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  • View in gallery

    Composite 500-hPa and surface analysis for 1200 UTC 19 May 2013 from Fig. 9a of Weisman et al. (2015). Winds (half barb = 2.5, full barb = 5, and pennant = 25 m s−1), annotated temperatures (°C), height contours (decameters), and wind speeds (shading) are obtained from NAM operational 500-hPa analyses. Overlaid surface low-pressure symbols, fronts, and dryline (dashed yellow line) have conventional meteorological meanings and are subjectively analyzed.

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    Oklahoma surface mesonet (Brock et al. 1995) station data from the closest available 5-min increments corresponding to the overlaid visible satellite imagery at the indicated times: (a) 1856, (b) 1938, and (c) 2033 UTC. The station model contains winds (barbs as in Fig. 1), temperature (°C, red), and dewpoint (°C, yellow). The gray horizontal line indicates 35° latitude.

  • View in gallery

    Base-level radar reflectivity (colors, dBZ) from the Twin Lakes, OK (KTLX), NEXRAD WSR-88D for (a) 2055, (b) 2220, and (c) 2350 UTC. The 8 and 12 g kg−1 vapor mixing ratio isopleths (brown lines), objectively analyzed using surface observations from the displayed locations, approximate the position of the front and rear of the surface dryline in central Oklahoma. Colored stars in (a) indicate locations and UTC times of MPEX mobile upsonde launches presented in Figs. 13b and 14.

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    The ARW Model outer horizontal domain d01 (Δ = 15 km) and two-way interactive nest d02 (Δ = 3 km) used in all 10 ensemble members, and the innermost two-way interactive nest d03 (Δ = 1 km) used in the highest-resolution simulations of ensemble members 6 and 9 presented in section 4.

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    Model-derived radar reflectivity (dBZ) at the lowest model grid point within d02 (Fig. 4) at hour 6 of the forecast for (a)–(j) each of the 10 ensemble members. The (f),(h),(j) solid and (b),(d),(i) dashed rectangles indicate the location of composite line-averaged cross sections presented in Figs. 23a,c and Figs. 23b,d, respectively.

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    Model-derived radar reflectivity (dBZ) from the lowest model grid point and its relationship to the dryline (in central Oklahoma) and frontal moisture gradient (northwest Oklahoma) approximated by the 8–12 g kg−1 surface water vapor mixing ratio isopleths (contours) in d03 (Fig. 4) of ensemble members (a),(c) 6 and (b),(d) 9 at (top) 2048 and (bottom) 2218 UTC. Colored stars in (a),(b) indicate locations and UTC times of MPEX mobile upsonde launches presented in Figs. 13b and 14.

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    Evolution of PBL horizontal winds (barbs as in Fig. 1), vertical velocity (color shading, m s−1), potential temperature (blue dashed contours, 2-K intervals), and their relationships to the surface vapor mixing ratio (black solid contours with 2 g kg−1 intervals) within d03 (Fig. 4) of ensemble members (left) 6 and (right) 9: (a),(c),(e) 1900 to 1957 UTC and (b),(d),(f) 1930 to 2115 UTC. Bold red contours indicate locations of surface model-derived radar reflectivity >35 dBZ used as an indicator of deep CI. Note that the horizontal locations of the displayed regions differ between ensemble members (left) 6 and (right) 9. The single arrow in(d) indicates the approximate location along the dryline where cells A and B in Figs. 8 and 9 are initiated.

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    Vertical velocity (color shading, m s−1) and water vapor mixing ratio (green contours with 1 g kg−1 intervals from 1 to 16 g kg−1) from d03 (Fig. 4) of ensemble member 9 along the southwest–northeast transect (SW–NE) in Figs. 9a–e. Annotations near convective updrafts within the vertical cross section identify discrete cells defined as in the caption of Fig. 9. The annotations near the bottom of the cross section locate DL1 and the intensifying secondary moisture gradient DL2 indicated in Fig. 7b and discussed in the text.

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    Relationships among evolutions in the horizontal structure of thermodynamic and kinematic variables—surface water vapor mixing ratio (brown contours, g kg−1), 5-km MSL vertical velocity (red contours, m s−1), and MUCAPE (dashed black contours, J kg−1)—and the initiation of deep convection within d03 (Fig. 4) of ensemble member 9: (a)–(i) 2018 to 2106 UTC. Updraft centers with vertical velocities that exceed 2 m s−1 at 5 km MSL for at least 12 min are labeled alphabetically in the chronological order of their development. Cells denoted by multiple letters indicate mergers of previously defined cells. The southwest–northeast transect in (a)–(e) indicates the horizontal location of the vertical cross section displayed in Fig. 8.

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    Schematic diagram from Trier et al. (2014) illustrating the buoyancy minimum (Bmin, virtual temperature units, blue line) for a surface-based air parcel (p = po) lifted to the pressure of its minimum buoyancy (p = pBmin). The gray shading indicates the vertically integrated CIN for the same surface-based air parcel between its origination level and the LFC. The red (green) curve indicates the virtual temperature (dewpoint) of the environment. The black curve indicates the temperature of a pseudoadiabatically lifted surface-based air parcel in which saturation occurs at the LCL. The plot background lines have their conventional meanings from skew T–logp diagrams and are described in Trier et al. (2014).

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    The 1900 UTC May 2013 (t = 4 h) surface water vapor mixing ratio (black contours with 2 g kg−1 contour intervals) and winds (barbs as in Fig. 1) within d03 of ensemble members (left) 6 and (right) 9, with color shadings indicating (a),(b) the minimum buoyancy Bmin (°C) for a 50-hPa-deep average parcel containing the highest equivalent potential temperature in a vertical column from the surface to 700 hPa and (c),(d) the CAPE (J kg−1) for the same 50-hPa-deep average parcel containing the highest equivalent potential temperature. The bold green contours indicate locations where model-derived radar reflectivity in the lowest model grid point exceeds 35 dBZ at 1957 UTC (approximately 1 h later). The white rectangles in each panel indicate the location of the line-averaged cross sections in Fig. 12. The red arrows show new rain cells.

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    Line-averaged (a) Bmin (K) and (b) CAPE (J kg−1) calculated from parcel theory (solid curves) for the 50-hPa-deep air parcel with highest equivalent potential temperature in the vertical column. The horizontal axes represent the distance along the major axis of the white rectangles in Fig. 11 with the red and blue curves representing regions within d03 of ensemble members 6 and 9, respectively. Dashed curves indicate values of these thermodynamic quantities with hypothetically modified air parcels experiencing 10% entrainment of environmental air per kilometer, as described in the text. Note that, since the dryline is slightly farther west at 1900 UTC in ensemble member 6 (Fig. 11), these averages (red curves) have been shifted 10 km to the right so that the mean surface mixing ratio equals 8 g kg−1 at x ~ 0 for each member.

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    Relationship between Bmin (abscissa) and CIN (ordinate) for the 50-hPa-deep air parcel with maximum equivalent potential temperature in the color-coded locations of the MPEX mobile upsondes (Figs. 3a, 6a) for (a) the simultaneous and closest model horizontal grid points in d03 of ensemble member 6 (Figs. 6a,c) and (b) for the upsondes themselves.

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    Scatter diagrams of (a) CIN, (b) Bmin, and (c) MSE (normalized by specific heat at constant pressure) for 50-hPa-deep air parcels having the highest equivalent potential temperature in the vertical column. Mobile upsonde values at color-coded locations in Fig. 3a are plotted on the abscissa, and simultaneous values of the nearest horizontal grid point in d03 of ensemble member 6 are plotted on the ordinate.

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    Comparison of temperature (red) and dewpoint (blue) between upsondes (solid curves) and simultaneous model soundings (dashed curves) at the nearest horizontal grid point in d03 of ensemble member 6 for the (a) 2110 UTC 19 May 2013 CSU MPEX upsonde location and the (b) 2053 UTC 19 May 2013 Purdue University MPEX upsonde location. These locations are shown in Figs. 3a and 6a.

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    Comparison of observed (blue) and simulated (ensemble member 6) Bmin (red) values for the 50-hPa-deep air parcels having the highest equivalent potential temperature in a vertical column from the five upsonde locations in Figs. 3a and 6a that are closest, both spatially and temporally to observed and simulated deep convection initiation.

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    (a) Sounding evolution at dot locations [in (b),(c),(d)] for ensemble member 6 during the 3-h period prior to the onset of CI (after 1930 UTC). Horizontal solid brown lines indicate typical parcel origination levels for deep convection and the dashed ones indicate lifted levels for these parcels where buoyancy is minimized (see blue horizontal line in Fig. 10). (bottom) Surface water vapor mixing ratio contours (solid red lines) of 8 and 12 g kg−1 enclosing the approximate horizontal position of the dryline and (b) Bmin (°C) for air parcels originating at model level 4 (~0.3 km AGL) that are vertically averaged over 50 hPa, (c) virtual potential temperature (K) at 1.7 km MSL, approximating the mean level of minimum buoyancy for air parcels originating at model level 4 east of the dryline (see dashed blue lines in Figs. 18a,b), and (d) equivalent potential temperature (K) for air parcels originating at model level 4 (~0.3 km AGL) and averaged over 50 hPa within d02 of ensemble member 6 at 1930 UTC 19 May 2013 (t = 4.5 h). The tan rectangles in (b),(c),(d) indicate the location of the line-averaged vertical cross sections and transects in Fig. 18.

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    (top) Illustration of 3-h time-averaged (1630–1930 UTC) and 150-km line-averaged thermally direct vertical circulation (red arrows) prior to CI: (a) vertical motion (color shading, cm s−1) and 1930 UTC water vapor mixing ratio (black contours with 2 g kg−1 intervals); (b) horizontal winds (m s−1) and 1930 UTC potential temperature (black contours with 1-K intervals). (c) The 3-h Bmin change (K) for model level 4 (~0.3 km AGL) air parcels (blue dashed–dotted), 3-h buoyancy change for model level 4 air parcels (solid cyan), its total forcing (solid black), and the error in the forcing (orange dashed). (e) Portion of the total forcing (solid black) due to parcel changes (solid red) and due to environment changes (blue). (d) The components of the parcel forcing (red solid), including horizontal temperature advection (red dashed), horizontal moisture advection (red dotted), and the sum of the temperature and moisture tendencies from the PBL scheme (red dashed–dotted). (f) The components of the environment forcing (solid blue), including those related to vertical motions (blue dotted), horizontal temperature advections (blue dashed) and temperature tendencies from the PBL scheme (blue dashed–dotted). In (c)–(f), the buoyancy changes are evaluated at the 3-h mean Bmin level [thick dark blue dashed line in (a),(b)] The dashed vertical rectangles indicate the CI zone. All plots are for quantities line averaged across the rectangles in Figs. 17b–d.

