronounced than in the MERGER and NOMERGER simulations because the cyclonic and anticyclonic bookend vortices are closer together, producing a larger additive effect on the RIJ (e.g., Weisman 1993). Notably, the strongest near-surface winds in the Y90 and Y60 simulations occur along and south of the merger, associated with the HP supercell and weaker bowing (Figs. 22e,f). Farther north, while the RIJ is observed to intensify and the bowing is more pronounced, there is no mechanism to facilitate its descent, and thus there is little production of strong surface winds.

From the foregoing discussion, it is clear that the ultimate impact of the merger on squall-line evolution varies strongly with merger location. Mergers that occur near the apex of the strongest premerger RIJ ultimately lead to the largest change in squall-line organization and generally more compact, dramatic, bowing (e.g., the MERGER, Y150, and Y120 simulations). As the merger is displaced north of this region the impacts diminish, with the Y180 and Y210 simulations producing squall lines that are qualitatively quite similar to the NOMERGER simulation through most of their lifetimes. Mergers that occur south of the apex trend toward structures that are more like an embedded HP supercell. In these cases a merger-induced line break facilitates stronger bowing within the line segment north of the merger; however, the strongest severe winds still occur south of the merger. As noted above, these results broadly support the speculation of FP12 that the different modes of bow echo they observed may have been tied to the location of the merger along the squall line. In particular, these results are consistent with FP12’s embedded bowing mode occurring for mergers near the center of a long squall line, while the system-scale bowing is more favorable for mergers near the northern end of the line.

These tests also demonstrate that postmerger severe weather production varies with merger location as well. Additional severe wind production beyond that occurring in the NOMERGER simulation was not observed for mergers occurring near the northern end of the squall line (the Y150, Y180, and Y210 simulations). Farther south, however, severe winds were generally enhanced along a swath that followed the track of the merged system. This was either the result of the merger enhancing a developing bow echo by strengthening and facilitating the descent of the RIJ to the surface following the merger (e.g., the MERGER and Y120 simulations) or due to the presence of embedded HP supercells within the squall line (e.g., the Y90 and Y60 simulations). In other words, provided the merger occurs away from the northernmost portion of the squall line, there appears to be a high likelihood it will represent a region of enhanced severe wind production. Notably, as time increases following the merger, the simulations begin to converge toward very similar bow echo structures in terms of scale, intensity of the RIJ, and even location (not shown). This implies that there is a limited memory of the merger (on the order of 1–2 h) after which the background environment becomes the primary control on convective organization.

c. Additional sensitivities

The simulations in this study, including the sensitivity tests discussed above, were designed to mimic the evolution that results when a supercell merges with a well-organized, mature squall line. In particular, the baseline MERGER and NOMERGER runs were set up to mimic FP12’s system-scale bowing archetype, their most commonly observed evolution. Seeing as the processes related to both the postmerger evolution and severe wind production are strongly tied to the evolution of the cold pool and other convective-scale structures in the squall line, it is likely that variations in convective-scale organization could have significant effects on the outcome of a merger. Indeed, some limited testing of the impacts of the maturity of the squall line on postmerger evolution revealed that if the supercell (and its associated higher shear environment) was introduced an hour into the squall-line simulation (the supercell was introduced after 3 h in the MERGER simulation), the merger scenario differed considerably. The initial squall line decayed over a much wider area and the supercell remained isolated for over 2 h (it merges in under 90 min in the MERGER simulation). More notably, the merger did not contribute to bow echo development or severe surface winds. In fact, this earlier merger produced a smaller area of severe surface winds compared to a similarly configured non-merger simulation, opposite what was seen when comparing the original MERGER and NOMERGER runs.

A detailed evaluation of all possible sensitivities is beyond the scope of this study; however, we included this additional test to illustrate that a wider range of outcomes of these types of mergers is likely depending on initial storm structures. Other model configurations, such as varying the relative storm motions (speed and direction) may also be important to the final outcome of the merged system. Such additional testing could represent some useful avenues for future work.

