Editorial Type:
Article
Article Type:
Research Article

Observations and Simulation of Elevated Nocturnal Convection Initiation on 24 June 2015 during PECAN

Stanley B. Trier National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Stanley B. Trier in
Current site
Google Scholar
PubMed Close
,
Scott D. Kehler Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada

Search for other papers by Scott D. Kehler in
Current site
Google Scholar
PubMed Close
, and
John Hanesiak Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada

Search for other papers by John Hanesiak in
Current site
Google Scholar
PubMed Close
Online Publication:
01 Feb 2020
Print Publication:
01 Feb 2020
DOI:
https://doi.org/10.1175/MWR-D-19-0218.1
Page(s):
613–635
Free access

Abstract

The environment of elevated nocturnal deep convection initiation (CI) on 24 June 2015 is investigated using radiosonde data from the Plains Elevated Convection at Night (PECAN) field experiment and a convection-allowing simulation. Elevated CI occurs around midnight in ascending westerly flow above the northeastern terminus of the nocturnal low-level jet (LLJ) several hundred kilometers poleward of the leading edge of a surface warm front. This CI originates from within preexisting banded altocumulus clouds that are supported by persistent large-scale ascent within the entrance region of a midtropospheric jet streak. Model trajectories calculated backward from convective updraft cores during CI indicate abrupt lifting at the leading edge of the surface front during the late afternoon to altitudes above that of the subsequent southerly LLJ. This air remains significantly subsaturated during northward movement until after several hours of weaker but persistent ascent within the highly elevated westerly airstream during the evening. Unlike in many previous studies of frontal overrunning by the LLJ, strong local drying occurs within the LLJ core. Nevertheless, vertical displacements from persistent mesoscale ascent were sufficient for trajectory air parcels to reach their LFC and sustain deep convection. The mesoscale upward displacement along trajectories is well explained by isentropic upglide associated with frontal overrunning at horizontal distances greater than 100 km from the CI and subsequent mature convection. However, the significant additional mesoscale vertical displacements needed for deep CI to occur in the westerlies above the horizontally convergent ~100-km-wide LLJ terminus region, were associated with local cooling and are not accounted for by steady isentropic upglide.

Current affiliation: Weatherlogics Inc., Winnipeg, Manitoba, Canada.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Plains Elevated Convection At Night (PECAN) Special Collection.

Corresponding author: Stanley B. Trier, trier@ucar.edu

Abstract

The environment of elevated nocturnal deep convection initiation (CI) on 24 June 2015 is investigated using radiosonde data from the Plains Elevated Convection at Night (PECAN) field experiment and a convection-allowing simulation. Elevated CI occurs around midnight in ascending westerly flow above the northeastern terminus of the nocturnal low-level jet (LLJ) several hundred kilometers poleward of the leading edge of a surface warm front. This CI originates from within preexisting banded altocumulus clouds that are supported by persistent large-scale ascent within the entrance region of a midtropospheric jet streak. Model trajectories calculated backward from convective updraft cores during CI indicate abrupt lifting at the leading edge of the surface front during the late afternoon to altitudes above that of the subsequent southerly LLJ. This air remains significantly subsaturated during northward movement until after several hours of weaker but persistent ascent within the highly elevated westerly airstream during the evening. Unlike in many previous studies of frontal overrunning by the LLJ, strong local drying occurs within the LLJ core. Nevertheless, vertical displacements from persistent mesoscale ascent were sufficient for trajectory air parcels to reach their LFC and sustain deep convection. The mesoscale upward displacement along trajectories is well explained by isentropic upglide associated with frontal overrunning at horizontal distances greater than 100 km from the CI and subsequent mature convection. However, the significant additional mesoscale vertical displacements needed for deep CI to occur in the westerlies above the horizontally convergent ~100-km-wide LLJ terminus region, were associated with local cooling and are not accounted for by steady isentropic upglide.

Current affiliation: Weatherlogics Inc., Winnipeg, Manitoba, Canada.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Plains Elevated Convection At Night (PECAN) Special Collection.

