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    Horizontal grids used for real-data numerical simulations of quasi-linear convective systems on (a) 6 Jul 2003 and (b) 24 Oct 2001. In each case, d01, d02, and d03 utilize 9-, 3-, and 1-km horizontal grid spacings, respectively.

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    Comparison of radar reflectivity factor at 0.5° elevation and ∼2-km AGL simulated radar reflectivity factor at (a) ∼0300 UTC (from the KOAX WSR-88D)/0130 UTC 6 Jul 2003, (b) ∼0445 UTC (from the KOAX WSR-88D)/0300 UTC 6 Jul 2003, and (c) ∼2200 UTC (from the KIWX WSR-88D)/2300 UTC 24 Oct 2001. Note the discrepancies in timing between companion panels in (a), (b), and (c), which are because of the evolution of the simulated systems.

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    Proximity sounding and hodograph from (a), (b) OAX (Omaha, NE) observations at 0000 UTC 6 Jul 2003, and from (c), (d) DTX (Detroit, MI) and (e), (f) ILN (Wilmington, OH) observations at 0000 UTC 25 Oct 2001. In (b), (d), and (f), the first four nodes along the hodograph trace correspond to 925, 850 (∼1400 m), 700 (∼3000 m), and 500 hPa (∼5700 m).

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    Images of radar reflectivity factor and ground-relative radial velocity at (a) 0.5° elevation, from the WSR-88D KOAX at 0554:13 and 0554:33 UTC 6 Jul 2003, respectively; and (b) 0.5° elevation, from the WSR-88D KIWX at 2050:19 and 2050:39 UTC 24 Oct 2001. Range rings are displayed at 60-km intervals. Inset in (a) shows storm-relative motion within the dashed box.

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    Horizontal cross sections at ∼2.0 and ∼0.4 km AGL at (a), (b) 0300 UTC 6 Jul 2003 and (c), (d) 2300 UTC 24 Oct 2001. Positive and negative vertical velocities are shown, in (a) and (c), every 5 m s−1 as solid and dashed black lines, respectively, with no zero contour. Positive vertical vorticity values are shown, in (b) and (d), every 500 × 10−5 s−1 as solid black lines. In (a)–(d), rainwater mixing ratios greater than 1, 3, and 5 g kg−1 are shaded light, medium, and dark gray, respectively, and every tenth ground-relative, horizontal wind vector is plotted. Full and half barbs denote speeds of 10 and 5 m s−1, respectively. Low-level mesovortices are denoted with an MV# on the plots at ∼0.4 km AGL. Tick marks are displayed every 20 km.

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    West–east vertical cross sections of vertical vorticity, vertical velocity, and potential temperature (see color bar) through (a) MV2 in Fig. 5b at 0300 UTC 6 Jul 2003 and (b) MV3 in Fig. 5d at 2300 UTC 24 Oct 2001. Vertical vorticity (black lines) is contoured every 400 × 10−5 s−1 with no zero contour and dashed negative contours. Vertical velocity (gray lines) is contoured very 5 m s−1, with no zero contour and dashed negative contours.

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    Approximately 400-m AGL horizontal cross section of potential temperature contours (every 4 K), vertical velocity (see color bar), and vertical vorticity contours (every 400 × 10−5 s−1, with no zero contour and dashed negative contours), at 0236 UTC 6 Jul 2003. Tick marks are plotted every 1 km.

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    Time series of parcel height (thin solid line), absolute vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line) for a representative parcel originating in the inflow. Time “0” corresponds to the release time of 0236 UTC 6 Jul 2003.

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    A forward trajectory: Time series of parcel height (thin solid line), absolute vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line) for a representative parcel originating in the inflow. Time “0” corresponds to the release time of 2130 UTC 24 Oct 2001.

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    Horizontal cross section, on the lowest model level, of (a) vertical vorticity (every 250 × 10−5 s−1, with no zero contour and dashed negative contours), at the two times indicated. (b) The inner box and “x” shows the geographic area and the center of a mesovortex at 2130 UTC, respectively. Also in (b), vertical vorticity contours (every 250 × 10−5 s−1, with no zero contour and dashed negative contours) and potential temperature contours (every 4 K). Tick marks are plotted every 20 km in (a) and every 1 km in (b).

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    Horizontal cross sections of the magnitude of the θe gradient on the lowest model level (see color bar; K m−1) at (a) 0300 UTC 6 Jul 2003 and (b) 2300 UTC 24 Oct 2001. In (a) and (b), the 1 g kg−1 rainwater mixing ratio contour is contoured (dashed line). In (a), black dots denote the positions of 40-km line-averaged cross sections shown in Fig. 16. Tick marks are displayed every 20 km.

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    Approximately 250-m AGL horizontal cross sections of equivalent potential temperature (every 4 K) at (a) 0253, (b) 0256, and (c) 0303 UTC; and of divergence/convergence contours (dashed/thin solid lines; every 400 × 10−5 s−1, with no zero contour), at (d) 0253, (e) 0256, and (f) 0303 UTC. In (a)–(c), rainwater mixing ratios between 1 and 3 g kg−1 are lightly shaded, with values greater than 3 g kg−1 darkly shaded. In (d)–(f), convergence values greater than 1200 × 10−5 s−1 are shaded. In (a)–(f), positive vertical vorticity contours are plotted every 0.005 s−1 (thick solid lines). Tick marks are displayed every 1 km.

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    Approximately 250-m AGL horizontal cross sections, at 0303 UTC of (a) positive vertical vorticity (every 500 × 10−5 s−1) and equivalent potential temperature (every 4 K); and of (b) vertical velocity contours (see color bar; areas of downdraft are enclosed by dashed contours) and horizontal vorticity vectors. A vector with a magnitude of 0.1 s−1 exactly reaches the tail of the next adjacent vector. In (a), the projections of 3D trajectories released at 0303 UTC (thin gray lines) are displayed. In (b), the projection of a 3D trajectory originating from the boundary is displayed. In (a) and (b), tick marks are plotted every 1 km.

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    Time series of (a) parcel height (thin solid line), vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line), for a representative parcel originating along the boundary; and of (b) the magnitude of the horizontal vorticity vector. Time “0” corresponds to the release time of 0303 UTC 6 Jul 2003.

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    Horizontal cross sections, at 0000 UTC 6 July 2003, of (a) CAPE for the parcel in each column with maximum equivalent potential temperature below 3000 m AGL (i.e., most unstable CAPE), (b) CIN for these same parcels, (c) every ninth 0–3-km shear vector and corresponding contours, and (d) every ninth 0–6-km shear vector and corresponding contours. In (a) and (b), every ninth ground-relative, horizontal wind vector from the lowest model level has been plotted. In (a)–(d), full and half barbs denote speeds of 5 and 2.5 m s−1 respectively; flags indicate speeds of 25 m s−1.