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    Analysis of 1.7-km MSL horizontal temperature advection (contours with interval of 1°C h−1; negative values dashed and zero contour eliminated), winds (barbs as in Fig. 1), and potential temperature (color shading, K) averaged from 1630 to 1930 UTC using 15-min model output for d02 (Fig. 4) of ensemble member 6. The white contours are 8 and 12 g kg−1 surface water vapor mixing ratio contours illustrating the approximate front and rear positions of the surface dryline at 1930 UTC. The yellow rectangle indicates the location of the vertical cross sections and forcing budget analyses in Fig. 18, which are line averaged along the minor axis (northeast–southwest direction) of the rectangle.

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    The 3-h back trajectories (colored arrows) from 1.7 km MSL, approximating the mean (i.e., 3 h) Bmin level for parcels originating from model level 4 (~0.3 km AGL) plotted over fields of Bmin (°C, colored shading) from model level 4 and the 8 and 12 g kg−1 surface water vapor mixing ratio isopleths (black) approximating the dryline location at (a) 1930 (back trajectory start) and (b) 1630 UTC 19 May 2013 (back trajectory finish). (c) Average heights of the five groups of 7–8 color-coded trajectories organized in rows parallel to, and at different distances from, the dryline at 1930 UTC, with the orange (cyan) trajectories ending up being closest to (farthest away) the dryline. The yellow rectangles included for reference are identical to those in Figs. 17b–d and represent the region of the line-averaged cross sections and budget for buoyancy change in Fig. 18.

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    (a) Parcel forcing terms [section 5b(1)] for ensemble members 6 (solid) and 9 (dashed–dotted), including the total parcel forcing (bold black) and parcel forcing components of horizontal temperature advection (red), horizontal moisture advection (cyan), and combined temperature and moisture tendencies from the PBL scheme (orange). (b) Environment forcing terms [section 5b(1)] for ensemble members 6 (solid) and 9 (dashed–dotted), including the total environment forcing (black), environment forcing components of horizontal temperature advection (red), those related to vertical motions (violet), and the combined temperature and moisture tendencies from the PBL scheme (orange). Forcings are 150-km line averages for a vertical cross section taken normal to the dryline, which is time averaged from 1630 to 1930 UTC.

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    As in Fig. 12a, but for the composites from subensembles that include members 6, 8, and 10 (SDRY), and members 2, 4, and 9 (DDRY). The line-averaged values of Bmin in these composites do not include effects of entrainment of environmental air (as in the corresponding solid curves in Fig. 12a).

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    (a),(c) As in Figs. 18a,e, respectively, but for a composite of ensemble members 6, 8, and 10 along the solid rectangles shown in Figs. 5f,h,j and line averaged in the northeast–southwest direction across those rectangles. (b),(d) As in Figs. 18a,e, respectively, but for a composite of ensemble members 2, 4, and 9 along the dashed rectangles shown in Figs. 5b,d,i and line averaged in the northeast–southwest direction across those rectangles.

  • View in gallery

    Composite forcing budget for 3-h buoyancy change (K) diagnosed at the 3-h mean Bmin levels for air parcels originating at model level 4 (~0.3 km AGL) in ensemble members 1, 3, 6, 8 and 10. Gray shading indicates surface water vapor mixing ratios between 8 and 12 g kg−1, approximating dryline location at the end of the 3-h buoyancy forcing period; The green contours indicate frequencies of model-derived radar reflectivity exceeding 35 dBZ 1 h after the 3-h buoyancy forcing period. (left) (a) Net forcing for 3-h buoyancy change (1-K contour interval; negative values dotted) and (d) its error (0.5-K contour interval; negative values dotted; zero contour omitted). (middle) As in (a), but due to (b) grid-resolved and (e) PBL-scheme forcings. (right) As in (a), but due to (c) parcel changes at its origination level and (f) environment changes at the 3-h mean Bmin level of the parcel. The semitransparent colored shading indicates the region where there are substantial differences between ΔBMIN and the ΔBUOY that the forcing in (a) attempts to diagnose. Analyses of the forcing in this shaded region are less representative of forcing for ΔBMIN.

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Mesoscale Thermodynamic Influences on Convection Initiation near a Surface Dryline in a Convection-Permitting Ensemble

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  • 1 National Center for Atmospheric Research,* Boulder, Colorado
  • | 2 Department of Earth and Atmospheric Science, University of Illinois at Urbana–Champaign, Urbana, Illinois
  • | 3 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
  • | 4 NOAA/National Severe Storms Laboratory, Norman, Oklahoma
  • | 5 Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania
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Abstract

In this study, the authors examine initiation of severe convection along a daytime surface dryline in a 10-member ensemble of convection-permitting simulations. Results indicate that the minimum buoyancy Bmin of PBL air parcels must be small (Bmin > −0.5°C) for successful deep convection initiation (CI) to occur along the dryline. Comparing different ensemble members reveals that CAPE magnitudes (allowing for entrainment) and the width of the zone of negligible Bmin extending eastward from the dryline act together to influence CI. Since PBL updrafts that initiate along the dryline move rapidly northeast in the vertically sheared flow as they grow into the free troposphere, a wider zone of negligible Bmin helps ensure adequate time for incipient storms to mature, which, itself, is hastened by larger CAPE.

Local Bmin budget calculations and trajectory analysis are used to quantify physical processes responsible for the reduction of negative buoyancy prior to CI. Here, the grid-resolved forcing and forcing from temperature and moisture tendencies in the PBL scheme (arising from surface fluxes) contribute about equally in ensemble composites. However, greater spatial variability in grid-resolved forcing focuses the location of the greatest net forcing along the dryline. The grid-resolved forcing is influenced by a thermally direct vertical circulation, where time-averaged ascent at the east edge of the dryline results in locally deeper moisture and cooler conditions near the PBL top. Horizontal temperature advection spreads the cooler air eastward above higher equivalent potential temperature air at source levels of convecting air parcels, resulting in a wider zone of negligible Bmin that facilitates sustained CI.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Stanley B. Trier, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000. E-mail: trier@ucar.edu

Abstract

In this study, the authors examine initiation of severe convection along a daytime surface dryline in a 10-member ensemble of convection-permitting simulations. Results indicate that the minimum buoyancy Bmin of PBL air parcels must be small (Bmin > −0.5°C) for successful deep convection initiation (CI) to occur along the dryline. Comparing different ensemble members reveals that CAPE magnitudes (allowing for entrainment) and the width of the zone of negligible Bmin extending eastward from the dryline act together to influence CI. Since PBL updrafts that initiate along the dryline move rapidly northeast in the vertically sheared flow as they grow into the free troposphere, a wider zone of negligible Bmin helps ensure adequate time for incipient storms to mature, which, itself, is hastened by larger CAPE.

Local Bmin budget calculations and trajectory analysis are used to quantify physical processes responsible for the reduction of negative buoyancy prior to CI. Here, the grid-resolved forcing and forcing from temperature and moisture tendencies in the PBL scheme (arising from surface fluxes) contribute about equally in ensemble composites. However, greater spatial variability in grid-resolved forcing focuses the location of the greatest net forcing along the dryline. The grid-resolved forcing is influenced by a thermally direct vertical circulation, where time-averaged ascent at the east edge of the dryline results in locally deeper moisture and cooler conditions near the PBL top. Horizontal temperature advection spreads the cooler air eastward above higher equivalent potential temperature air at source levels of convecting air parcels, resulting in a wider zone of negligible Bmin that facilitates sustained CI.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Stanley B. Trier, National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-3000. E-mail: trier@ucar.edu

1. Introduction

Large longitudinal contrasts in lower-tropospheric water vapor occur climatologically across the southern Great Plains (SGP) of the United States. Diurnally driven processes in spring and early summer often result in localized gradients of water vapor mixing ratio (qυ), referred to as drylines (e.g., McGuire 1962). SGP drylines are of meteorological interest because they often serve as a focus for severe convection (Rhea 1966). Incipient convection that forms along or near the SGP dryline is often relatively isolated but may evolve into long-lived supercell storms, which are influenced by the large convective available potential energy (CAPE) and strong vertical wind shear in their environments (e.g., Bluestein and Parker 1993).

Less well understood is how different physical processes interact to influence the initiation of deep convection (CI) near the dryline. Two general classes of vertical circulations influence CI near the dryline. One class includes dry convective-scale motions arising from surface heating in the daytime planetary boundary layer (PBL), of which horizontal convective rolls (HCRs), dry convective cells, and gravity waves excited in stable layers atop the PBL (e.g., Balaji and Clark 1988) are examples. The second includes mesoscale thermally direct vertical circulations driven by differential heating over broader regions, owing to the gently sloping terrain and vegetation and soil moisture contrasts across the SGP (Ogura and Chen 1977; Sun and Ogura 1979; Sun and Wu 1992; Weiss and Bluestein 2002; Trier et al. 2004; Kang and Bryan 2011).

This mesoscale circulation can influence dryline intensity and the characteristic deeper layer of surface-based moisture extending several tens of kilometers downwind from the dryline, which favors CI (e.g., Ziegler et al. 1995). Dryline intensity, motion, and associated CI may be further influenced by synoptic factors (e.g., Carlson et al. 1983; Hane et al. 2001), including confluence and implied deformation frontogenesis from larger scales (e.g., Schultz et al. 2007).