Corresponding author: Stanley B. Trier, trier@ucar.edu
Keywords: Convective storms/systems; Deep convection; Mesoscale processes; Vertical motion

1. Introduction

Nocturnal deep convection over the central United States commonly organizes into mesoscale convective systems (MCSs) or complexes (MCCs, Maddox 1980), which are typically influenced by regional-scale warm advection (Maddox 1983) associated with the nocturnal low-level jet (LLJ). A frequent characteristic of these large precipitation systems is their elevated inflow of large moist static energy occurring in a layer above the surface. MCSs and MCCs are most likely to be elevated when they occur poleward of surface quasi-stationary or warm fronts because of a deeper surface-based layer of large static stability than that which occurs solely from nocturnal radiative cooling of the surface.

The Plains Elevated Convection at Night (PECAN) field project (Geerts et al. 2017) occurred over the central United States during 1 June–16 July 2015 in an effort to improve understanding of nocturnal elevated convection. One focus of PECAN was to study physical processes important to convection initiation (CI) in the nocturnal environment, which is difficult to forecast in terms of timing and location (e.g., Geerts et al. 2017; Weckwerth et al. 2019). In the current study we use PECAN radiosonde data and a convection-allowing simulation to examine physical processes contributing to elevated CI during PECAN intensive observing period (IOP) 14 on 24 June 2015.

Reif and Bluestein (2017) found that CI occurred on the cold side of surface fronts or boundaries (CS CI events) in 35% of nocturnal CI cases from a 20-yr central U.S. climatology, which is consistent with the earlier results of Kane et al. (1987) for the location of mature MCSs. Trier et al. (2017) documented precursor mesoscale ascent in each of their several analyzed cases of CI occurring north of surface fronts during PECAN. Such mesoscale ascent is often associated with the air within LLJs “overrunning” the sloping upper surface of the front (Fig. 1). Reif and Bluestein (2017) found that 74% of their CS CI cases occurred with a LLJ, and Weckwerth et al. (2019) found frontal overrunning by the LLJ to be either a contributing or primary factor governing initiation in about 1/3 of CI days during PECAN.

Fig. 1.
Fig. 1.

Schematic diagram illustrating idealized flow characteristics in a north–south oriented vertical cross section through a surface warm front. The nocturnal low-level jet (LLJ, heavy black arrow) is ascending above the warm front (red line with conventional semicircle symbols pointing toward cold air). The thin arrows represent wind vectors within the plane of the cross section and the circled dots indicate front-parallel flow (out of the page) within the cool and moist air beneath the frontal surface. Adapted from Trier and Parsons (1993).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

For the conceptual model of Fig. 1 introduced in Trier and Parsons (1993), it was argued that warm and moist air within the LLJ core could be transported upward approximately along the sloping isentropic surfaces of fronts and influence elevated CI up to several hundred kilometers poleward of their leading edge. Here, air can be lifted to either its level of free convection (LFC) or to some level where convection inhibition (CIN) is sufficiently small that CI may be more easily achieved by other means, including bores (Haghi et al. 2019) and trapped gravity waves (Wilson et al. 2018).1 Moore et al. (2003, their Fig. 14) refined this conceptual model by incorporating additional mesoscale effects including lower-tropospheric frontogenesis (e.g., Colman 1990; Augustine and Caracena 1994) and deep coupling from thermally direct vertical circulations associated with upper-tropospheric jet streaks. Peters et al. (2017) discussed how horizontal position errors in simulated convection could be explained by initialization errors in upstream surface moisture being subjected to the type of isentropic upglide idealized in Fig. 1.

Though the idealized concept of steady 2D isentropic upglide (Fig. 1) may explain CI or sustenance of deep convection in some cases, there are relevant unresolved issues pertaining to its application in estimating air-parcel displacements in frontal overrunning environments (e.g., Weckwerth et al. 2019). For instance, wind profiles in warm-advection zones near surface fronts and the nocturnal LLJ typically display strong veering (i.e., clockwise directional change with height) that cannot be adequately represented with a simple 2D model. In addition, frontal overrunning by the mesoscale nocturnal LLJ sometimes occurs in conjunction with synoptic and mesoscale forcings, which can, themselves, have a significant impact on CI. Furthermore, these forcings may lead to frontogenetical vertical circulations, which can result in local temperature changes, and are thus unlikely to be well represented by steady isentropic upglide.