6. Summary and conclusions

A series of idealized simulations have been run to explore the storm-scale processes associated with the development of bow echo structures following a merger between a squall line and an isolated supercell. These processes are summarized in Fig. 25. Prior to the two storms merging, outflow from the supercell drives a weakening of the squall line, and the supercell plays a dominant role in the merger process. Bow echo formation begins shortly after the merger as a local strengthening of the cold pool and rear-inflow jet cause the squall line to surge forward just south of the merged supercell. As the bow echo matures, the locally intense rear-inflow jet descends to the surface, producing a large swath of intense surface winds. This basic evolution is in line with the observations of FP12, but we have now isolated the role of the merger, and have identified the storm-scale processes responsible.

Fig. 25.
Fig. 25.

Schematic diagram illustrating the basic squall-line evolution following a merger with a supercell. White and dark gray shaded outlines represent radar reflectivity, blue contours represent cold pool potential temperature perturbations, heavy dark arrows represent the RIJ, red curved arrows represent vortices, and the light gray shaded area represents the swath of damaging surface winds. Adapted from Fig. 7 of FP12.

Citation: Monthly Weather Review 142, 12; 10.1175/MWR-D-13-00356.1

The development of the bow echo is broadly a function of the background environment, but is strongly modulated by the presence of the merger. Bow echoes developed in both the MERGER and NOMERGER simulations; however, a stronger, more compact bow developed in the presence of the merger. This finding could have implications for severe weather production in merger cases (discussed in detail below) as smaller-scale (more compact) bow echoes have been shown to produce more wind damage than broad bow echoes (Wheatley et al. 2006).

The details of the bowing varied based on the relative location of the merger along the line. These results suggest that merger location may play an important role in determining the various modes of bow echo formation documented by FP12. The morphology captured by the MERGER simulation, with a merger near the north end of the line, appears similar to the “system-scale bowing” mode of FP12, while several of the configurations featuring mergers south of the midpoint of the squall line produced morphologies comparable to their “embedded bowing” mode. Additionally, despite a wide range of bowing structures associated with the various merger simulations (MERGER, Y60–210), if the simulations are allowed to proceed for a sufficient duration, the general trend is toward fairly uniform bowing structures overall (similar to the later stages of the NOMERGER simulation). Thus, while the merger will have an impact on the bow structure, the “memory” of this impact is somewhat limited.

Finally, the swaths of intense near-surface winds, vorticity, and heavy rainfall associated with the merged system (Fig. 6) indicate that the merger location represents an area of enhanced severe weather potential compared to other portions of the squall line. This addresses one of the key questions that remained from the observational work of FP12. Furthermore, compared with a bow echo evolving in the same environment without a supercell merger (the NOMERGER simulation), the merger results in a substantially larger, more intense swath of our model proxies for severe weather. In other words, the supercell merger may mean the difference between a severe and nonsevere bow echo for a given background environment.

The present manuscript has focused on storm evolution associated with squall line–supercell mergers primarily from the perspective of how the squall line evolves. A companion paper is being prepared that will carry out similar analyses focusing on the evolution of the supercell during this type of scenario. This future work will address the question of why there is an apparent increase in low-level storm rotation during these types of merger events, and will also explore the role that the premerger mesocyclone may play in the development of the strong line-end vortex that developed in the present simulations, and was a common feature in a number of observed merger events. Our long-range goal is to provide a complete picture of the storm-scale processes at work when squall lines and supercells merge.