Observational studies from dryline environments have indicated that convective-scale PBL circulations, including HCRs, enhance cloud formation when they intersect drylines (e.g., Atkins et al. 1998) and, in some cases, influence CI at locations that are significantly removed from where the dryline qυ gradient is strongest (e.g., Weckwerth et al. 2008). These results and similar results from other investigations point toward the importance of finescale PBL circulations in focusing the precise locations of CI near drylines.

However, such dry convective-scale thermal circulations are ubiquitous in the heated daytime PBL near drylines but there are many instances in which CI does not occur (e.g., Cai et al. 2006; Markowski et al. 2006; Wakimoto and Murphey 2009). Each of these three “null CI” studies characterized the thermodynamic environment using dropsondes from the International H2O (IHOP_2002) field experiment (Weckwerth et al. 2004). In two of these studies (Cai et al. 2006; Wakimoto and Murphey 2009) it was concluded that the kinetic energy of the strongest ~3 m s−1 diagnosed dry convective-scale PBL updrafts was insufficient to overcome the inhibition energy for deep convection (CIN; Colby 1984). In contrast, Markowski et al. (2006) noted vanishingly small CIN in some locations but suggested the lack of continuous mesoscale ascent as a possible factor prohibiting sustained CI. Together, these observational results are consistent with the results from the high-resolution mesoscale modeling study of Ziegler et al. (1997), which found deep storm-bearing clouds existing only where magnitudes of CIN had been reduced to near zero within bands of mesoscale ascent.

In the current study, we use a 10-member ensemble of convection-permitting simulations to examine thermodynamic influences on dryline CI for a case of severe convection that occurred on 19 May 2013 during the Mesoscale Predictability Experiment (MPEX; Weisman et al. 2015). As convection-permitting ensemble prediction systems have gained wider use for probabilistic forecasts, they have also been leveraged as a tool for qualitative and quantitative diagnosis of weather systems. By considering each member of an ensemble as a plausible outcome of a particular forecast scenario, the differences between members with “good” forecasts and those without can be used to gain insight into the processes that caused a weather event of interest. Hakim and Torn (2008) provided an overview of these “ensemble synoptic analysis” techniques, which may include 1) the covariance between atmospheric state variables and statistical metrics (e.g., Martin and Xue 2006; Ancell and Hakim 2007; Hawblitzel et al. 2007; Zheng et al. 2013; Bednarczyk and Ancell 2015); 2) composite analysis using subsets of the larger ensemble (e.g., Reinecke and Durran 2009; Schumacher 2011; Hanley et al. 2011; Melhauser and Zhang 2012); or 3) contrasting members of an ensemble through statistical or manual analysis (e.g., Clark et al. 2010; Schumacher et al. 2013; Lynch and Schumacher 2014). Real-time sensitivity calculations from a convection-permitting ensemble were also important inputs that influenced decisions for data collection in MPEX (Weisman et al. 2015).

Herein, we will employ both analysis of ensemble subsets and comparison of individual ensemble members to diagnose processes influencing dryline CI. In particular, we use local thermodynamic budget analyses combined with trajectory analysis to quantify contributions from different physical processes (including those related to grid-resolved horizontal and vertical transports and subgrid surface fluxes) in reducing lower-tropospheric negative buoyancy in the simulated daytime dryline environment prior to CI. Here, budget analyses are performed for both individual ensemble members where CI either resembled or differed from the actual CI in both timing and location, and for composites comprising subsets of the 10-member ensemble exhibiting these different CI behaviors. We also use different members of the ensemble to illustrate how the horizontal scale over which the negative buoyancy becomes vanishingly small can impact CI in the environment of strong vertical shear near the dryline.

2. Overview of the 19 May 2013 central Oklahoma convective event

The CI examined in this paper occurred during intensive observing period (IOP) 4 of MPEX (see www.eol.ucar.edu/field_projects/mpex). Aspects related to the prediction of the broader distribution of deep convection over the SGP during this MPEX IOP are discussed in Weisman et al. (2015). In this section, we focus specifically on deep convection over central Oklahoma and environmental features most directly related to this region of CI.

The synoptic conditions at 1200 UTC 19 May 2013 (Fig. 1) are representative of those often associated with subsequent afternoon severe convective weather in the SGP during the spring. Strong 500-hPa flow existed ahead of a quasi-stationary surface front with one jet streak having |V| > 25 m s−1 centered over central Oklahoma and another approaching the base of a trough (Fig. 1). The surface dryline over the central Texas panhandle at 1200 UTC (Fig. 1) had moved into west-central Oklahoma by early afternoon (Fig. 2a). At this time, the warm (T ~30°C) and moist Td [(20°–22°C)] surface conditions immediately east of the dryline (Fig. 2a), combined with cold midtropospheric conditions (Fig. 1), contribute to CAPE in the range of 2000–3500 J kg−1. The strong 10–12 m s−1 south-southeast surface flow in this location (Figs. 2a,b) with ~(20–25) m s−1 southwesterly 500-hPa winds resulted in strong vertical shear on the order of 25 m s−1 (5 km)−1, which, in the presence of large CAPE, supported the development of supercell thunderstorms.

Fig. 1.
Fig. 1.

Composite 500-hPa and surface analysis for 1200 UTC 19 May 2013 from Fig. 9a of Weisman et al. (2015). Winds (half barb = 2.5, full barb = 5, and pennant = 25 m s−1), annotated temperatures (°C), height contours (decameters), and wind speeds (shading) are obtained from NAM operational 500-hPa analyses. Overlaid surface low-pressure symbols, fronts, and dryline (dashed yellow line) have conventional meteorological meanings and are subjectively analyzed.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 2.
Fig. 2.

Oklahoma surface mesonet (Brock et al. 1995) station data from the closest available 5-min increments corresponding to the overlaid visible satellite imagery at the indicated times: (a) 1856, (b) 1938, and (c) 2033 UTC. The station model contains winds (barbs as in Fig. 1), temperature (°C, red), and dewpoint (°C, yellow). The gray horizontal line indicates 35° latitude.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

An elongated ~20-km-wide zone of shallow cumulus clouds (Fig. 2a) was evident at 1856 UTC (1356 local daylight time). Within the next hour, deep convection initiated along the dryline, located at the western edge of the cloud zone (Fig. 2b), and grew rapidly upscale, forming a circular ~100-km-scale cloud shield by 2033 UTC (Fig. 2c). Radar imagery from shortly thereafter indicates that some of the developing storms had advanced beyond the surface dryline, which by then had nearly ceased its eastward progression (Fig. 3a). Note that the majority of storms at this time are located downwind (relative to the 500-hPa flow; Fig. 1) of the dryline’s east edge, marked by a radar fine line (Wilson and Schreiber 1986). Several supercells appear in the radar reflectivity at 2220 UTC (Fig. 3b). The southwesternmost of these storms produced an enhanced Fujita scale category 4 (EF-4) tornado that resulted in multiple fatalities near Shawnee, Oklahoma (OK) [located ~20 km northeast of Norman, Oklahoma (station OUN)], close to the time of the 2350 UTC radar image in Fig. 3c.

Fig. 3.
Fig. 3.

Base-level radar reflectivity (colors, dBZ) from the Twin Lakes, OK (KTLX), NEXRAD WSR-88D for (a) 2055, (b) 2220, and (c) 2350 UTC. The 8 and 12 g kg−1 vapor mixing ratio isopleths (brown lines), objectively analyzed using surface observations from the displayed locations, approximate the position of the front and rear of the surface dryline in central Oklahoma. Colored stars in (a) indicate locations and UTC times of MPEX mobile upsonde launches presented in Figs. 13b and 14.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

3. Numerical model and experiment design

a. Numerical model

Our 10-member ensemble uses version 3.3.1 of the Advanced Research core of the Weather Research and Forecasting Model (ARW; Skamarock and Klemp 2008). Each simulation uses a two-way interactive nest d02 with 1046 × 871 horizontal grid points having a spacing of Δ = 3 km, which is embedded within an outer cycled analysis (section 3b) domain d01 with 415 × 325 horizontal grid points having spacing of Δ = 15 km (Fig. 4). In this paper, we discuss only results from domain d02, except in sections 4 and 5a, where results from an additional interactive nest d03 (Fig. 4) are used for more detailed comparisons between two selected ensemble members and with field observations. This innermost nest has 661 × 661 horizontal grid points with spacing of Δ = 1 km. Each domain in Fig. 4 has 40 vertical levels with a model top at ~50 hPa.

Fig. 4.
Fig. 4.

The ARW Model outer horizontal domain d01 (Δ = 15 km) and two-way interactive nest d02 (Δ = 3 km) used in all 10 ensemble members, and the innermost two-way interactive nest d03 (Δ = 1 km) used in the highest-resolution simulations of ensemble members 6 and 9 presented in section 4.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Our 10 ensemble members have identical physical parameterizations, which are motivated by the success of real-time simulations during MPEX (Weisman et al. 2015) that used the same ones. Domain d02 uses no cumulus scheme, which differs from the outer domain d01 where the Tiedtke cumulus scheme (Tiedtke 1989; Zhang et al. 2011) is applied. The physical parameterizations used for domain d03 are identical to those for domain d02 and include the Thompson et al. (2008) bulk microphysical parameterization, which predicts the mixing ratios of cloud water, snow, and graupel and both mixing ratios and number concentrations of cloud ice and rain. Other parameterizations include the Mellor–Yamada–Janjić (MYJ; Mellor and Yamada 1982; Janjić 1994, 2002) PBL scheme, the Rapid Radiative Transfer Model for Global Climate Models (RRTMG; Mlawer et al. 1997; Iacono et al. 2008) longwave and shortwave radiation schemes with ozone and aerosol climatologies (Tegen et al. 1997), and the Noah land surface model (Chen and Dudhia 2001). Subgrid horizontal mixing is determined using a Smagorinsky-type first-order closure.

b. Initialization and lateral boundary conditions for the convection-permitting ensemble

Initializing convection-permitting forecasts with ensemble Kalman filter (EnKF; Evensen 2003) analyses have been demonstrated as an effective approach for skillful and reliable probabilistic forecasts of severe storms (e.g., Wheatley et al. 2012; Stensrud et al. 2013; Romine et al. 2013; Schwartz et al. 2014, 2015). In this study, ensemble analyses are generated with the Data Assimilation Research Testbed (DART; Anderson et al. 2009) software. The 50-member adjustment Kalman filter (Anderson 2001, 2003) is used to initialize ensemble forecasts. The model analysis system settings were tuned to minimize bias and RMS error between observations and the background analysis (Romine et al. 2013; Schwartz et al. 2015). The analysis system was initialized on 1 May 2013 and thereafter was continuously cycled in real time with 6-hourly updates. As part of a broader investigation of mesoscale uncertainty, a retrospective period of analysis cycling was later initialized from the 0000 UTC 19 May 2013 real-time analysis background but with hourly updates through 1500 UTC. This retrospective ensemble analysis state was used to initialize the forecasts shown in the study.