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    The 40-km line-averaged vertical cross sections of potential temperature and circulation vectors through the (a) northern and (b) southern ends of the system at 0300 UTC 6 Jul 2003. The horizontal components of circulation vectors are scaled such that a magnitude of 25 m s−1 exactly reaches the tail of the next adjacent vector. The maximum vertical vectors in (a) and (b) are 10.8 and 6.6 m s−1 (see bottom-right corner of each plot), respectively.

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    Mesovortex tracks for the periods (a) 0000–0400 UTC 6 Jul 2003 and (b) 2100 UTC 24 Oct–0000 UTC 25 Oct 2001. Track plots represent the sum of 10-min positive vertical vorticity fields, for values greater than 10−2 s−1, over the periods of interest. In (a), the shear-no shear line is derived from Fig. 15d.

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The Effect of Mesoscale Heterogeneity on the Genesis and Structure of Mesovortices within Quasi-Linear Convective Systems

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  • 1 Purdue University, West Lafayette, Indiana
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Abstract

This study examines the structure and evolution of quasi-linear convective systems (QLCSs) within complex mesoscale environments. Convective outflows and other mesoscale features appear to affect the rotational characteristics and associated dynamics of these systems. Thus, real-data numerical simulations of two QLCS events have been performed to (i) identify and characterize the various ambient mesoscale features that modify the structure and evolution of simulated QLCSs; and then to (ii) determine the nature of interaction of such features with the systems, with an emphasis on the genesis and evolution of low-level mesovortices.

Significant low-level mesovortices develop in both simulated QLCSs as a consequence of mechanisms internal to the system—consistent with idealized numerical simulations of mesovortex-bearing QLCSs—and not as an effect of system interaction with external heterogeneity. However, meso-γ-scale (order of 10 km) heterogeneity in the form of a convective outflow boundary is sufficient to affect mesovortex strength, as air parcels populating the vortex region encounter enhanced convergence at the point of QLCS–boundary interaction. Moreover, meso-β-scale (order of 100 km) heterogeneity in the form of interacting air masses provides for along-line variations in the distributions of low- to midlevel vertical wind shear and convective available potential energy. The subsequent impact on updraft strength/tilt has implications on the vortex stretching experienced by leading-edge mesovortices.

* Current affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Dustan M. Wheatley, NOAA/National Severe Storms Laboratory, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. Email: dustan.wheatley@noaa.gov

Abstract

This study examines the structure and evolution of quasi-linear convective systems (QLCSs) within complex mesoscale environments. Convective outflows and other mesoscale features appear to affect the rotational characteristics and associated dynamics of these systems. Thus, real-data numerical simulations of two QLCS events have been performed to (i) identify and characterize the various ambient mesoscale features that modify the structure and evolution of simulated QLCSs; and then to (ii) determine the nature of interaction of such features with the systems, with an emphasis on the genesis and evolution of low-level mesovortices.

Significant low-level mesovortices develop in both simulated QLCSs as a consequence of mechanisms internal to the system—consistent with idealized numerical simulations of mesovortex-bearing QLCSs—and not as an effect of system interaction with external heterogeneity. However, meso-γ-scale (order of 10 km) heterogeneity in the form of a convective outflow boundary is sufficient to affect mesovortex strength, as air parcels populating the vortex region encounter enhanced convergence at the point of QLCS–boundary interaction. Moreover, meso-β-scale (order of 100 km) heterogeneity in the form of interacting air masses provides for along-line variations in the distributions of low- to midlevel vertical wind shear and convective available potential energy. The subsequent impact on updraft strength/tilt has implications on the vortex stretching experienced by leading-edge mesovortices.

* Current affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Dustan M. Wheatley, NOAA/National Severe Storms Laboratory, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. Email: dustan.wheatley@noaa.gov

1. Introduction

An important unresolved issue in severe weather research is the relationship between quasi-linear convective systems (QLCSs) such as squall lines and bow echoes and the complex mesoscale environments within which they evolve. Some observational results (e.g., Klimowski et al. 2000; Przybylinski et al. 2000; Schmocker et al. 2000) suggest that mesoscale variability in the wind and thermodynamic fields due, for example, to convective outflows can significantly affect the rotational characteristics of severe QLCSs. Nevertheless, idealized numerical simulations produce apparently severe QLCSs in the absence of environmental heterogeneity.

In the idealized numerical simulations of QLCSs (e.g., Thorpe et al. 1982; Rotunno et al. 1988; Weisman 1992, 1993; Skamarock et al. 1994; Weisman and Davis 1998; Weisman and Trapp 2003; Trapp and Weisman 2003) and other convective storms, the initial conditions are supplied by a one-dimensional sounding that varies only with height; horizontal homogeneity along model vertical levels is assumed. The resultant class of solutions—while arising from an incomplete formulation of deep moist convection (see Balaji and Clark 1988)—agree with observations of highly organized, self-sustaining QLCSs (e.g., Burgess and Smull 1990; Jorgensen and Smull 1993). Many hypotheses put forth to explain the morphology, dynamics, and severe weather potential of QLCSs are derived from idealized modeling, and some have been validated by subsequent studies. For example, a growing body of observational evidence (e.g., Atkins et al. 2005; Wheatley et al. 2006; Wakimoto et al. 2006) has confirmed the role of low-level mesovortices in the production of damaging surface winds within QLCSs, as described in Trapp and Weisman (2003).

But idealized numerical simulations that develop mesoconvective systems are unable to fully document the environmental conditions affecting the life cycles of these systems, as they cannot reproduce the inherent four-dimensionality of the environment.

a. Conceptual models of storm–boundary interactions that produce tornadoes

A long series of modeling and observational studies have focused on the life cycles of convective storms in the presence of environmental heterogeneity. Consider the evidence that a kinematic boundary is at times a necessary condition for the development of nonsupercell tornadoes (e.g., Carbone 1983; Brady and Szoke 1989; Wakimoto and Wilson 1989; Mueller and Carbone 1987; Lee and Wilhelmson 1997a, b). In the conceptual model of nonsupercell tornadogenesis, small-scale circulations form along a convergence or shear boundary through the release of a horizontal shearing instability. The circulations strengthen to tornadic intensity through stretching in the updraft of overhead convection.

A preexisting1 thermal boundary has been suggested as a necessary condition for the development of significant tornadoes [i.e., F2 or greater on the Fujita damage intensity scale (Fujita 1981)]. Maddox et al. (1980) developed a physical model of boundary layer wind fields to explain the seeming natural tendency of thunderstorms to become more severe and even tornadic, upon interaction with a synoptic-scale front or external thunderstorm outflow boundary. In their conceptual model, boundary layer vertical wind profiles owing to shallow baroclinic zones enhance moisture content, convergence, and vertical vorticity, providing for tornadic thunderstorms in an otherwise unsupportive environment.