Acknowledgments

The authors wish to thank Drs. Anantha Aiyyer, Gary Lackmann, and Sandra Yuter from NCSU for constructive comments on portions of this work that were completed as part of the first author’s doctoral dissertation. We also thank George Bryan of NCAR for developing, maintaining and freely distributing CM1, the cloud model used for these simulations, and Casey Davenport for her leading role in developing and refining the BSS code that was instrumental in running these simulations. This work also benefited from discussions with members of the Convective Storms Group at NCSU, particularly Johannes Dahl and Matt Morin, as well as the thoughtful and thorough reviews by Adam Houston and two anonymous reviewers. Early work on this project utilized computational resources from the Renaissance Computing Institute (RENCI) in Chapel Hill, North Carolina. This work was supported by NSF Grants ATM-0552154 and ATM-0758509 while the first author was at NCSU, and a Competitive Research Grant from the South Dakota Board of Regents.

REFERENCES

  • Adlerman, E. J., , K. K. Droegemeier, , and R. Davies-Jones, 1999: A numerical simulation of cyclinc mesocyclogenesis. J. Atmos. Sci., 56, 20452069, doi:10.1175/1520-0469(1999)056<2045:ANSOCM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., , and M. St. Laurent, 2009a: Bow echo mesovortices. Part I: Processes that influence their damaging potential. Mon. Wea. Rev., 137, 14971513, doi:10.1175/2008MWR2649.1.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., , and M. St. Laurent, 2009b: Bow echo mesovortices. Part II: Their genesis. Mon. Wea. Rev., 137, 15141532, doi:10.1175/2008MWR2650.1.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., , and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, doi:10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Calianese, E. J., , J. K. Jordan, , E. B. Curran, , A. R. Moller, , and G. Woodall, 2002: The Mayfest high-precipitation supercell of 5 May 1995: A case study. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 105–108.

  • Dahl, J. M., , M. D. Parker, , and L. J. Wicker, 2012: Uncertainties in trajectory calculations with near-surface mesocyclones of simulated supercells. Mon. Wea. Rev., 140, 29592966, doi:10.1175/MWR-D-12-00131.1.

    • Search Google Scholar
    • Export Citation
  • Dial, G. L., , J. P. Racy, , and R. L. Thompson, 2010: Short-term convective mode evolution along synoptic boundaries. Wea. Forecasting, 25, 14301446, doi:10.1175/2010WAF2222315.1.

    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, , and J. S. Evans, 2003: Proximity sounding analysis for derechos and supercells: An assessment of similarities and differences. Atmos. Res., 67–68, 117–133, doi:10.1016/S0169-8095(03)00047-4.

    • Search Google Scholar
    • Export Citation
  • Evans, J. S., , and C. A. Doswell, 2001: Examination of derecho environments using proximity soundings. Wea. Forecasting, 16, 329342, doi:10.1175/1520-0434(2001)016<0329:EODEUP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Finley, C. A., , W. R. Cotton, , and R. A. Pielke, 2001: Numerical simulation of tornadogenesis in a high-precipitation supercell. Part I: Storm evolution and transition into a bow echo. J. Atmos. Sci., 58, 15971629, doi:10.1175/1520-0469(2001)058<1597:NSOTIA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., , and Y. Ogura, 1988: Numerical simulation of a midlatitude squall line in two dimensions. J. Atmos. Sci., 45, 38463879, doi:10.1175/1520-0469(1988)045<3846:NSOAMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2008: The initiation and evolution of multiple modes of convection within a meso-alpha-scale region. Wea. Forecasting, 23, 12211252, doi:10.1175/2008WAF2222136.1.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2010: The response of simulated nocturnal convective systems to a developing low-level jet. J. Atmos. Sci., 67, 33843408, doi:10.1175/2010JAS3329.1.

    • Search Google Scholar
    • Export Citation
  • French, A. J., , and M. D. Parker, 2012: Observations of mergers between squall lines and isolated supercell thunderstorms. Wea. Forecasting, 27, 255278, doi:10.1175/WAF-D-11-00058.1.

    • Search Google Scholar
    • Export Citation
  • Fujita, T. T., 1978: Manual of downburst identification for project NIMROD. SMRP Research Paper 117, University of Chicago, 104 pp. [NTIS N78-30771/1GI.]