Convection-permitting simulations in domain d02 are initialized by downscaling the first 10 members from the continuously cycled 50-member ensemble mesoscale analyses in the Δ = 15 km outer domain (Fig. 4). Schwartz et al. (2014) demonstrate that a more sophisticated selection approach for determining which members of the analysis to use for the forecasts is likely unwarranted. The model is then integrated for 12 h from 1500 UTC 19 May to 0300 UTC 20 May 2013. During this period, lateral boundary conditions for the outer domain of the ensemble are provided by 3-hourly Global Forecast System (GFS) forecasts, with perturbations supplemented from the WRF three-dimensional variational data assimilation (WRFDA-3DVAR) system (Barker et al. 2012) using the fixed covariance perturbation technique of Torn et al. (2006).

4. Convection initiation in high-resolution simulations

Convection near the Oklahoma–Kansas border is similar among the 10 ensemble members (Fig. 5) and corresponds well to observations (Fig. 3a). However, there is considerable variation in the timing and coverage of simulated CI within domain d02 near the dryline in central Oklahoma (Fig. 5). Here, we follow previous studies (e.g., Roberts and Rutledge 2003; Mecikalski and Bedka 2006; Kain et al. 2013; Burghardt et al. 2014) and define CI as the onset of model-derived reflectivity exceeding 35 dBZ. We now examine the central Oklahoma CI in higher-resolution simulations that utilize the Δ = 1 km nest d03 (Fig. 4) for the two selected members 6 (Fig. 5f) and 9 (Fig. 5i), which exemplify the range of CI differences in the Δ = 3 km 10-member ensemble.

Fig. 5.
Fig. 5.

Model-derived radar reflectivity (dBZ) at the lowest model grid point within d02 (Fig. 4) at hour 6 of the forecast for (a)–(j) each of the 10 ensemble members. The (f),(h),(j) solid and (b),(d),(i) dashed rectangles indicate the location of composite line-averaged cross sections presented in Figs. 23a,c and Figs. 23b,d, respectively.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

a. Variability of simulated CI in ensemble members 6 and 9

Pronounced differences between ensemble members 6 and 9 are also evident within domain d03 (Fig. 6). Deep convective cells in ensemble member 6 (Fig. 6a) are centered about 25 km southwest of the simultaneous observed storms in Fig. 3a. The north–south sequence of storm triggering also differs, which leads to minor differences in orientation of the observed and simulated lines of convection, since individual storms rapidly move off the dryline in the strong midtropospheric southwesterly flow (Fig. 1). However, both the timing and spatial extent of CI along the eastern edge of the central Oklahoma dryline in member 6 (Fig. 6a) strongly resembles the observations (Fig. 3a). This contrasts with member 9, where CI is both delayed (Fig. 6d) and more isolated than in observations (Figs. 3a,b).

Fig. 6.
Fig. 6.

Model-derived radar reflectivity (dBZ) from the lowest model grid point and its relationship to the dryline (in central Oklahoma) and frontal moisture gradient (northwest Oklahoma) approximated by the 8–12 g kg−1 surface water vapor mixing ratio isopleths (contours) in d03 (Fig. 4) of ensemble members (a),(c) 6 and (b),(d) 9 at (top) 2048 and (bottom) 2218 UTC. Colored stars in (a),(b) indicate locations and UTC times of MPEX mobile upsonde launches presented in Figs. 13b and 14.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

b. Finescale kinematic and thermodynamic structure near simulated CI

Dry convective-scale PBL updrafts occur in ensemble member 6 both along the dryline and in its surrounding environment (Figs. 7a,c). The elongation of the PBL vertical velocity features in the direction of the lower-to-middle PBL flow (approximating that of the vertical shear) suggests that these features are akin to HCRs arising from thermal-shear instability (Asai 1970, 1972), although they may not be completely resolved at Δ = 1 km (Ching et al. 2014). The width of the zone of PBL vertical motions in the cooler, moister air on the east side of the dryline prior to CI (Figs. 7a,c) of a few tens of kilometers is consistent with that across the rows of shallow cumuli prior to CI (Fig. 2a).

Fig. 7.
Fig. 7.

Evolution of PBL horizontal winds (barbs as in Fig. 1), vertical velocity (color shading, m s−1), potential temperature (blue dashed contours, 2-K intervals), and their relationships to the surface vapor mixing ratio (black solid contours with 2 g kg−1 intervals) within d03 (Fig. 4) of ensemble members (left) 6 and (right) 9: (a),(c),(e) 1900 to 1957 UTC and (b),(d),(f) 1930 to 2115 UTC. Bold red contours indicate locations of surface model-derived radar reflectivity >35 dBZ used as an indicator of deep CI. Note that the horizontal locations of the displayed regions differ between ensemble members (left) 6 and (right) 9. The single arrow in(d) indicates the approximate location along the dryline where cells A and B in Figs. 8 and 9 are initiated.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

An important difference in PBL structure between ensemble members 6 and 9 in Fig. 7, the ramifications of which are later discussed, is the development of a secondary moisture gradient in member 9, which is initially located several tens of kilometers east of the primary dryline (Fig. 7b). Such “double drylines” have been described in previous observational studies (e.g., Hane et al. 1993, 2001; Demoz et al. 2006; Weiss et al. 2006). Their mechanism of formation remains a current research topic and likely varies among different cases.

The onset of the secondary moisture gradient in ensemble member 9 is associated with the advection of relatively dry air ahead of the dryline by strong southwesterly flow in the PBL (Fig. 7b). Sustained deep convection ensues in ensemble member 9 when the more rapidly approaching primary dryline becomes collocated with the developing secondary moisture gradient in the frontogenetical environment of increasing surface confluence (Fig. 7f). However, as previously noted, this CI lags the CI along the primary dryline in both observations and ensemble member 6 by more than 1 h (cf. Fig. 7e).

Similar to previous high-resolution modeling studies (Peckham et al. 2004; Xue and Martin 2006), air parcels in ensemble member 9 reach their level of free convection (LFC) along the east edge of the primary dryline (DL1; Figs. 8a,b) where it is intersected by an HCR originating from its west (indicated by the single arrow in Fig. 7d). However, in contrast to these previous studies, this incipient deep convection marked by updraft cells A and B (Figs. 8b–d, 9a–c) dissipates as it passes over the relatively dry near-surface air southwest of the intensifying secondary moisture gradient DL2 (Figs. 8c–e). Sustained deep convection occurs with the merger of cells F and E (Figs. 9f–h) and cells G and H (Figs. 9g–j), the elements of which form along the east edge of DL2 as it is overtaken by the more rapidly advancing DL1.

Fig. 8.
Fig. 8.

Vertical velocity (color shading, m s−1) and water vapor mixing ratio (green contours with 1 g kg−1 intervals from 1 to 16 g kg−1) from d03 (Fig. 4) of ensemble member 9 along the southwest–northeast transect (SW–NE) in Figs. 9a–e. Annotations near convective updrafts within the vertical cross section identify discrete cells defined as in the caption of Fig. 9. The annotations near the bottom of the cross section locate DL1 and the intensifying secondary moisture gradient DL2 indicated in Fig. 7b and discussed in the text.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 9.
Fig. 9.

Relationships among evolutions in the horizontal structure of thermodynamic and kinematic variables—surface water vapor mixing ratio (brown contours, g kg−1), 5-km MSL vertical velocity (red contours, m s−1), and MUCAPE (dashed black contours, J kg−1)—and the initiation of deep convection within d03 (Fig. 4) of ensemble member 9: (a)–(i) 2018 to 2106 UTC. Updraft centers with vertical velocities that exceed 2 m s−1 at 5 km MSL for at least 12 min are labeled alphabetically in the chronological order of their development. Cells denoted by multiple letters indicate mergers of previously defined cells. The southwest–northeast transect in (a)–(e) indicates the horizontal location of the vertical cross section displayed in Fig. 8.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

c. Mesoscale thermodynamic variations influencing CI in ensemble members 6 and 9

Near the time of CI onset in ensemble member 6, the maximum PBL vertical velocities of ~(2–3) m s−1 along the dryline in member 9 are comparable, and the dryline qυ gradient is even stronger (Fig. 7b) than in member 6 (Fig. 7c). This indicates that differences in CI timing and coverage between these two ensemble members cannot be explained by these dry convective-scale updraft magnitudes alone. Thus, we look toward mesoscale thermodynamic differences suggested in the previous comparison as a more likely primary cause of the CI timing and coverage differences between these ensemble members.

Trier et al. (2014, hereafter T14) noted that, in regions of mesoscale convergence, CI often first occurs where the parcel buoyancy minimum Bmin (Fig. 10, blue horizontal line) approaches zero. Though only a proxy for the integral quantity CIN (shading in Fig. 10), Bmin has several advantages for analysis of thermodynamic destabilization. Unlike CIN, Bmin does not depend on there being an LFC and is therefore a spatially continuous field. This property of Bmin also affords straightforward computation of local temporal trends. Moreover, forcing budgets that attribute such trends to various physical processes (sections 5b and 6) are simpler to compute and interpret because they do not require vertical integration. As noted in T14, Bmin depends only on conditions at the air parcel origination level (p = po) and the level , where a pseudoadiabatically displaced parcel attains its minimum buoyancy (Fig. 10).

Fig. 10.
Fig. 10.