In this paper, we examine the role of some of these other effects for a case in which the onset of CI occurs near a mesoscale region of frontal overrunning by the nocturnal LLJ. Section 2 provides an overview of CI and subsequent growth of elevated convection into a nocturnal MCS. Data and analysis techniques are described in section 3. Section 4 documents the CI environment using upstream radiosonde data from PECAN and section 5 discusses results from a supporting convection-allowing simulation of the event.

2. Overview of nocturnal convection on 24 June 2015

The 24 June 2015 elevated CI case was selected by Stelten and Gallus (2017) to exemplify their type-I pristine nocturnal convection initiation, which occurs north of a surface boundary or front and is associated with a LLJ. In this section, we further document the relationship of the convection to the surface front with mosaics of maximum reflectivity in a vertical column (MREF) from the network of NEXRAD Doppler (WSR-88D) radars and objectively analyzed National Weather Service (NWS) surface airways observations (SAOs).

Recent studies (e.g., Parker 2008; Schumacher 2015; Schumacher and Peters 2017; Hitchcock et al. 2019) have emphasized many nocturnal precipitation systems that appear to be elevated can ingest sizeable amounts of near-surface air, which may be critical to their intensity and maintenance. Here, our determination of the elevated character of the convection on 24 June is based on satellite data (section 4a), the thermodynamic structure of nearby upstream soundings (section 4b), and analyses from a numerical simulation (section 5).

Prior to the CI of interest, a slow-moving surface warm front lies across northern Kansas (Fig. 2a) at 0400 UTC 24 June (UTC = LST +5 h), which is about 2 h after sunset. The front separates a very warm surface air mass with southerly winds from much cooler conditions (|Δθ| ≈ 10 K) in easterly flow north of the front.

Fig. 2.
Fig. 2.

NEXRAD WSR-88D radar mosaic of maximum reflectivity in a vertical column (MREF, color shadings) and objectively analyzed surface horizontal winds and potential temperature (brown contours, 2-K intervals) at (a) 0400, (b) 0600, (c) 0800, and (d) 1000 UTC 24 Jun 2015. The surface horizontal wind symbols have half barb = 5 kt (1 kt ≈ 0.51 m s−1) (~2.5 m s−1), full barb = 10 kt (~5 m s−1), and circles < 2.5 kt. The annotated symbols indicate the locations of radiosonde data discussed in the text.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The earliest deep convection to influence the PECAN region was a small MCS that developed during the early evening near the Colorado–Nebraska–Kansas border region (Fig. 2a). During the next 2 h this MCS begins to weaken as it moves eastward along the surface frontal zone (Fig. 2b). However, mesoscale bands of new organized deep convection develop farther northeast over east-central Nebraska (immediately north of MG3) and over western and central Iowa (northeast of KOAX). Though located up to several hundred kilometers to its north, these CI events have an orientation similar to the surface front (Fig. 2b). The two bands within the easternmost region of CI (Fig. 2b) eventually coalesce into a single nocturnal MCS (Fig. 2d). This elongated MCS had training line-adjoining stratiform organization (TL/AS, Schumacher and Johnson 2005), which often leads to repeated heavy rainfalls over the same area. In the current case this organization contributed to overnight rainfalls of 3 to 5 in. (~75 to 125 mm) over central Iowa (NCDC 2015).

3. Data and methods

a. Data

Besides the radar and surface data discussed in the previous section, satellite and operational radiosondes are used in our analysis of CI and its mesoscale environment. The satellite data include both visible imagery from the Geostationary Operational Environmental Satellite-13 (GOES-13) at 1-km resolution, and 4-km resolution infrared brightness temperature imagery. Twenty-two NWS radiosondes surrounding the PECAN region are also used in this study.