  • Fujita, T. T., 1985: The downburst: Microburst and macroburst. SMRP Research Paper 210, University of Chicago, 122 pp. [NTIS PB-148880.]

  • Fujita, T. T., , and H. R. Byers, 1977: Spearhead echo and downbursts in the crash of an airliner. Mon. Wea. Rev., 105, 129146, doi:10.1175/1520-0493(1977)105<0129:SEADIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gallus, W. A., Jr., , N. A. Snook, , and E. V. Johnson, 2008: Spring and summer severe weather reports over the Midwest as a function of convective mode: A preliminary study. Wea. Forecasting, 23, 101113, doi:10.1175/2007WAF2006120.1.

    • Search Google Scholar
    • Export Citation
  • Goodman, S. J., , and K. R. Knupp, 1993: Tornadogenesis via squall line and supercell interaction: The November 15, 1989, Huntsville, Alabama, tornado. The Tornado: Its Structure, Dynamics, Prediction, and Hazards,Geophys. Monogr., Vol. 79, Amer. Geophys. Union, 183199, doi:10.1029/GM079p0183.

  • Grim, J. A., , R. A. Rauber, , G. M. McFarquhar, , B. F. Jewett, , and D. P. Jorgensen, 2009: Development and forcing of the rear inflow jet in a rapidly developing and decaying squall line during BAMEX. Mon. Wea. Rev., 137, 12061229, doi:10.1175/2008MWR2503.1.

    • Search Google Scholar
    • Export Citation
  • Houston, A. L., , and R. B. Wilhelmson, 2011: The dependence of storm longevity on the pattern of deep convection initiation in a low-shear environment. Mon. Wea. Rev., 139, 31253138, doi:10.1175/MWR-D-10-05036.1.

    • Search Google Scholar
    • Export Citation
  • Houston, A. L., , and R. B. Wilhelmson, 2012: The impact of airmass boundaries on the propagation of deep convection: A modeling-based study in a high-CAPE, low-shear environment. Mon. Wea. Rev., 140, 167183, doi:10.1175/MWR-D-10-05033.1.

    • Search Google Scholar
    • Export Citation
  • James, R. P., , J. M. Fritsch, , and P. M. Markowski, 2005: Environmental distinctions between cellular and slabular convective lines. Mon. Wea. Rev., 133, 26692691, doi:10.1175/MWR3002.1.

    • Search Google Scholar
    • Export Citation
  • James, R. P., , P. M. Markowski, , and J. M. Fritsch, 2006: Bow echo sensitivity to ambient moisture and cold pool strength. Mon. Wea. Rev., 134, 950964, doi:10.1175/MWR3109.1.

    • Search Google Scholar
    • Export Citation
  • Jewett, B. F., , and R. B. Wilhelmson, 2006: The role of forcing in cell morphology and evolution within midlatitude squall lines. Mon. Wea. Rev., 134, 37142734, doi:10.1175/MWR3164.1.

    • Search Google Scholar
    • Export Citation
  • Klimowski, B. A., , M. R. Hjelmfelt, , and M. J. Bunkers, 2004: Radar observations of the early evolution of bow echoes. Wea. Forecasting, 19, 727734, doi:10.1175/1520-0434(2004)019<0727:ROOTEE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kogan, Y. L., , and A. Shapiro, 1996: The simulation of a convective cloud in a 3D model with explicit microphysics. Part II: Dynamical and microphysical aspects of cloud merger. J. Atmos. Sci., 53, 25252545, doi:10.1175/1520-0469(1996)053<2525:TSOACC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lafore, J.-P., , and M. W. Moncrieff, 1989: A numerical investigation of the organization and interaction of the convective and stratiform regions of tropical squall lines. J. Atmos. Sci., 46, 521544.

    • Search Google Scholar
    • Export Citation
  • Letkewicz, C. E., , A. J. French, , and M. D. Parker, 2013: Base-state substitution: An idealized modeling technique for approximating environmental variability. Mon. Wea. Rev., 141, 30623086, doi:10.1175/MWR-D-12-00200.1.