Observational studies born of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX; Rasmussen et al. 1994) have considered a number of cases where tornadogenesis via thunderstorm interactions with shallow baroclinic zones appeared likely. In particular, Markowski et al. (1998) found that nearly 70% of the significant tornadoes that occurred during VORTEX were associated in some way with external shallow baroclinic zones. Moreover, of this subset, most of the tornadoes occurred within the baroclinic zones of the boundaries, and generally within 30 km of the boundaries’ leading edges.

An issue especially in the latter observational studies is the difficulty in establishing the unambiguous effect of environmental heterogeneity, due to the lack of a homogeneous control. Toward this end, Atkins et al. (1999) used a cloud-resolving model to quantify the influence of preexisting boundaries on supercell evolution. In their control “no-boundary” run, the model was initialized in the standard way, using a single-sounding representation of a tornadic environment. Initial conditions for the second, “boundary” experiment were chosen to resemble the meteorological conditions near Garden City, Kansas, on 16 May 1995, which was characterized by a preexisting trough line. In both sets of experiments, warm thermal bubbles were used to initiate convection.

The inception and evolution of low-level rotation [i.e, significant vertical vorticity of O(10−2 s−1) within the primary updraft] within the storms simulated in the boundary runs tended to be earlier, stronger, and more persistent, when compared to the no-boundary runs. Moreover, vorticity analyses of the two storms revealed that the origin of rotation in the boundary runs differed in part from the usual conceptualization of low-level mesocyclogenesis (e.g., Rotunno and Klemp 1985; Davies-Jones and Brook 1993), in which streamwise horizontal vorticity along the forward- (rear) flank gust front is vertically tilted by the primary updraft (rear-flank downdraft). Now, the low levels on the cool-air side of the boundary were a source region for parcels rich in horizontal baroclinic vorticity, which then flowed into the updraft in a streamwise manner. This behavior was consistent in those simulated storms that propagated along the boundary, sometimes at small angles toward the warm-air side of the boundary.

By employing an otherwise idealized model with mesoscale variability in the environmental conditions, the experimental methodology of Atkins et al. (1999) and more recently Richardson et al. (2007) represent the most robust treatments of numerically simulated convective storms interacting with their heterogeneous environment. It should be noted, though, that their initial conditions are defined analytically (without enhancement by observations) to closely resemble desired environmental conditions, and significant uncertainties exist within this input, as stated by the authors. Furthermore, the interaction is also necessarily “one way,” hence, the convective scale is not permitted to modify the mesoscale, which then cannot feedback to the convective scale. For these reasons, it is uncertain whether their idealized results can be generalized to the real atmosphere.

b. Conceptual models of a QLCS interacting with its environment

At present, only a few observational studies in the literature have considered how mesoscale heterogeneities might affect the dynamics and severe weather potential of QLCSs. Collectively, Klimowski et al. (2000) and Przybylinski et al. (2000) have suggested that an isolated convective cell(s) in advance of a linear MCS, upon merger with the main convective line, plays a role in subsequent bow-echo genesis. While not a prerequisite for these types of interactions, these cells often initiate in proximity to and are indicative of a preexisting surface boundary and associated region of enhanced low-level convergence. Such mergers, albeit locally, may intensify ongoing convection, which in turn should force more intense (rainy) downdrafts. At last, a deeper (i.e., stronger) cold pool and associated region of hydrostatically induced high pressure accelerates the near-surface horizontal flow.

Analogous to the findings of Markowski et al. (1998) on supercell–boundary interactions, Przybylinski et al. (2000) suggested an association between QLCS–boundary interactions and tornadogenesis within QLCSs. Similar interaction between a QLCS and its heterogeneous mesoscale environment is noted by Schmocker et al. (2000). In this conceptual model, streamwise horizontal vorticity enhancement occurs along a preexisting, line-normal thermal boundary, where baroclinicity is appreciable. The production of cyclonic vertical vorticity occurs as parcels flow into the base of the updraft and undergo considerable vertical vortex stretching. Indeed, Przybylinski et al. (2000) noted that the development of severe weather (primarily damaging “straight-line” winds) often followed the interactions between QLCSs and preexisting surface boundaries. Moreover, they noted a near one-to-one correspondence between tornado damage (as inferred from damage surveys) and mesovortex tracks (as inferred from single-Doppler radar), which argues for the enhanced potential for QLCS tornadogenesis.

While intuitive, this mechanism for low-level rotation fails to explain the development of near-surface rotation. In fact, Davies-Jones (1982a, b) contended that such an “in, up, and out” type flow will only produce significant vertical vorticity after parcels flowing into the updraft have ascended a few kilometers. Abrupt upward turning of the streamlines, which are coincident with the vortex lines, would require uncharacteristic horizontal variations in vertical velocities over very short distances.

Results of the studies summarized above indicate the need to investigate the interactions of QLCSs with their complex mesoscale environments and the subsequent implications for the rotational characteristics of these systems. The inherent incompleteness of conventional and even experimental observations has precluded a satisfactory resolution of this scientific issue. To this end, complete data are only available in the form of numerical model fields. There are examples of numerical studies of QLCSs, such as Bernardet and Cotton (1998) and Coniglio and Stensrud (2001), that have incorporated mesoscale variability in their initial conditions, albeit through different means, but none of these studies directly consider the subsequent impact of these features on the simulated system. Largely, modeling studies of QLCSs are still limited by the use of environments that are horizontally homogeneous, despite growth in computing power and the development of advanced numerical weather prediction models. The latter numerical models, though, can be run with heterogeneous initial conditions interpolated from a large-scale analysis (e.g., the 40-km Eta analysis) for “real-data” cases, as well as a land surface model.

Thus, using real-data numerical simulations of severe QLCSs, the objectives herein are to

  1. identify and characterize the various ambient mesoscale features that modify structure and evolution of simulated QLCSs; and then

  2. determine the nature of interaction of such features with systems, emphasizing the dynamics of genesis and evolution of low-level mesovortices.

In section 2, candidate events for simulation and analysis are identified, followed by a discussion of the research methodology employed in this study. Section 3 provides an overview of the simulations. In section 4, the mechanism(s) for low-level mesovortex genesis is considered within a real-data framework, and then compared to the fundamental explanation given from an idealized perspective. The effects of meso-γ- and meso-β-scale heterogeneities on the rotational characteristics of the simulated QLCS are examined in sections 5 and 6, respectively. Finally, in section 7, the results of this study are summarized, their implications are discussed, and suggestions for future research on this topic are offered.

2. Methodology

The fully compressible, nonhydrostatic Advanced Research Weather Research and Forecasting (WRF-ARW; Skamarock 2005) version 2 is used to perform real-data numerical simulations of the mature, extensive bow echo on 6 July 2003 and the squall-line bow echo on 24 October 2001. Schemes used to parameterize physical processes include the six-class Purdue Lin microphysical scheme (Chen and Sun 2002), the Noah land surface model (Chen and Dudhia 2001), and the Yonsei University (YSU) planetary boundary scheme (Noh et al. 2003), and, for atmospheric radiation, the Rapid Radiative Transfer Model (longwave; Mlawer et al. 1997) and the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5; Dudhia) scheme (shortwave; Dudhia 1989). All simulations take account of earth’s rotation.