Schematic diagram from Trier et al. (2014) illustrating the buoyancy minimum (Bmin, virtual temperature units, blue line) for a surface-based air parcel (p = po) lifted to the pressure of its minimum buoyancy (p = pBmin). The gray shading indicates the vertically integrated CIN for the same surface-based air parcel between its origination level and the LFC. The red (green) curve indicates the virtual temperature (dewpoint) of the environment. The black curve indicates the temperature of a pseudoadiabatically lifted surface-based air parcel in which saturation occurs at the LCL. The plot background lines have their conventional meanings from skew T–logp diagrams and are described in Trier et al. (2014).

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

In ensemble member 6, the magnitude of Bmin for the highest θe parcel becomes vanishingly small along and for ~40 km east of the dryline by 1900 UTC (Fig. 11a). The width of the zone of near-zero Bmin is important in aiding vertically developing updrafts as they move off the surface dryline after becoming embedded in strong midtropospheric southwesterly flow (Fig. 1). During the next hour, new rain cells develop within this zone of near-zero Bmin where the surface dryline and associated confluence is strongest (Fig. 11a). This contrasts with the narrower zone of near-zero Bmin and the lack of CI along the same part of the dryline in ensemble member 9 (Fig. 11b). These thermodynamic differences between simulations are apparent in line averages (Fig. 12a) taken across the subsequent region of CI in the two ensemble members.

Fig. 11.
Fig. 11.

The 1900 UTC May 2013 (t = 4 h) surface water vapor mixing ratio (black contours with 2 g kg−1 contour intervals) and winds (barbs as in Fig. 1) within d03 of ensemble members (left) 6 and (right) 9, with color shadings indicating (a),(b) the minimum buoyancy Bmin (°C) for a 50-hPa-deep average parcel containing the highest equivalent potential temperature in a vertical column from the surface to 700 hPa and (c),(d) the CAPE (J kg−1) for the same 50-hPa-deep average parcel containing the highest equivalent potential temperature. The bold green contours indicate locations where model-derived radar reflectivity in the lowest model grid point exceeds 35 dBZ at 1957 UTC (approximately 1 h later). The white rectangles in each panel indicate the location of the line-averaged cross sections in Fig. 12. The red arrows show new rain cells.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 12.
Fig. 12.

Line-averaged (a) Bmin (K) and (b) CAPE (J kg−1) calculated from parcel theory (solid curves) for the 50-hPa-deep air parcel with highest equivalent potential temperature in the vertical column. The horizontal axes represent the distance along the major axis of the white rectangles in Fig. 11 with the red and blue curves representing regions within d03 of ensemble members 6 and 9, respectively. Dashed curves indicate values of these thermodynamic quantities with hypothetically modified air parcels experiencing 10% entrainment of environmental air per kilometer, as described in the text. Note that, since the dryline is slightly farther west at 1900 UTC in ensemble member 6 (Fig. 11), these averages (red curves) have been shifted 10 km to the right so that the mean surface mixing ratio equals 8 g kg−1 at x ~ 0 for each member.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Case studies (e.g., Ziegler and Rasmussen 1998) from the dryline environment and more general statistical studies of CI over the central United States (e.g., Lock and Houston 2014) have noted potentially significant effects of dilution by dry environmental air on buoyancy and CI. However, entrainment rates for developing supercell storms in the central United States are not well established from actual measurements. Recent large-eddy simulations of more generic deep convection (e.g., Romps 2010; Yeo and Romps 2013) have revealed fairly substantial entrainment rates of about 10% per kilometer through the depth of the troposphere.

Thus, in an attempt to provide a rough estimate of entrainment effects not accounted for in parcel theory, we prescribe a constant entrainment rate of 10% per kilometer, following the approach of Davis and Ahijevych (2013). Here, parcel mixing ratio and temperature are mixed separately with environmental air as the parcel is lifted from one model vertical level to the next. Parcels with the resulting mixture are then lifted to the next overlying model level, and this process is repeated through the depth of the troposphere. Figure 12a reveals that such entrainment of environmental air has little effect on Bmin. This is not surprising, considering the offsetting effects on buoyancy of entraining warmer but drier air and the typical location of Bmin for a well-mixed daytime boundary layer near the parcel lifted condensation level (LCL), which requires only modest vertical excursions from parcel source levels in the PBL (Fig. 10).

This is not the case for CAPE (Fig. 12b) in the dryline environment, where, above the LFC, the air parcel is entraining both drier and colder air through a much greater depth. Here, our prescribed entrainment rate of 10% km−1 reduces CAPE of the highest θe parcel (MUCAPE) by approximately 50% in both ensemble members 6 and 9 (Fig. 12b).

The zone of smaller MUCAPE in ensemble member 9 roughly coincides with the zone of larger Bmin magnitudes ~(20–40) km southeast of the dryline (Figs. 12a,b). As for Bmin (Fig. 11b), the reduced MUCAPE (Fig. 11d) stems from the drier near-surface air behind the developing secondary moisture gradient. Even with our large prescribed entrainment rate, significant CAPE of ~900 J kg−1 remains within this region for ensemble member 9 (Fig. 12b). However, these values are only about half those of ensemble member 6, contributing to weaker updrafts in member 9 (not shown). This, in turn, could slow the development of internal dynamical forcings favoring storm sustenance, including updraft rotation in the deeply sheared environment (e.g., Rotunno and Klemp 1985) or rain-produced cold pools (e.g., Rotunno et al. 1988), which may be necessary to sustain deep updrafts (Figs. 8a–e) in the face of nonnegligible Bmin.

Recall that sustained deep convection in ensemble member 9 fails to initiate until the merger of the primary dryline and secondary moisture gradient (Figs. 9f–i). The broad area of large negative buoyancy east of the secondary moisture gradient in ensemble member 9 at 1900 UTC (x = 50–150 km in Fig. 12a), though subsequently reduced (not shown), is not eroded entirely, and it thus presents an obstacle for sustained CI similar to that encountered earlier east of the original primary dryline. However, at this location, MUCAPE is much larger (Fig. 9), and strong frontogenesis has resulted in substantial increases in baroclinity at the new dryline boundary (Fig. 7f). The latter, especially when combined with strong vertical shear, supports stronger lower-tropospheric updrafts at DL2 (Fig. 8f) than simulated earlier at DL1 (Figs. 8a,b). These aspects collectively favor sustainable deep convection (Figs. 9f–i), though the storms remain isolated (Fig. 6d), consistent with significant Bmin magnitudes in their path. This 2–3-h evolution of deep convection in ensemble member 9 contrasts significantly with that in ensemble member 6, where both a wider zone of negligible Bmin east of the primary dryline (Fig. 12a) and larger MUCAPE (Fig. 12b) promoted both earlier and more widespread storm development, as inferred from the numerous rain cells within ~25 km of the dryline in Fig. 6a.

Though favorable horizontal distributions of both MUCAPE (Fig. 11c) and Bmin (Fig. 11a) together promote sustainable CI in ensemble member 6, Bmin both better delineates the mesoscale region of eventual CI occurring near the most intense segment of the dryline (Fig. 11a) and is insensitive to entrainment (Fig. 12a). Thus, analyses of thermodynamic processes responsible for CI in the next two sections emphasize parcel theory–based forcing budgets for Bmin tendencies.

5. Observations and simulation of the thermodynamic environment near CI

a. Comparison of the thermodynamic state in member 6 with mobile upsondes

Because of the similarities in CI timing and coverage between ensemble member 6 and observations (cf. Figs. 3a and 6a), we focus our analysis in the present section on this simulation. We first compare thermodynamic quantities from the MPEX upsondes (Trapp et al. 2015) with their simultaneous counterparts from the closest model grid points in domain d03 of this simulation. It is important to note that many of these upsondes sampled the inflow regions of mature supercell storms (Fig. 3a) as opposed to inflow regions associated with CI. Nevertheless, such comparisons are helpful for assessing the appropriateness of using Bmin as a proxy for CIN and for evaluation of model biases. T14 demonstrated the efficacy of using Bmin in place of CIN for three disparate simulated warm-season CI environments (their Fig. 8). However, it is well recognized that the vertical thermodynamic structure in present convection-permitting models is typically too smooth (e.g., Coniglio et al. 2013). Thus, it is not clear a priori whether sampling issues arising from using Bmin would lead to different results for research soundings that have enhanced vertical resolution and are not affected by inadequacies in model physics.

The Bmin and CIN are well correlated (r = 0.96) in the current simulation (Fig. 13a). Though there is clearly more scatter, the relationship is similar (r = 0.85) for the mobile upsondes (Fig. 13b). However, similar diagrams indicate model biases in CIN (Fig. 14a), Bmin (Fig. 14b), and moist static energy (MSE, Fig. 14c), which is analogous to θe. Though model gridpoint values of CIN and Bmin are generally correlated with their upsonde counterparts (r = 0.77 for CIN; r = 0.88 for Bmin), the model values are systematically less negative. The model bias is most acute for MSE of PBL parcels, where model values are significantly larger than observed (Fig. 14c).

Fig. 13.
Fig. 13.

Relationship between Bmin (abscissa) and CIN (ordinate) for the 50-hPa-deep air parcel with maximum equivalent potential temperature in the color-coded locations of the MPEX mobile upsondes (Figs. 3a, 6a) for (a) the simultaneous and closest model horizontal grid points in d03 of ensemble member 6 (Figs. 6a,c) and (b) for the upsondes themselves.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 14.
Fig. 14.

Scatter diagrams of (a) CIN, (b) Bmin, and (c) MSE (normalized by specific heat at constant pressure) for 50-hPa-deep air parcels having the highest equivalent potential temperature in the vertical column. Mobile upsonde values at color-coded locations in Fig. 3a are plotted on the abscissa, and simultaneous values of the nearest horizontal grid point in d03 of ensemble member 6 are plotted on the ordinate.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Factors influencing these biases are evident from comparisons of selected model and observed soundings (Fig. 15). The model PBL is too shallow and moist, accounting for the bias in PBL MSE, which results in excess CAPE at the Colorado State University (CSU) 2110 (Fig. 15a) and Purdue 2053 (Fig. 15b) upsonde locations 40–60 km northeast of a mature supercell storm (Fig. 3a). Coniglio et al. (2013) found similar differences after daytime heating (at ~2300 UTC) for a larger sample of soundings in convection-permitting simulations that also used the MYJ PBL scheme.