    • Search Google Scholar
    • Export Citation
  • Mahoney, K. M., , and G. M. Lackmann, 2011: The sensitivity of momentum transport and severe surface winds to environmental moisture in idealized simulations of a mesoscale convective system. Mon. Wea. Rev., 139, 13521369, doi:10.1175/2010MWR3468.1.

    • Search Google Scholar
    • Export Citation
  • Markowski, P., , and Y. Richardson, 2010: Mesoscale Meteorology in Midlatitudes. Wiley, 430 pp.

  • Moller, A. R., , C. A. Doswell III, , and R. Przybylinski, 1990: High precipitation supercells: A conceptual model and documentation. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, Alberta, Canada, Amer. Meteor. Soc., 52–57.

  • Moller, A. R., , C. A. Doswell III, , M. P. Foster, , and G. R. Woodall, 1994: The operational recognition of supercell thunderstorm environments and storm structures. Wea. Forecasting, 9, 327347, doi:10.1175/1520-0434(1994)009<0327:TOROST>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Przybylinski, R. H., 1995: The bow echo: Observations, numerical simulations, and severe weather detection methods. Wea. Forecasting, 10, 203218, doi:10.1175/1520-0434(1995)010<0203:TBEONS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rasmussen, E. N., , and D. O. Blanchard, 1998: A baseline climatology of sounding–derived supercell and tornado forecast parameters. Wea. Forecasting, 13, 11481164, doi:10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Richardson, Y. P., , K. K. Droegemeier, , and R. P. Davies-Jones, 2007: The influence of horizontal environmental variability on numerically simulated convective storms. Part I: Variations in vertical shear. Mon. Wea. Rev., 135, 34293455, doi:10.1175/MWR3463.1.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , J. B. Klemp, , and M. L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463485, doi:10.1175/1520-0469(1988)045<0463:ATFSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sabones, M., , E. M. Agee, , and M. Akridge, 1996: The Pulaski county and West Lafayette, Indiana, tornadoes, 26–27 April 1994: A case of supercell (mesocyclone) and squall line bow-echo interaction. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 746–750.

  • Sieveking, J. E., , and R. W. Przybylinski, 2004: The interaction of a HP supercell thunderstorm and bow echo to produce a prolonged severe wind event in east central Missouri. 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 7A.5. [Available online at https://ams.confex.com/ams/11aram22sls/webprogram/Paper81818.html.]

  • Skamarock, W. C., , M. L. Weisman, , and J. B. Klemp, 1994: Three-dimensional evolution of simulated long-lived squall lines. J. Atmos. Sci., 51, 25632584, doi:10.1175/1520-0469(1994)051<2563:TDEOSL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smith, B. T., , R. L. Thompson, , J. S. Grams, , C. Broyles, , and H. E. Brooks, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part I: Storm classification and climatology. Wea. Forecasting, 27, 11141135, doi:10.1175/WAF-D-11-00115.1.

    • Search Google Scholar
    • Export Citation
  • Smull, B. F., , and R. A. Houze Jr., 1987: Rear inflow in squall lines with trailing stratiform precipitation. Mon. Wea. Rev., 115, 28692889, doi:10.1175/1520-0493(1987)115<2869:RIISLW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., , B. T. Smith, , J. S. Grams, , A. R. Dean, , and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Storm supercell and QLCS tornado environments. Wea. Forecasting, 27, 11361154, doi:10.1175/WAF-D-11-00116.1.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., , and M. L. Weisman, 2003: Low-level mesovortices within squall lines and bow echoes. Part II: Their genesis and implications. Mon. Wea. Rev., 131, 28042823, doi:10.1175/1520-0493(2003)131<2804:LMWSLA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., , S. A. Tessendorf, , E. S. Godfrey, , and H. E. Brooks, 2005: Tornadoes from squall lines and bow echoes. Part I: Climatological distribution. Wea. Forecasting, 20, 2334, doi:10.1175/WAF-835.1.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., 2001: Convectively driven high wind events. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 255–298.