The initial conditions for the real-data simulations are supplied by the 40-km Eta model analysis, with boundary conditions updated on a 3-h interval using the Eta model forecasts. Model computations are performed on a parent grid and two inner or nested grids that are fully two-way interactive. The parent grid uses a horizontal grid point spacing of 9 km to allow for the influence of large-scale forcing mechanisms. The effects of deep cumulus convection are parameterized with the Kain–Fritsch scheme (Kain 2004) only on this grid. The intermediate and finest grids, with horizontal grid point spacings of 3 and 1 km, respectively, effectively provide for convective-system (Weisman et al. 1997) and cloud-resolving modeling. The placement of the intermediate grid encompasses the region of convection initiation, while that of the finest grid reflects the movement of the observed (and simulated) QLCS during it late formative and mature stages; the domain constructions for the specific cases are shown in Fig. 1. The parent grid at every coarse-grid time step specifies nested lateral boundary conditions. The vertical grid has 31 levels that are spaced less than 100 m near the surface to over 1 km at model top (i.e., the 50-hPa pressure surface).

Interpretation of the modeling results that follow is guided by our philosophical approach to real-data numerical simulations. A successful simulation must replicate the salient structural characteristics of the observed system and its proximity environment. In this regard, conventional observations are used to verify the representativeness of the results. The observed and simulated systems, though, are viewed most appropriately as corresponding, but not identical, parts. Particularly, at increasingly smaller spatial scales, the observations required to confirm the dynamical characteristics of (some) system–environment interactions produced in these simulations are not presently available. Like earlier idealized modeling studies (later verified by observations), additional case studies and confirmatory observations will be needed to further generalize insights gleaned from this initial study.

3. Overview of the simulations

a. The 6 July 2003 bow echo: A warm-season example

The bow echo of 6 July 2003, observed during the Bow Echo and MCV Experiment (BAMEX; Davis et al. 2004), is one subject of this study. This bowing convective system evolved from intense multicellular convection over northeastern Nebraska (see Fig. 2a), just downwind of a shortwave upper-level trough and beneath moderately strong flow (21 m s−1) at 500 hPa. The atmosphere in proximity to the mature system was quite unstable and moist, with ML CAPE of 3079 J kg−1 in the 0000 UTC sounding from Omaha, Nebraska, and surface dewpoints in excess of 18°C over eastern Nebraska and extreme western Iowa (Fig. 3a). Such high instability apparently compensated for the relatively weak 0–2.5-km shear of 10 m s−1 (Figs. 3a,b), thus, allowing for the formation of the strong system shown in Fig. 2b. While short-lived, the bow echo of 6 July 2003 exhibited the salient features of more organized systems—including a well-defined rear-inflow jet (RIJ), line-end vortices, and a diversity of low-level mesovortices (e.g., see Fig. 4a)—and produced tens of high wind reports [(National Climatic Data Center) NCDC 2003], with widespread F0-intensity (and more localized F1-intensity) wind damage occurring across eastern Nebraska and western Iowa.

To simulate this event, the WRF model is applied to a domain that covers the Great Plains, upper Midwest, and the lower Ohio River Valley (Fig. 1a). The model is initialized at 0000 UTC 5 July 2003, approximately 21 h before the occurrence of initial convective cells. Such a period of time is necessary for the simulated environment to evolve from an otherwise cold start, which possesses no cloud water and only that heterogeneity resolved in the initial conditions.

1) System-scale structure

Comparable to the observed severe bow echo (see Figs. 2a,b), the simulated bow echo has a structure and evolution described as follows: At approximately 2100 UTC 5 July, several individual convective cells initiate over the southwest quadrant of South Dakota, ahead of a synoptic-scale shortwave trough embedded in northwesterly flow (not shown). These convective cells move to the east-southeast and merge with ongoing convection over northeastern Nebraska (Fig. 2a). By 0130 UTC, the interaction of these cells leads to a mesoscale convective system greater than 100 km in length, as evidenced by a continuous line of simulated radar reflectivity in excess of 35 dBZ (Fig. 2a). Over the next few hours, this system grows upscale into a mature, extensive bow echo approximately 200 km in length, which moves through the Omaha metropolitan area and into western Iowa (Fig. 2b).

Although occurring 1–2 h early compared to the observations, the salient features of the observed system (rear-inflow jet, line-end vortices, etc.) are reproduced well by the WRF model at high resolution. To demonstrate this point, the system-scale structure of the simulated bow system during its mature stage, at 0300 UTC, is examined (Fig. 5a). At approximately 2.00 km AGL, a narrow zone of nearly continuous updraft occurs along the system’s leading edge. A concentrated rear-inflow jet extends tens of kilometers rearward of the active leading-line convection. Furthermore, a dominant cyclonic vortex is evidenced on the northern end of the convective system by a general cyclonic turning of the velocity vectors.

2) Subsystem-scale structure

Here the subsystem-scale structure of the simulated bow system during its mature stage, at approximately 0300 UTC, is examined (Fig. 5b). At approximately 400 m AGL, several small-amplitude waves occur along the leading edge of the cold pool (i.e., the 304-K potential temperature contour), and are collocated with low-level mesovortices. For reference, a “significant” mesovortex is one with a diameter ≥4 km (four horizontal grid intervals on d03), maximum vertical vorticity ≥0.01 s−1, appreciable vertical depth (>1 km), and general time and space coherency.

A west–east cross section through MV2 (see Fig. 5b) at 0300 UTC provides further insight into the structural characteristics of a significant mesovortex (Fig. 6a). MV2 is located within a zone of potential temperature gradient behind the advancing edge of the cold pool. The maximum vertical vorticity associated with MV2, 0.016 s−1 or approximately 1.6 times mesocyclone-scale vorticity, occurs at low levels. An earlier west–east cross section through MV2 confirms that it develops first near the surface (not shown) and builds upward to 4 km MSL. The structure and evolution of MV2, as well as other low-altitude mesovortices within this simulated bow system (for the strengths of other mesovortices, see ahead Fig. 17), are consistent with QLCS observations (e.g., Atkins et al. 2004, 2005; Przybylinski et al. 2000) and the idealized numerical simulations of (e.g., Weisman and Trapp 2003).

b. The 24 October 2001 squall-line bow echo: A cool-season example

The squall-line bow echo on 24 October 2001 is the other subject of this study. Occurring in October, this event exemplifies a severe bow echo forced at the synoptic scale by a dynamic pattern more typical of cool-season months. Ahead of a strong, migrating low pressure system over the upper Midwest, meteorological conditions across northern Indiana, southern Michigan, and surrounding areas were marginally unstable, with ML CAPE of 500–1000 J kg−1 in the 0000 UTC soundings from Detroit, Michigan, and Wilmington, Ohio (Figs. 3c,e). Large vertical wind shear was concentrated at low levels in these same soundings, with (south) southwesterly winds increasing to greater than 25 m s−1 at 1–2 km AGL (Figs. 3c–f). Within this low-instability/high-shear parameter space, an extensive, south–north-oriented squall line develops across the eastern half of the United States. This mesovortex-bearing system (e.g., see Fig. 4b) was host to 13 tornadoes across northeastern Indiana, and numerous incidents of high wind were also reported (NCDC 2001). Results of a real-data numerical simulation of this bow-echo event are summarized below.