Fig. 15.
Fig. 15.

Comparison of temperature (red) and dewpoint (blue) between upsondes (solid curves) and simultaneous model soundings (dashed curves) at the nearest horizontal grid point in d03 of ensemble member 6 for the (a) 2110 UTC 19 May 2013 CSU MPEX upsonde location and the (b) 2053 UTC 19 May 2013 Purdue University MPEX upsonde location. These locations are shown in Figs. 3a and 6a.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Though Bmin magnitudes are too small in the model, the regional trend indicating diminishing inhibition over the area spanned by the southernmost five upsondes (Fig. 3a) is similar to observations (Fig. 16). This provides some confidence that the model is capable of accurately capturing the overall thermodynamic destabilization process influencing CI, which we seek to elucidate in the forthcoming analysis.

Fig. 16.
Fig. 16.

Comparison of observed (blue) and simulated (ensemble member 6) Bmin (red) values for the 50-hPa-deep air parcels having the highest equivalent potential temperature in a vertical column from the five upsonde locations in Figs. 3a and 6a that are closest, both spatially and temporally to observed and simulated deep convection initiation.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

b. Thermodynamic forcing budget for ensemble member 6

Since we are most interested in the mesoscale aspects of the thermodynamic destabilization and will be comparing our member 6 results with those from other ensemble members, we calculate the budget using output from d02 (Fig. 4), which has a horizontal grid spacing of 3 km.

In the current case of CI following strong surface heating, the relevant parcel source levels reside within the PBL (Fig. 17a). The local thermodynamic destabilization from 1630 to 1930 UTC prior to CI is associated with both substantial warming of the lower PBL and strong local cooling at parcel lifted levels immediately above the PBL (Fig. 17a). The θe value (or MSE) at a PBL parcel origination level (Fig. 17d) influences Bmin by specifying the moist adiabat, upon which the parcel virtual temperature difference from that of the surrounding environment at is determined. However, θe is fairly uniform for ~100 km east of the dryline (Fig. 17d), and the horizontal structure of Bmin for the chosen parcel origination level (Fig. 17b) appears dominated by the horizontal structure of environmental θυ at parcel lifted levels (Fig. 17c). The budget analysis approach outlined below allows us to discriminate between the forcings for Bmin modifications resulting from changes both to the parcel at its source level and in the environment at the lifted level where its buoyancy minimum occurs.

Fig. 17.
Fig. 17.

(a) Sounding evolution at dot locations [in (b),(c),(d)] for ensemble member 6 during the 3-h period prior to the onset of CI (after 1930 UTC). Horizontal solid brown lines indicate typical parcel origination levels for deep convection and the dashed ones indicate lifted levels for these parcels where buoyancy is minimized (see blue horizontal line in Fig. 10). (bottom) Surface water vapor mixing ratio contours (solid red lines) of 8 and 12 g kg−1 enclosing the approximate horizontal position of the dryline and (b) Bmin (°C) for air parcels originating at model level 4 (~0.3 km AGL) that are vertically averaged over 50 hPa, (c) virtual potential temperature (K) at 1.7 km MSL, approximating the mean level of minimum buoyancy for air parcels originating at model level 4 east of the dryline (see dashed blue lines in Figs. 18a,b), and (d) equivalent potential temperature (K) for air parcels originating at model level 4 (~0.3 km AGL) and averaged over 50 hPa within d02 of ensemble member 6 at 1930 UTC 19 May 2013 (t = 4.5 h). The tan rectangles in (b),(c),(d) indicate the location of the line-averaged vertical cross sections and transects in Fig. 18.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

1) Budget methodology

The tendency for buoyancy change (in temperature units) at the parcel lifted level arising from forcing for the changes to the parcel at its origination level ,
e1
has contributions due to horizontal temperature advection (HTADVP), a combination of adiabatic temperature change and vertical temperature advection (VTADVP), horizontal moisture advection (HMADVP), vertical moisture advection (VMADVP), and subgrid temperature and moisture tendencies obtained from the PBL parameterization (PBLP) . Herein, we refer to this forcing in (1) as the parcel forcing. The tendency for buoyancy change due to forcing for environmental changes at ,
e2
is influenced by horizontal temperature advection (HTADVE), a combination of adiabatic temperature change and vertical temperature advection (VTADVE), and the subgrid temperature tendency obtained from the PBL parameterization (PBLE). Herein, we refer to this forcing in (2) as the environment forcing. Note that, while we retain the influence of moisture on the full environmental virtual temperature, we have eliminated the relatively small effects of moisture tendencies on the environment forcing. The total forcing for buoyancy change at the parcel lifted level is simply (the sum of the parcel and environment forcing). The mathematical forms of these forcing terms on the right sides of (1) and (2) and how they are linked to buoyancy changes are provided in T14. Note that one exception to this concerns the final terms on the right side of each of these equations, which are strongly influenced by surface heat and moisture fluxes but, unlike in T14, involve tendencies obtained directly from the PBL scheme. The part of from (1) and (2) that does not include this PBL forcing (PBLP + PBLE) is referred to as the grid-resolved forcing.

We compute the forcing budget from 1630 to 1930 UTC over the rectangle shown in Fig. 17b following the approach detailed in T14. In the present study, we select 0.3-km AGL for the parcel origination level, since it both resides within the PBL for the entire 3-h destabilization period and is situated above unrepresentative near-surface superadiabatic layers. Analyzing the forcing during the 3 h prior to CI provides a long enough time interval to have confidence that the forcing is relevant to the overall thermodynamic destabilization while short enough to be confined to a distinct regime in the diurnal cycle when strong surface heating occurs, which often precedes CI near drylines.

For each horizontal grid point within the rectangle, a 50-hPa-deep parcel centered at its origination level is perturbed using temperature and moisture tendencies calculated from instantaneous forcings at . To obtain the perturbed parcel is then pseudoadiabatically displaced to a mean 3-h Bmin level , and its resulting virtual temperature is compared to that of an unperturbed parcel pseudoadiabatically displaced to . The environmental perturbation is obtained by comparing environmental virtual temperatures perturbed by instantaneous forcings at to unperturbed virtual temperatures at . These two comparisons are performed at 15-min intervals (i.e., 13 times), and the resulting forcings, , are both time averaged for the 3-h destabilization period and line averaged for 150 km across the rectangle. To assess the accuracy of the budget, we compare the average forcing for the 3-h buoyancy change to similar line averages of the actual 3-h buoyancy change (ΔBUOY) at which approximates the 3-h Bmin change (ΔBMIN) at temporally varying Bmin levels .

2) Budget results for member 6 and comparison to member 9

The line-averaged vertical cross sections in Figs. 18a and 18b indicate a time-averaged thermally direct circulation occurring over the budget calculation region (Figs. 17b–d) that has strong ascent at the east edge of the dryline and weak subsidence maximized about 50 km from the dryline center. This mesoscale vertical circulation approximately coincides with the zone of near-zero Bmin at the end of the 3-h time interval (Fig. 17b), after which CI occurs. Figure 18c reveals that ΔBUOY nicely approximates ΔBMIN in the region east of the final dryline position (Fig. 18a). Here, the total forcing for ΔBUOY has a sharper spatial peak than ΔBUOY itself, but this error is a relatively small percentage of ΔBUOY (Fig. 18c).

Fig. 18.
Fig. 18.

(top) Illustration of 3-h time-averaged (1630–1930 UTC) and 150-km line-averaged thermally direct vertical circulation (red arrows) prior to CI: (a) vertical motion (color shading, cm s−1) and 1930 UTC water vapor mixing ratio (black contours with 2 g kg−1 intervals); (b) horizontal winds (m s−1) and 1930 UTC potential temperature (black contours with 1-K intervals). (c) The 3-h Bmin change (K) for model level 4 (~0.3 km AGL) air parcels (blue dashed–dotted), 3-h buoyancy change for model level 4 air parcels (solid cyan), its total forcing (solid black), and the error in the forcing (orange dashed). (e) Portion of the total forcing (solid black) due to parcel changes (solid red) and due to environment changes (blue). (d) The components of the parcel forcing (red solid), including horizontal temperature advection (red dashed), horizontal moisture advection (red dotted), and the sum of the temperature and moisture tendencies from the PBL scheme (red dashed–dotted). (f) The components of the environment forcing (solid blue), including those related to vertical motions (blue dotted), horizontal temperature advections (blue dashed) and temperature tendencies from the PBL scheme (blue dashed–dotted). In (c)–(f), the buoyancy changes are evaluated at the 3-h mean Bmin level [thick dark blue dashed line in (a),(b)] The dashed vertical rectangles indicate the CI zone. All plots are for quantities line averaged across the rectangles in Figs. 17b–d.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Near the dryline, the forcing of the previous 3 h is dominated by changes to the parcel (Fig. 18e). The parcel changes themselves are dominated by tendencies from the PBL scheme (owing to strong surface heating) but are significantly enhanced in the immediate vicinity of the dryline (x ~ 0–20 km) by contributions from warm advection (Fig. 18d), evident along and slightly east of the dryline in Figs. 7a and 7c. Forcing from terms related to vertical motion [VTADVP and VMADVP from (1)] is over an order of magnitude smaller at the parcel origination level (0.3 km AGL) and is not included in Fig. 18d.

The environment forcing at the 3-h mean Bmin level (Fig. 18e) is maximized 40–60 km east of the final dryline position (Fig. 18a) and thus contributes to spreading the zone of negligible Bmin eastward, which was shown to influence the earlier sustained CI in this ensemble member (section 4c). The environment forcing is dominated by cold advection (HTADVE in Fig. 18f), which contrasts with the daytime cold front/dryline case in T14, where flow above the PBL was much weaker and vertical motion effects dominated the environment forcing.