In total, 38 radiosondes from the PECAN radiosonde network operating on IOP 14 (Fig. 3) constitute the primary data used this study. This network included soundings from six fixed profiling (FP) sites (Holdridge and Turner 2015; Vermeesch 2015; Clark 2016; UCAR/NCAR—Earth Observing Laboratory 2015, 2016a,b) in the PECAN Integrated Sounding Array (PISA) and four mobile profiling (MP) facilities of the PISA (Knupp 2015; Klein et al. 2016; Wagner et al. 2016; UCAR/NCAR—Earth Observing Laboratory 2016c). A more detailed description of the PISA network is found in Geerts et al. (2017).

Fig. 3.
Fig. 3.

PECAN research radiosonde network during intensive observing period (IOP) 14 on 24 Jun 2015. The transect AA′ indicates the location of vertical cross sections (Fig. 9) constructed using PECAN radiosondes and the triangles indicate locations of mesoscale vertical velocity estimates obtained from radiosonde data (Figs. 10 and 20) and model output (Fig. 20) at their vertices.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

In addition to the PISA soundings, which were typically launched with 180-min frequency, mobile GPS (MG) soundings (Ziegler et al. 2016) having 90-min frequency were synchronously launched from two other locations prior to and during CI (0300–0600 UTC 24 June). These facilities included MG3 operated by Colorado State University and MG1 operated by the National Severe Storms Laboratory (NSSL) in conjunction with North Carolina State University. MG3 was located in the immediate low- to midtropospheric inflow of the convective band that forms by 0600 UTC 24 June in east-central Nebraska (Fig. 2b). Though significantly farther from CI locations, MG1 was the closest available upstream sounding location to the larger nocturnal convective development over western and central Iowa (Fig. 2b).

b. Analysis methods

The PECAN radiosondes are used to construct vertical cross sections that examine the evening evolution of frontal structure and the nocturnal LLJ along line AA′ in Fig. 3. This transect AA′ has a northeast terminus located close to the two areas of CI indicated in Fig. 2b. In constructing these vertical cross sections, 0300 and 0600 UTC 24 June data from FP3, MP3, MP2, and MG1 (NSSL1) were projected onto line AA′, which is approximately parallel to the surface potential temperature gradient (i.e., normal to the front) near MP1 (cf. Figs. 2a,b).

These radiosonde data were then vertically interpolated to Δz = 50 m levels from the surface to ~500 hPa to examine evolution of winds and thermodynamic vertical structure at upstream locations near the time of CI. To assess which sounding layers supported CI, vertical profiles of convective available potential energy (CAPE) and convective inhibition (CIN) based on virtual temperature and water vapor mixing ratio (Doswell and Rasmussen 1994) were calculated using 500-m-deep averaged air parcels centered on the height of each Δz = 50-m sounding level.

Trier et al. (2017) found that mesoscale vertical motions had a significant influence on thermodynamic destabilization leading to nocturnal CI for several PECAN cases occurring in different synoptic environments. In the current study, we follow the approach discussed in section 3a of Trier et al. (2017), which uses Bellamy (1949) triangles to estimate area averages of horizontal divergence:
∇p⋅V=1ADADt,
valid at the centroids of triangles with area A, whose vertices are composed of radiosonde observations vertically interpolated to Δp = 5 hPa surfaces. The horizontal divergence profiles are then vertically integrated to obtain vertical profiles of the pressure vertical velocity ω ≡ Dp/Dt ≈ −ρgw using the kinematic method:
ω⁡(p2)=ω⁡(p1)−∫p1p2∇p⋅V dp,
where p1 is highest common pressure of the three radiosondes that compose the triangle and p2 is the pressure at which the pressure vertical velocity is sought in 5-hPa increments extending up to 100 hPa, with ω(p1) determined by the terrain-following lower-boundary condition described in Trier et al. (2017). During the vertical integration an adjustment is applied to the horizontal divergence to eliminate net column divergence, which ensures that ω = 0 at the top (100 hPa) of the column (O’Brien 1970). The magnitude of adjustment to the divergence at each of the 5-hPa levels decreases linearly to zero at the bottom of the column as described in Trier et al. (2017).