  • Wakimoto, R. M., , H. V. Murphey, , C. A. Davis, , and N. T. Atkins, 2006: High winds generated by bow echoes. Part II: The relationship between the mesovortices and damaging straight-line winds. Mon. Wea. Rev., 134, 28132829, doi:10.1175/MWR3216.1.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., 1993: The genesis of severe, long-lived bow echoes. J. Atmos. Sci., 50, 645670, doi:10.1175/1520-0469(1993)050<0645:TGOSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev., 110, 504520, doi:10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and J. B. Klemp, 1984: The structure and classification of numerically simulated convective storms in directionally varying wind shears. Mon. Wea. Rev., 112, 24792498, doi:10.1175/1520-0493(1984)112<2479:TSACON>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , and C. A. Davis, 1998: Mechanisms for the generation of mesoscale vortices within quasi-linear convective systems. J. Atmos. Sci., 55, 26032622, doi:10.1175/1520-0469(1998)055<2603:MFTGOM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., , J. B. Klemp, , and R. Rotunno, 1988: Structure and evolution of numerically simulated squall lines. J. Atmos. Sci., 45, 19902013, doi:10.1175/1520-0469(1988)045<1990:SAEONS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Westcott, N. E., 1994: Merging of convective clouds: Cloud initiation, bridging, and subsequent growth. Mon. Wea. Rev., 122, 780790, doi:10.1175/1520-0493(1994)122<0780:MOCCCI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wheatley, D. M., , R. J. Trapp, , and N. T. Atkins, 2006: Radar and damage analysis of severe bow echoes observed during BAMEX. Mon. Wea. Rev., 134, 791806, doi:10.1175/MWR3100.1.

    • Search Google Scholar
    • Export Citation
  • Wicker, L. J., , and R. B. Wilhelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 26752703, doi:10.1175/1520-0469(1995)052<2675:SAAOTD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wolf, P. L., 1998: WSR-88D radar depiction of supercell–bow echo interaction: Unexpected evolution of a large, tornadic “comma-shaped” supercell over eastern Oklahoma. Wea. Forecasting, 13, 492504, doi:10.1175/1520-0434(1998)013<0492:WRDOSB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wolf, R., , R. Przybylinski, , and P. Berg, 1996: Observations of a merging bowing segment and supercell. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 740–745.

  • Xue, M., 2004: Tornadogenesis within a simulated supercell storm. 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 9.6. [Available online at https://ams.confex.com/ams/11aram22sls/techprogram/paper_81574.htm.]

  • Yang, M.-J., , and R. A. Houze Jr., 1995: Sensitivity of squall-line rear inflow to ice microphysics and environmental humidity. Mon. Wea. Rev., 123, 31753193, doi:10.1175/1520-0493(1995)123<3175:SOSLRI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
1

While the base-state thermodynamic variables (e.g., θ0, p0, q, υ0, etc.) do not change throughout the simulation, the full variables (e.g., θ0 + θ′) do respond to the presence of the squall line, which has perturbed the far-field environment. This accounts for the changes in CAPE and CIN between Figs. 1a and 1b. If the base-state variables alone were plotted in Fig. 1b, the thermodynamic profile would be identical to Fig. 1a.

2

As can be shown using the diagnostic pressure equation [e.g., Eq. (2.131) of Markowski and Richardson (2010)], regions of buoyancy increasing with height are associated with a local minimum in perturbation pressure.

3

A set of 3 680 000 parcels were initialized within an 80 km × 80 km × 4 km box centered on the merged system at 10-min increments throughout the merger and integrated forward in time for 1 h during the simulation. Forward trajectories were chosen as they can be computed during the model run, greatly reducing errors in location compared to trajectories calculated from history files with a courser time resolution (e.g., Dahl et al. 2012).

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