The WRF model is applied to a domain that covers the eastern one-half of the United States (Fig. 1b). We note that the placement of the finest grid is chosen such that it covers the area of embedded bowing segments. The model is initialized at 0000 UTC 24 October 2001, approximately 18 h before convective storms.

1) System-scale structure

Comparable to the observed severe squall-line bow echo (Fig. 2c), the simulated squall-line bow echo has a structure and evolution described as follows: by 1800 UTC, convective cells associated with a strong, prefrontal convergence line organize into a linear convective system over central Illinois and southeastern Missouri (not shown). Around 2300 UTC, the main convective line extends from southern Michigan southwestward over northeastern Arkansas, as evidenced by a continuous line of simulated radar reflectivity in excess of 35 dBZ. This main convective line develops pronounced bowing segments over the northern half of Indiana and southern Michigan, each with their own rear-inflow jets (Fig. 5c). It should be noted that the timing of the simulated squall line, though, lags the observed system by about 1 h.

2) Subsystem-scale structure

At approximately 400 m AGL, a number of low-level mesovortices can be found along-line during the simulated system’s time on the finest grid (e.g., Fig. 5d). Maximum vertical vorticities associated with these mesovortices, at times, exceed 3 times mesocyclone-scale vorticity. A west–east cross section through MV3 at 2300 UTC shows its maximum vertical vorticity, like that of MV2 from the 6 July 2003 bow-echo event, occurring at low levels (Fig. 6b).

4. Analysis of low-level mesovortex genesis

a. The 6 July 2003 bow echo

The development of a significant low-level mesovortex on the finest grid is now examined. At 0300 UTC, MV2 is one of several significant mesovortices along the system’s leading edge (see again Fig. 5b). The developmental history of MV2 can be traced back to a cyclonic–anticyclonic vortex couplet some 30 min earlier (Fig. 7). At this earlier time, a nearly symmetrical (particularly in regards to vortex intensity) couplet straddles a low-level downdraft and local maximum in the rainwater mixing ratio field. This implication is that this and other mesovortices are formed as horizontal vorticity associated with the cold pool is tilted into the vertical by convective downdrafts.

To confirm the deductions from Fig. 7, consider the following form of absolute vertical vorticity equation:
i1520-0493-136-11-4220-e1
where ζa = ζ + f (θ) is the absolute vertical vorticity, θ is the latitude, ωH is the horizontal vorticity vector, w is the vertical velocity, VH is the horizontal velocity vector, and Fζ is the mixing term. The first and second terms on the RHS of the above equation represent the tilting of horizontal vorticity in the vertical and the stretching of absolute vertical vorticity, respectively. As in Trapp and Weisman (2003), the time-integrated contributions from the tilting and stretching processes in Eq. (1) are calculated along trajectories as follows:
i1520-0493-136-11-4220-e2
Here, model data predicted every 1 min are used to diagnose these forcing terms as well as ζa. Trajectories of all parcels in the vicinity of significant low-level mesovortices are considered. The total time integration period is t ≤ 10 min.

Backward trajectories are calculated for parcels spaced every 1 km within a cubic region encompassing MV2. All of the parcels originate from either the inflow or the rear of the system. Figure 7 shows a representative trajectory projected into the plane. Times series of parcel height show that the positive vertical vorticity associated with MV2 is generated in a downward current of air, as baroclinic horizontal vorticity is tilted vertically (Fig. 8). Beyond 0236 UTC, the terminus for the above trajectories, MV2 is maintained along the gust front for greater than 1 h.

b. The 24 October 2001 squall-line bow echo

Horizontal components of vorticity are quite large in the prefrontal environment—typically between 0.03 and 0.04 s−1—owing to an intense southerly low-level jet (20–25 m s−1 at ∼500 m AGL). Upward tilting of this eastward-directed horizontal vorticity generates vertical vorticity values of 0.001–0.003 s−1 at ∼250– 750 m AGL (Fig. 9). With subsequent stretching, the rate of vorticity production shown in Fig. 9 readily explains the narrow band of positive vertical vorticity along the east flank of the system-scale updraft—especially below 1 km AGL—where ζ ∼0.004 s−1.

The emergence of vorticity maxima and ultimately low-level mesovortices from this 3- (±1) km-wide vortex sheet appears to be associated with the release of a horizontal shearing instability (see, e.g., Carbone 1983; Mueller and Carbone 1987). At 2100 UTC, a number of small-scale vortices separated by ∼10–20-km distance can be found along the northern end of the squall line (Fig. 10a). (The southern end of the squall line enters this domain with well-developed vortices.) This spacing is consistent with the linear theory of Miles and Howard (1964), which predicts that the wavelength of the instabilities is ∼7.5 times the vortex sheet width, and with the idealized numerical simulations of Lee and Wilhelmson (1997a,b), which suggest that this wavelength can be roughly half this theoretical value. Further evidence of horizontal shearing instability as a mechanism for the generation of low-level mesovortices is the general lack of anticyclonic–cyclonic vortex couplets at all stages of vortex development (see Fig. 10b).

In summary, the basic mechanism for low-level mesovortex genesis within the real-data numerical simulation of the warm-season QLCS event of 6 July 2003 is dynamically equivalent to the process described within the idealized modeling framework of Trapp and Weisman (2003). As just shown, mesovortices occurring within the cool-season QLCS event of 24 October 2001 appear due to the release of a horizontal shearing instability. In each case, the genesis mechanism is in direct response to the intrinsic dynamics of the system—as suggested in the aforementioned idealized experiments—and not from some system interaction with external (from the system) mesoscale heterogeneity. This finding is significant given that such variability can arise in real-data numerical simulations without further refinement, and previous observational studies of mesovortex-bearing QLCSs have described this type of role for system–environment interactions. Subsequent sections, though, will demonstrate how preexisting heterogeneities can affect the structure and evolution of a preexisting vortex.