The time-averaged cold advection in the present case has components owing to both the thermally direct circulation normal to the dryline and the portion of the temperature gradient along the dryline (Fig. 19). Though vertical motion does not contribute directly to the positive buoyancy forcing diagnosed in the budget, the related vertical displacements play an important role by strongly influencing the temperature gradients near the Bmin level. This is illustrated by an analysis of 3-h back trajectories emanating from 1.7 km MSL (the approximate Bmin level; cf. Figs. 18a,b), which coincide horizontally with both the region of near-zero Bmin at the 1930 UTC release time (Fig. 20a) and the relatively cool region above parcel source levels east of the dryline from 1630 to 1930 UTC (Fig. 19). These trajectories all originate east of the eastward-translating dryline (Fig. 20b) and have net upward displacements during the 3-h period (Fig. 20c), with the orange trajectories finishing closest to the dryline rising the most.

Fig. 19.
Fig. 19.

Analysis of 1.7-km MSL horizontal temperature advection (contours with interval of 1°C h−1; negative values dashed and zero contour eliminated), winds (barbs as in Fig. 1), and potential temperature (color shading, K) averaged from 1630 to 1930 UTC using 15-min model output for d02 (Fig. 4) of ensemble member 6. The white contours are 8 and 12 g kg−1 surface water vapor mixing ratio contours illustrating the approximate front and rear positions of the surface dryline at 1930 UTC. The yellow rectangle indicates the location of the vertical cross sections and forcing budget analyses in Fig. 18, which are line averaged along the minor axis (northeast–southwest direction) of the rectangle.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 20.
Fig. 20.

The 3-h back trajectories (colored arrows) from 1.7 km MSL, approximating the mean (i.e., 3 h) Bmin level for parcels originating from model level 4 (~0.3 km AGL) plotted over fields of Bmin (°C, colored shading) from model level 4 and the 8 and 12 g kg−1 surface water vapor mixing ratio isopleths (black) approximating the dryline location at (a) 1930 (back trajectory start) and (b) 1630 UTC 19 May 2013 (back trajectory finish). (c) Average heights of the five groups of 7–8 color-coded trajectories organized in rows parallel to, and at different distances from, the dryline at 1930 UTC, with the orange (cyan) trajectories ending up being closest to (farthest away) the dryline. The yellow rectangles included for reference are identical to those in Figs. 17b–d and represent the region of the line-averaged cross sections and budget for buoyancy change in Fig. 18.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

These different analyses collectively indicate that vertical motion in the ascending branch of the thermally direct circulation near the dryline contributes to the local cool anomaly near the PBL top (Fig. 18b). The cool air is advected eastward above parcel origination levels by the southwesterly flow and helps remove negative buoyancy for several tens of kilometers east of the dryline. This provides an environment that allows storms that are initiated along the dryline to intensify and successfully mature as they develop vertically and move east of the dryline in ensemble member 6.

There is stronger overall forcing for buoyancy changes near the dryline in member 6 than in member 9, which is dominated by differences in total parcel forcing (Fig. 21a) and contributes to corresponding differences in negative buoyancy (Fig. 12a) and timing of CI (Figs. 6a,b). The parcel forcing differences from x = 0–30 km are, in turn, dominated by significant differences in PBLP and HMADVP between members (Fig. 21a). The smaller positive buoyancy forcing from PBLP in member 9 from x = 0–30 km (Fig. 21a) is consistent with the deeper PBL simulated in this location than that for member 6 (not shown), which, for the same surface heat and moisture fluxes, favors smaller parcel virtual temperature and moisture changes for member 9. The differences in PBLP and HMADVP between members 6 and 9 are interrelated since near-surface air from the deeper and drier PBL east of the primary dryline in member 9 is advected by the near-surface southwesterlies, contributing to the more widespread dry tongue with qυ < 12 g kg−1 at 1930 UTC in member 9 (cf. Figs. 7b,c).

Fig. 21.
Fig. 21.

(a) Parcel forcing terms [section 5b(1)] for ensemble members 6 (solid) and 9 (dashed–dotted), including the total parcel forcing (bold black) and parcel forcing components of horizontal temperature advection (red), horizontal moisture advection (cyan), and combined temperature and moisture tendencies from the PBL scheme (orange). (b) Environment forcing terms [section 5b(1)] for ensemble members 6 (solid) and 9 (dashed–dotted), including the total environment forcing (black), environment forcing components of horizontal temperature advection (red), those related to vertical motions (violet), and the combined temperature and moisture tendencies from the PBL scheme (orange). Forcings are 150-km line averages for a vertical cross section taken normal to the dryline, which is time averaged from 1630 to 1930 UTC.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

The greater parcel forcing along and immediately east of the dryline in member 6 is partly compensated by smaller environment forcing at the parcel 3-h mean Bmin level than for member 9 (bold black curves at x = 0–30 km in Fig. 21b). The much sharper peak in the total environment forcing in member 6 (Fig. 21b) is a reflection of the more intense and organized thermally direct dryline circulation in member 6 (Figs. 18a,b) than for member 9 (not shown).

6. Composite analyses of thermodynamic forcing for CI within the ensemble

In this section, we analyze the forcing for negative buoyancy changes, defined in section 5b(1), in different composites of simulations selected from the 10-member ensemble. The first composite analysis (section 6a) discriminates between conditions in three ensemble members, where the timing and spatial coverage of CI over central Oklahoma is similar to observations, from conditions in three other members, where CI in central Oklahoma is both delayed and significantly less widespread. The second analysis (section 6b) uses a broader composite of five members that produced timely CI over central Oklahoma. For this analysis, we present horizontal plots of the forcing of negative buoyancy removal but without averaging in the cross-dryline direction. Here, we are better able to examine the relationships among the spatial characteristics of the different forcings, dryline intensity, and subsequent rainfall frequencies than in the earlier reduced-dimension analyses. In this second composite analysis, we also provide a more detailed quantification of both the errors and limitations of the Bmin forcing budget.

a. Comparison of composites of ensemble members with different CI timing and coverage

We now compare composites of three-member subensembles, including one in which CI is most concentrated in central Oklahoma (members 6, 8, and 10) and another where CI is either absent or substantially delayed in this region (members 2, 4, and 9). We shall refer to these subensembles as single dryline (SDRY; members 6, 8, and 10), and double dryline (DDRY; members 2, 4, and 9), which reflects their structural differences.

We composite the different members in these subensembles relative to the 1930 UTC dryline position (location of qυ = 8 g kg−1) in central Oklahoma. For each member of these two subensembles, Bmin budget calculations are performed identically to those described earlier for ensemble members 6 and 9 [section 5b(1)] and are similarly line averaged. The results from the three members within each of the two subensembles of line averages (solid and dashed rectangles in Fig. 5) are then averaged to produce these two composites.

As found in the earlier Bmin comparison between ensemble members 6 and 9 (Fig. 12a), there are important differences in composites of 150-km line-averaged Bmin in the SDRY and DDRY subensembles (Fig. 22) within which these two members respectively reside. In particular, the SDRY composite has Bmin magnitudes at 1900 UTC that approach zero and are ≥0.3 K smaller than DDRY out to 40 km from the dryline center (Fig. 22). Much stronger maximum ascent occurs in the SDRY composite, which produced earlier CI (Fig. 23a) than in the DDRY composite with delayed CI (Fig. 23b). In the DDRY composite, the maximum ascent is also shifted eastward toward the secondary PBL moisture gradient (Fig. 23b), which is not evident in the SDRY composite (Fig. 23a). The less organized mean vertical circulation in the DDRY composite is consistent with a decrease in intensity of environment forcing for ΔBUOY compared to the SDRY composite (Figs. 23c,d) and the eastward shift of its maximum to the location east of the developing secondary moisture gradient (Fig. 23d).

Fig. 22.
Fig. 22.

As in Fig. 12a, but for the composites from subensembles that include members 6, 8, and 10 (SDRY), and members 2, 4, and 9 (DDRY). The line-averaged values of Bmin in these composites do not include effects of entrainment of environmental air (as in the corresponding solid curves in Fig. 12a).

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

Fig. 23.
Fig. 23.

(a),(c) As in Figs. 18a,e, respectively, but for a composite of ensemble members 6, 8, and 10 along the solid rectangles shown in Figs. 5f,h,j and line averaged in the northeast–southwest direction across those rectangles. (b),(d) As in Figs. 18a,e, respectively, but for a composite of ensemble members 2, 4, and 9 along the dashed rectangles shown in Figs. 5b,d,i and line averaged in the northeast–southwest direction across those rectangles.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

The effects of greater upward vertical displacements in the SDRY composite is reflected in the greater depth of upwelling moisture extending downwind (east) of the time-averaged vertical velocity maximum (Fig. 23a) than that for DDRY (Fig. 23b). The differences between the subensembles in the total forcing near the primary dryline (x ~ 0–15 km), which favors earlier CI in SDRY, are largely a reflection of the maximum 3-h parcel forcing being greatest near this location in SDRY (Fig. 23c). In contrast, the parcel forcing in DDRY is greatest near the secondary moisture gradient (x ~ 50 km in Fig. 23d), where, because of larger initial Bmin magnitudes owing to longitudinal gradients (e.g., Fig. 20b), CI is delayed relative to SDRY.

b. Composite of ensemble members 1, 3, 6, 8, and 10

We now examine a five-member subensemble containing members 1, 3, 6, 8, and 10. These members (Figs. 5a,c,f,h,j) are distinguished from others in the full 10-member ensemble by having CI within both 50 km and 45 min of where and when it actually occurred. Since the locations of CI can shift substantially from that of its first instance over a mesoscale region, we composite analyses from these five ensemble members relative to centroids of >35-dBZ reflectivity 1 h after the first cell is detected. The green contours in Fig. 24 indicate frequencies of model-derived reflectivity > 35 dBZ relative to the dryline position (gray shading) at the time of CI onset 1 h earlier.

Fig. 24.
Fig. 24.