5. An effect of meso-γ-scale heterogeneity

When present, heterogeneity in the mesoscale environments of the QLCSs is normally revealed well in maps of the magnitude of the gradient of equivalent potential temperature (θe) (Fig. 11). In the case of the 6 July 2003 bow-echo event, one can identify two distinct scales of heterogeneity, excluding the horizontal variability in temperature associated with the system-generated cold pool (Fig. 11a). The meso-β-scale heterogeneity is related to an airmass boundary across central Nebraska and west-central Iowa, and is reserved for discussion in section 6. The meso-γ-scale heterogeneity is a nearly circular outflow boundary displaced just to the northwest of the northern end of the main convective line. This outflow is associated with a cluster of convective cells that initiated 1–2 h earlier over extreme southeastern South Dakota, and have since moved east-southeast over west-central Iowa. The southern periphery of this outflow possesses a cross-boundary θe gradient of the order of 10 K km−1, and is oriented normal to the system’s leading edge.

We now consider the effect of this mesoscale heterogeneity on the developmental history of MV1, another leading-edge mesovortex that forms during the mature stage of the simulated bow echo (see Fig. 5b). At 0253 UTC, MV1 is one of two mesovortices embedded within an elongated region of positive vertical vorticity along the northern end of the system’s leading edge (Fig. 12a). The vorticity maximum of approximately 0.01 s−1 associated with MV1 is located just on the warm-air side of the line-normal boundary. Like MV2, this mesovortex is generated via the tilting of baroclinic horizontal vorticity within a downdraft; its intensification appears to be linked to a focused region of enhanced low-level convergence, produced by the intersection of the system-generated cold pool and boundary (Fig. 12d).

Over the next few minutes, in a storm-relative framework, the boundary moves toward the south-southeast (Fig. 12b). By 0256 UTC, the local maximum in the convergence field associated with the boundary spatially corresponds with MV1 (Fig. 12e), presumably promoting the stretching and subsequent amplification of its vertical vorticity. The process of mesovortex intensification continues through 0303 UTC (Fig. 12c), after which mesovortex strength increases by nearly 200%, to nearly 0.03 s−1.

To confirm the nature of this QLCS–boundary interaction, backward trajectories were calculated for parcels within a cubic region encompassing MV1 (see Fig. 13 for their projections into the horizontal plane). The upper bound for this cubic region is the model sigma level at approximately 1 km AGL. Similar to the analysis of low mesovortex genesis in section 4, parcels within the vortex region at 0303 UTC—the time of peak mesovortex intensity—originate from the inflow and behind the gust front (Fig. 13a). In this case, though, nearly 50% of the considered parcels originate along the boundary (Fig. 13a). Horizontal cross sections of horizontal vorticity vectors show appreciable streamwise horizontal baroclinic vorticity associated with the boundary (Fig. 13b). However, as shown in Fig. 13b and confirmed in Fig. 14, tilting of such vorticity is relatively weak for parcels flowing along the boundary. For the parcel examined, the tilting process contributes no more than 0.002 s−1 (i.e., ∼10% or less) to mesovortex strength at 0303 UTC, which is representative of the lot of parcels considered. However, small amounts of vertical vorticity born in the boundary contribute to MV1, which as demonstrated is amplified by significant stretching due to the QLCS–boundary interaction. It should be noted that parcels originating farther behind the boundary begin with small amounts of negative vorticity, which tends to zero with stretching.

While significant, the QLCS–boundary interaction described above is a relatively short-lived process. Beyond 0303 UTC, the convergence maximum has moved beyond the center of circulation, which is increasingly dislocated from the leading edge of the gust front (not shown). MV1 begins to weaken in the same period of time.

To summarize, these simulation results show that the effect of the boundary is limited to the intensification of MV1.

6. An effect of meso-β-scale heterogeneity

The meso-β-scale heterogeneity in Fig. 11a is related to a low-level airmass boundary that had been quasi-stationary over east-central Nebraska and west-central Iowa for 1–2 days prior to the bow-echo event. Across this transition zone, the low-level flow is south-southwesterly over southern parts of eastern Nebraska and western Iowa, and becomes light and variable (to, at times, easterly) north-northwest of this area (shown for the simulation in Fig. 15a), producing significant convergence across central Nebraska and west-central Iowa. This east–west-oriented boundary is distinguished from the surrounding area by a relatively subtle meridional temperature gradient. Significant low-level moisture convergence occurs along and north of the boundary, as revealed by the sharper gradient in equivalent potential temperature (shown for the simulation in Fig. 11a).

A number of these environmental conditions play a significant role in both the formation and mature stages of the simulated system. For example, the pooling of moisture near the boundary and the associated destabilization helps to control the east-southeasterly orientation and motion of the initial convection storms (Figs. 2a,b). Additionally, the vertical juxtaposition of weak easterly flow at the surface and westerly flow at 700 hPa produces a belt of enhanced 0–3-km shear along and north of the boundary (Fig. 15c). The shear distribution at midlevels is qualitatively similar to the low-level distribution, with greater values occurring in proximity to the boundary (Fig. 15d). This horizontal variation in the low- and midlevel shear fields produces significant along-line variability during the mature stage of the simulated system: the northern half of the simulated system propagates through stronger shear along and north of the boundary, while its southern half propagates though the area of weaker shear south of the boundary (Figs. 15c,d). Consistent with the theoretical discussion of Rotunno et al. (1988), this configuration is supportive of deeper, stronger, and more vertically erect updrafts along the leading edge of the northern half of the simulated system (see Figs. 16a,b).

The thermodynamic conditions of the storm proximity environment also may contribute to the variations in updraft strength/tilt shown in Fig. 16. Here, the distribution of most unstable (MU) CAPE is qualitatively similar to the distributions of low- and midlevel shear, with large amounts of MU CAPE in proximity to the boundary (Fig. 15a). Also, convective inhibition (CIN) is smallest in proximity to the boundary (Fig. 15b). The environmental sensitivity experiments of Weisman (1993) found that greater system-scale organization could be promoted by simply increasing environmental CAPE (above at least 2000 J kg−1), even for relatively weak low- to midlevel shear values.

These effects of the meso-β-scale heterogeneity on the system-scale structure also have consequences on the evolution of low-level mesovortices along the leading edge of the system. The strong, erect updrafts on the northern end of the line provide greater opportunity for deep lifting and vortex stretching than do those on the southern end of the line. Not surprisingly, low-level mesovortices along and north of the boundary tend be deeper, stronger, and longer lived than their counterparts on the southern end of the line (Fig. 17a). Vertical vorticity associated with northern-end mesovortices exceeds 0.03 s−1 compared to 0.01 s−1 for mesovortices on the southern end of the line. This finding is consistent with Weisman and Trapp (2003), who noted the dependence of low-level mesovortices within squall lines and bow echoes on environmental vertical wind shear.

As a reference, it is interesting to compare mesovortex evolution in the 6 July 2003 QLCS to that in the 24 October 2001 QLCS. The numerous vortices on 24 October 2001 have strengths comparable to those occurring on 6 July 2003, yet their tracks are nearly continuous (Fig. 17b). This reflects the relatively homogeneous environment encountered by the 24 October 2001 QLCS, as illustrated by the nonexistence of a θe gradient in excess of 1 K km−1 outside of the system-generated cold pool (Fig. 11b). Hence, we can conclude that the effect of mesoscale heterogeneity appears sufficient but not necessary for the later-stage development of low-level mesovortices.

7. Summary and discussion

Real-data simulations of two severe QLCS events have been presented, with an emphasis on the relationship between these systems and the complex environments within which they evolve. The 6 July 2003 event exemplifies a warm-season bow echo, and is characterized by considerable heterogeneity on multiple scales. The 24 October 2001 event is a cool-season, squall-line bow echo that formed in the relative absence of mesoscale heterogeneity, but was strongly forced on the synoptic scale.

The simulations replicate the characteristics of highly organized, severe QLCSs, and thus capture the salient features of the observed systems. For the 6 July 2003 QLCS event, the model reproduces a mature, extensive bow echo with a horizontal scale well in excess of 100 km. On the system-scale, this simulated bow system possesses a dominant cyclonic vortex and weaker anticyclonic vortex on its northern and southern flanks, respectively, as well as a concentrated RIJ tens of kilometers rearward of the leading-edge convection. For the 24 October 2001 QLCS event, the model reproduces a more dynamically forced squall line with a horizontal scale of several hundred kilometers. Comparable with the observed system, a number of embedded bowing segments occur over the northern half of Indiana and extreme southern Michigan.

In both cases on the subsystem-scale, several low-level mesovortices with horizontal scales of 5–10 km form on the simulated systems’ leading edges. The positive vertical vorticity associated with these circulations is maximized near the surface, and extends into the midlevels of the troposphere.

External heterogeneity is shown to play no detectable role in mesovortex genesis, which runs counter to what has been suggested by previous observational studies of mesovortex-bearing QLCSs. The simulated environment on 6 July 2003 possessed meso-γ- (order of 10 km) and meso-β-scale (order of 100 km) heterogeneities in the form of convective outflow and an airmass boundary, respectively, and mesovortices occur before any significant interaction with these environmental features. With the 24 October 2001 QLCS event, mesovortices readily form within a relatively homogeneous mesoscale environment, as gauged by the magnitude of the θe gradient, and their strengths were comparable to those of its warm-season counterpart. This behavior, whereby mesovortices form as a consequence of the intrinsic dynamics of the system, is consistent with previous idealized numerical simulations of highly organized QLCSs (see Trapp and Weisman 2003).

The genesis mechanisms of the low-level mesovortices are dissimilar between the two cases. For the warm-season case, mesovortices are formed by the tilting of crosswise horizontal baroclinic vorticity in downdrafts, consistent with the idealized modeling results of Trapp and Weisman (2003). For the cool-season case, tilting of the strong environment horizontal vorticity produces a vortex sheet, within which mesovortices appear to form through the release of a horizontal shearing instability. In each case, vortex intensification is a consequence of the stretching.

Mesoscale heterogeneity can still have an effect on the dynamics of QLCSs, however. The nature of such system–environment interaction appears dependent upon the scale of the heterogeneity. In the case of the 6 July 2003 simulated bow system, a leading-edge mesovortex undergoes rapid intensification after interacting with meso-γ-scale heterogeneity in the form of convective outflow. Trajectory analysis shows the boundary to be the predominant source region for air parcels populating the vortex region at peak intensity, many of which possess horizontal vorticity of the order of 0.05 s−1. However, vertical vorticity equation analysis shows that vortex intensification owes to the stretching of vertical vorticity brought about by enhanced convergence at the point of QLCS–boundary interaction. The time-integrated contribution to vertical vorticity from the tilting term is negligible, in contrast with current conceptual models of QLCS–boundary interactions.

Meso-β-scale heterogeneity in the form of interacting air masses provides for along-line variations in the strength of low- to midlevel vertical wind shear and the amount of thermodynamic instability as the simulated bow system moves across eastern Nebraska and western Iowa. North of the airmass boundary, stronger low- to midlevel vertical wind shear, as well as larger amounts of CAPE, help to maintain lift along the gust front during the simulated system’s mature stage, despite a strengthening cold pool. This system-scale behavior feeds back onto the subsystem scale. Mesovortices north of the boundary experience deeper lifting and achieve greater maximum vertical vorticities, while those on the southern end of the line (within the nominal shear region) are weaker and shorter lived.

The present study has evidenced the effect of mesoscale heterogeneity on the rotational dynamics of QLCSs, but the nature as well as sheer number of such storm–environment interactions cannot possibly be described through analysis of two simulated events. Toward a better understanding of these processes, data assimilation experiments are now being performed with an ensemble Kalman filter (EnKF) and involve the use of routine surface and upper-air observations. This part of the study will further consider the effect of mesoscale heterogeneity from the viewpoint of system initiation, and thus will concentrate on seemingly unpredictable QLCS events in which significant mesoscale variability appears to have played a role in system initiation and/or evolution.

Acknowledgments

The authors wish to thank the three anonymous reviewers for their constructive comments. Resources made available through NCAR’s Scientific Computing Division and Purdue University’s Rosen Center for Advanced Computing were used to generate the WRF model simulations. This research was supported in part by the National Science Foundation, under Grant ATM-023344 (DMW and RJT), and by a Bilsland Dissertation Fellowship (DMW).

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Fig. 1.
Fig. 1.

Horizontal grids used for real-data numerical simulations of quasi-linear convective systems on (a) 6 Jul 2003 and (b) 24 Oct 2001. In each case, d01, d02, and d03 utilize 9-, 3-, and 1-km horizontal grid spacings, respectively.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 2.
Fig. 2.

Comparison of radar reflectivity factor at 0.5° elevation and ∼2-km AGL simulated radar reflectivity factor at (a) ∼0300 UTC (from the KOAX WSR-88D)/0130 UTC 6 Jul 2003, (b) ∼0445 UTC (from the KOAX WSR-88D)/0300 UTC 6 Jul 2003, and (c) ∼2200 UTC (from the KIWX WSR-88D)/2300 UTC 24 Oct 2001. Note the discrepancies in timing between companion panels in (a), (b), and (c), which are because of the evolution of the simulated systems.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 3.
Fig. 3.

Proximity sounding and hodograph from (a), (b) OAX (Omaha, NE) observations at 0000 UTC 6 Jul 2003, and from (c), (d) DTX (Detroit, MI) and (e), (f) ILN (Wilmington, OH) observations at 0000 UTC 25 Oct 2001. In (b), (d), and (f), the first four nodes along the hodograph trace correspond to 925, 850 (∼1400 m), 700 (∼3000 m), and 500 hPa (∼5700 m).

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 4.
Fig. 4.

Images of radar reflectivity factor and ground-relative radial velocity at (a) 0.5° elevation, from the WSR-88D KOAX at 0554:13 and 0554:33 UTC 6 Jul 2003, respectively; and (b) 0.5° elevation, from the WSR-88D KIWX at 2050:19 and 2050:39 UTC 24 Oct 2001. Range rings are displayed at 60-km intervals. Inset in (a) shows storm-relative motion within the dashed box.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 5.
Fig. 5.