Composite forcing budget for 3-h buoyancy change (K) diagnosed at the 3-h mean Bmin levels for air parcels originating at model level 4 (~0.3 km AGL) in ensemble members 1, 3, 6, 8 and 10. Gray shading indicates surface water vapor mixing ratios between 8 and 12 g kg−1, approximating dryline location at the end of the 3-h buoyancy forcing period; The green contours indicate frequencies of model-derived radar reflectivity exceeding 35 dBZ 1 h after the 3-h buoyancy forcing period. (left) (a) Net forcing for 3-h buoyancy change (1-K contour interval; negative values dotted) and (d) its error (0.5-K contour interval; negative values dotted; zero contour omitted). (middle) As in (a), but due to (b) grid-resolved and (e) PBL-scheme forcings. (right) As in (a), but due to (c) parcel changes at its origination level and (f) environment changes at the 3-h mean Bmin level of the parcel. The semitransparent colored shading indicates the region where there are substantial differences between ΔBMIN and the ΔBUOY that the forcing in (a) attempts to diagnose. Analyses of the forcing in this shaded region are less representative of forcing for ΔBMIN.

Citation: Monthly Weather Review 143, 9; 10.1175/MWR-D-15-0133.1

The 3-h buoyancy change prior to CI predicted by [section 5b(1)] exceeds 4°C for ~100 km ahead of the most intense section of the dryline moisture gradient (Fig. 24a). This forcing overpredicts the actual simulated 3-h ΔBUOY in the region, but these errors are reasonably small (~1°C or <25%; cf. Figs. 24a,d).

Note that the Bmin forcing budget is greatly simplified by evaluating the Tυ changes to the parcel and the environment at the temporal mean Bmin level during the 3-h time interval over which the forcing is calculated [section 5b(1)]. However, a limitation of this approach is the requirement that thermodynamic quantities evolve relatively slowly and continuously during the time interval for which is calculated in order for the 3-h buoyancy change at , which the forcing attempts to diagnose, to be representative of the actual 3-h Bmin change. Thus, we confine our interpretation of the forcing budget not only to locations with small budget residuals (or small percentage errors) but also to regions where ΔBUOY ≈ ΔBMIN. In the current case of a translating daytime dryline, appropriate horizontal locations include those that are east of the dryline and parcel source levels that reside with the PBL during this entire 3-h time interval. In the red-shaded region of Fig. 24, the forcing calculations have less fidelity, because ΔBUOY fails to accurately approximate ΔBMIN. This inaccuracy is related to sudden and large variations in local Bmin levels resulting from the dryline passage.

In the destabilizing region occupying the 100-km zone east of where the dryline is most intense and CI eventually occurs, maximum contributions to the total forcing (Fig. 24a) from the grid-resolved forcing (Fig. 24b) and the PBL scheme (Fig. 24e) of >2.5 K (3 h)−1are comparable. This is consistent with Wang and Xue (2012), who, by disabling surface fluxes in model sensitivity studies, concluded that surface heating and moistening was important to the CI along an IHOP dryline. The greater spatial variability in the grid-resolved forcing diagnosed in the current analysis (Fig. 24b) indicates its greater importance in focusing where CI is most favored.

A relatively thin strip of enhanced forcing for 3-h buoyancy changes exceeding 2.5°C from parcel changes at their origination level (Fig. 24c) extends southward along and slightly ahead of the dryline (Fig. 24c). This region roughly corresponds to the ~30-km-wide zone of vanishing Bmin (e.g., Fig. 17b). Unlike the parcel forcing, the net environment forcing for buoyancy change is concentrated where both the dryline (Fig. 24f) and its time-averaged thermally direct circulation (e.g., Figs. 18a,b) are strongest. At a distance of ~30 km east from where the dryline is most intense, the magnitude of buoyancy reduction from environment forcing (i.e., cooling above the parcel source level) becomes comparable to that of the parcel forcing (cf. Figs. 24c,f). It is at this approximate location that frequencies of subsequent convection are greatest (green contours in Figs. 24c,f).

7. Summary and discussion

In this study, we use a 10-member ensemble of convection-permitting simulations with 3-km horizontal grid spacing to examine afternoon convection initiation (CI) along a central Oklahoma dryline in a case that produced tornadic supercells during MPEX. A subset of the ensemble members accurately reproduced both the timing and approximate location of CI, while, in others, it was both delayed and less widespread than observed.

In higher-resolution simulations with horizontal grid spacing of 1 km, mesoscale thermodynamic differences in the environment, including CAPE magnitudes and the width (extending east of the dryline) of the zone of negligible negative buoyancy for PBL parcels, acted synergistically to account for CI timing and location differences. In an ensemble member where sustained CI was delayed, updraft cells were initiated where HCRs intersected the dryline and these updrafts reached their LFC. However, as the vertically developing updrafts moved off the dryline in strong environmental southwesterly flow, they encountered unfavorable increases in negative buoyancy before they could mature and produce rain. In contrast, an ensemble member that produced sustainable CI earlier along the dryline had a broader zone of vanishing negative buoyancy and larger CAPE. There the greater width of the zone of negligible negative buoyancy extending eastward from the dryline provides more time for incipient storms to mature, while larger CAPE hastens the development of stronger free-tropospheric updrafts. In both ensemble members, once fully developed, storms are able to persist for several hours within a ~100-km region farther east, which, despite having large CAPE, retains appreciable negative buoyancy (ΔTυ < −1°C). The simulations of Ziegler et al. (2010) indicated a similar persistence of mature supercells after encountering an inversion layer overlying the PBL.

In the present case, we quantified the lower-tropospheric negative buoyancy using the parcel buoyancy minimum Bmin, discussed in more detail in Trier et al. (2014). Here, Bmin, which is insensitive to entrainment of dry environmental air, is well correlated with the integral quantity CIN in both the model and in simultaneous collocated MPEX research upsondes with enhanced vertical resolution. Though comparisons with the upsondes indicated a model bias in Bmin magnitude, which is primarily influenced by excess PBL moist static energy related to the selected PBL scheme, the simulated Bmin trends are quite similar to observed ones. This provides confidence in its use for budget calculations that provide quantification of the roles of different physical processes on the removal of negative buoyancy in afternoon dryline environments.

A time-averaged thermally direct vertical circulation combined with surface heating reduced Bmin to negligible magnitudes for a width of several tens of kilometers in an ensemble member that produced realistic timing and coverage of CI. By combining a local Bmin forcing budget for the buoyancy tendency of PBL parcels and trajectory analysis, we diagnosed that the ascending branch of the thermally direct vertical circulation contributed to cooler air near the top of the PBL. This air was advected eastward in the strong southwesterly flow above parcel source levels, thereby increasing the eastward extent of negative buoyancy reduction that contributed to CI originating along the dryline being sustained as it advanced beyond its eastern edge.

Comparison of a composite of three members exhibiting this type of CI behavior with a composite of three members exhibiting a significant delay in sustained CI revealed considerable differences in the time-averaged vertical circulation normal to the dryline. In the composite of cases with delayed CI, the maximum time-averaged ascent is shifted east toward a developing secondary moisture gradient, and the forcing for the negative buoyancy reduction near the primary dryline was weaker than in the other composite that initiated convection both at the correct earlier time and farther west.

In a composite of five ensemble members where CI occurred at approximately the correct time and locations, surface heating and moistening (through tendencies from the PBL scheme) account for approximately ½ of the 3-h negative buoyancy reduction prior to CI. However, not surprisingly, the grid-resolved thermodynamic forcing that accounts for the other ½ of the negative buoyancy reduction has far greater spatial variability and is thus more influential in determining where the maximum net forcing occurs, which itself is spatially correlated with greatest frequencies of subsequent deep convection in the composite.

Our calculation of Bmin forcing budgets enables attribution of negative buoyancy reductions related to both local changes in virtual temperature and moisture at relevant PBL parcel source levels and changes to the virtual temperature above them. The forcing for maximum changes at parcel source levels, owing to surface fluxes and local enhancements from warm advection, are maximized within the zone of a few tens of kilometers east of the dryline, where the negative buoyancy becomes vanishingly small and extends along the entire length of the dryline. Near the dryline, the environment forcing for buoyancy changes due to cooling above parcel source levels is smaller but becomes comparable to the parcel forcing at ~30 km from the dryline. Moreover, unlike for the parcel forcing, this environment forcing is most concentrated where both the dryline and its time-averaged vertical circulation is most intense. Thus, we conclude that the environment forcing above the parcel origination levels plays a primary role in 1) maximizing the net forcing for negative buoyancy reduction within a specific region along the dryline and 2) extending the region of negligible buoyancy eastward, supporting successful CI in the environment of strong westerly vertical shear.

In this study, clear differences in CI location, timing, and coverage have been tied to differences in forcing for removal of lower-tropospheric negative buoyancy near the dryline in an ensemble of convection-permitting simulations. From a predictability standpoint, additional work is needed to understand how these differences in the dryline thermodynamic environment develop from perturbations to the initial and boundary conditions among ensemble members. Torn and Romine (2015) indicate that subtle differences in upstream midtropospheric potential vorticity influence dryline location and precipitation for the current case. Further research is needed to determine how these aspects might possibly be connected through corresponding differences in the lower-tropospheric dryline environment.

Model PBL parameterizations have a demonstrated influence on the lower-tropospheric thermodynamic environment near simulated drylines. The mesoscale vertical circulation, which strongly influenced regions of CI in the current study, was found by Clark et al. (2015) to be a robust aspect of simulations that used different PBL schemes (see their Fig. 14). However, differences in the strength of the vertical mixing and related PBL depth among various schemes (Clark et al. 2015) could affect their contribution to the forcing of negative buoyancy removal due to surface heating. This is because, for a given surface heating, temperature and moisture tendencies will typically be larger (smaller) in a shallower (deeper) PBL. Additional research is needed to establish the response of the buoyancy forcing to these sensitivities.

Acknowledgments

The authors acknowledge Chris Davis (NCAR) for developing earlier versions of the Bmin diagnostic code used in this study and Morris Weisman (NCAR) for alerting us to the strong thermodynamic destabilization in the 19 May MPEX case. Chris Davis and Kristen Rasmussen (NCAR) are acknowledged for helpful internal reviews of this manuscript, which benefited further from the comments of four anonymous reviewers. We extend thanks to all participants for their hard work during MPEX and to the National Science Foundation for supporting this successful field experiment. The current research was performed as part of NCAR’s Short Term Explicit Prediction (STEP) program, which is supported by National Science Foundation funds for the U.S. Weather Research Program (USWRP). We acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation.

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