Horizontal cross sections at ∼2.0 and ∼0.4 km AGL at (a), (b) 0300 UTC 6 Jul 2003 and (c), (d) 2300 UTC 24 Oct 2001. Positive and negative vertical velocities are shown, in (a) and (c), every 5 m s−1 as solid and dashed black lines, respectively, with no zero contour. Positive vertical vorticity values are shown, in (b) and (d), every 500 × 10−5 s−1 as solid black lines. In (a)–(d), rainwater mixing ratios greater than 1, 3, and 5 g kg−1 are shaded light, medium, and dark gray, respectively, and every tenth ground-relative, horizontal wind vector is plotted. Full and half barbs denote speeds of 10 and 5 m s−1, respectively. Low-level mesovortices are denoted with an MV# on the plots at ∼0.4 km AGL. Tick marks are displayed every 20 km.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 6.
Fig. 6.

West–east vertical cross sections of vertical vorticity, vertical velocity, and potential temperature (see color bar) through (a) MV2 in Fig. 5b at 0300 UTC 6 Jul 2003 and (b) MV3 in Fig. 5d at 2300 UTC 24 Oct 2001. Vertical vorticity (black lines) is contoured every 400 × 10−5 s−1 with no zero contour and dashed negative contours. Vertical velocity (gray lines) is contoured very 5 m s−1, with no zero contour and dashed negative contours.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 7.
Fig. 7.

Approximately 400-m AGL horizontal cross section of potential temperature contours (every 4 K), vertical velocity (see color bar), and vertical vorticity contours (every 400 × 10−5 s−1, with no zero contour and dashed negative contours), at 0236 UTC 6 Jul 2003. Tick marks are plotted every 1 km.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 8.
Fig. 8.

Time series of parcel height (thin solid line), absolute vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line) for a representative parcel originating in the inflow. Time “0” corresponds to the release time of 0236 UTC 6 Jul 2003.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 9.
Fig. 9.

A forward trajectory: Time series of parcel height (thin solid line), absolute vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line) for a representative parcel originating in the inflow. Time “0” corresponds to the release time of 2130 UTC 24 Oct 2001.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 10.
Fig. 10.

Horizontal cross section, on the lowest model level, of (a) vertical vorticity (every 250 × 10−5 s−1, with no zero contour and dashed negative contours), at the two times indicated. (b) The inner box and “x” shows the geographic area and the center of a mesovortex at 2130 UTC, respectively. Also in (b), vertical vorticity contours (every 250 × 10−5 s−1, with no zero contour and dashed negative contours) and potential temperature contours (every 4 K). Tick marks are plotted every 20 km in (a) and every 1 km in (b).

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 11.
Fig. 11.

Horizontal cross sections of the magnitude of the θe gradient on the lowest model level (see color bar; K m−1) at (a) 0300 UTC 6 Jul 2003 and (b) 2300 UTC 24 Oct 2001. In (a) and (b), the 1 g kg−1 rainwater mixing ratio contour is contoured (dashed line). In (a), black dots denote the positions of 40-km line-averaged cross sections shown in Fig. 16. Tick marks are displayed every 20 km.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 12.
Fig. 12.

Approximately 250-m AGL horizontal cross sections of equivalent potential temperature (every 4 K) at (a) 0253, (b) 0256, and (c) 0303 UTC; and of divergence/convergence contours (dashed/thin solid lines; every 400 × 10−5 s−1, with no zero contour), at (d) 0253, (e) 0256, and (f) 0303 UTC. In (a)–(c), rainwater mixing ratios between 1 and 3 g kg−1 are lightly shaded, with values greater than 3 g kg−1 darkly shaded. In (d)–(f), convergence values greater than 1200 × 10−5 s−1 are shaded. In (a)–(f), positive vertical vorticity contours are plotted every 0.005 s−1 (thick solid lines). Tick marks are displayed every 1 km.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 13.
Fig. 13.

Approximately 250-m AGL horizontal cross sections, at 0303 UTC of (a) positive vertical vorticity (every 500 × 10−5 s−1) and equivalent potential temperature (every 4 K); and of (b) vertical velocity contours (see color bar; areas of downdraft are enclosed by dashed contours) and horizontal vorticity vectors. A vector with a magnitude of 0.1 s−1 exactly reaches the tail of the next adjacent vector. In (a), the projections of 3D trajectories released at 0303 UTC (thin gray lines) are displayed. In (b), the projection of a 3D trajectory originating from the boundary is displayed. In (a) and (b), tick marks are plotted every 1 km.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 14.
Fig. 14.

Time series of (a) parcel height (thin solid line), vertical vorticity (small dashed line), and the time-integrated contributions to vertical vorticity (thick solid line) from the tilting (medium dashed line) and absolute vorticity-stretching terms (large dashed line), for a representative parcel originating along the boundary; and of (b) the magnitude of the horizontal vorticity vector. Time “0” corresponds to the release time of 0303 UTC 6 Jul 2003.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 15.
Fig. 15.

Horizontal cross sections, at 0000 UTC 6 July 2003, of (a) CAPE for the parcel in each column with maximum equivalent potential temperature below 3000 m AGL (i.e., most unstable CAPE), (b) CIN for these same parcels, (c) every ninth 0–3-km shear vector and corresponding contours, and (d) every ninth 0–6-km shear vector and corresponding contours. In (a) and (b), every ninth ground-relative, horizontal wind vector from the lowest model level has been plotted. In (a)–(d), full and half barbs denote speeds of 5 and 2.5 m s−1 respectively; flags indicate speeds of 25 m s−1.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 16.
Fig. 16.

The 40-km line-averaged vertical cross sections of potential temperature and circulation vectors through the (a) northern and (b) southern ends of the system at 0300 UTC 6 Jul 2003. The horizontal components of circulation vectors are scaled such that a magnitude of 25 m s−1 exactly reaches the tail of the next adjacent vector. The maximum vertical vectors in (a) and (b) are 10.8 and 6.6 m s−1 (see bottom-right corner of each plot), respectively.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

Fig. 17.
Fig. 17.

Mesovortex tracks for the periods (a) 0000–0400 UTC 6 Jul 2003 and (b) 2100 UTC 24 Oct–0000 UTC 25 Oct 2001. Track plots represent the sum of 10-min positive vertical vorticity fields, for values greater than 10−2 s−1, over the periods of interest. In (a), the shear-no shear line is derived from Fig. 15d.

Citation: Monthly Weather Review 136, 11; 10.1175/2008MWR2294.1

1

Here, the qualifiers “preexisting” and “external” refer to a thermal and/or kinematic boundary generated by a source outside the convective cell/system affected. Synoptic-scale fronts (i.e., warm fronts and stationary fronts) and old thunderstorm outflow boundaries are both examples of preexisting thermal boundaries.

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