In section 4 we employ the above methodology to analyze both the large-scale kinematic vertical motion using the NWS radiosondes at the nominal 0000 UTC 24 June 2015 analysis time and mesoscale vertical motions during the late-evening interaction of the LLJ and the frontal zone using PECAN radiosondes (Fig. 3). For both the synoptic and PECAN vertical motion analyses, tests revealed the triangles to be sufficiently large that diagnosed ω values beneath 500 hPa were not significantly changed when calculations using (1) accounted for balloon drift. Because our analysis will focus on lower- to midtropospheric vertical motions, we present results with no corrections for balloon drift. Beneath 500 hPa, the horizontal divergence adjustments are small and differences between ω calculated from (2) with and without these adjustments are also small, having amplitudes ranging from ~0.1 to 1.0 μb s−1.

One objective of the current study is quantifying the degree to which the mesoscale vertical motions associated with the interaction of the nocturnal LLJ and the frontal zone can be explained by isentropic upglide. Two potentially important factors that are often overlooked in previous two-dimensional estimates of isentropic upglide are the 1) scale dependence of vertical motions and 2) vertical wind shear associated with veering wind profiles found in warm advection regions within frontal zones. The second aspect may lead to a significant angle between the flow direction and the horizontal temperature gradient, which can both vary with height. This effect is typically not accounted for in estimates of the full isentropic upglide:
ωI=−V⋅∇pθ∂θ/∂p.
Both scale dependence of vertical motion and possible three-dimensional effects discussed above can be accounted for if we compare kinematic and isentropic vertical motion estimates made over identical triangles, which include both MG3–MP4–MP1 and MG3–MG1–MP1 (Fig. 3).
Our estimates of isentropic vertical motion follow the approach detailed in Trier and Davis (2007, p. 2058) applied in the vicinity of mesoscale convective vortices (MCVs). By assuming the front is stationary, the steady component of the isentropic vertical motion (Trier and Davis 2007) may be estimated at triangle centroids by
ωI=au¯+bυ¯c⁡(∂θ/∂p¯),
where the coefficients a, b, and c, defined as
a=y1⁡(θ2−θ3)+y2⁡(θ3−θ1)+y3⁡(θ1−θ2)b=θ1⁡(x2−x3)+θ2⁡(x3−x1)+θ3⁡(x1−x2)c=x1⁡(y2−y3)+x2⁡(y3−y1)+x3⁡(y1−y2),
are components of a vector normal to a plane defined by the triangle vertices (indicated by subscripts 1, 2, and 3) and a constant pressure surface. In (4), u¯, υ¯, and ∂θ/∂p¯ are the average values at the triangle vertices of zonal and meridional winds, and static stability, respectively.

In steady isentropic vertical motion in (3), local temperature changes owing to vertical motions are exactly counteracted by those associated with horizontal temperature advections such that ∂θ/∂t = 0. The steady assumption used to derive the expression in (3) for isentropic vertical motion is consistent with the near stationarity of the front. However, contrary to this assumption, there can be still be large local potential temperature changes owing to strong dynamical and radiative effects that can occur in frontal environments near nocturnal LLJs. Such effects may dominate differences between isentropic and kinematic vertical motions in pre-CI environments lacking strong latent heat release.

c. ARW simulation

The PECAN sounding network for IOP 14 (Fig. 3) is well situated to sample near upstream conditions for late-evening CI in eastern Nebraska (Figs. 2b,c). However, the most widespread initiation of new convection over western and central Iowa is located 150 km or more northeast of the closest soundings, which are MG3 and MG1 (Figs. 2b,c). This motivates us to use output from a numerical simulation that covers a greater area in order to supplement our analysis of the available data. If the simulation replicates relevant aspects of the nocturnal CI and ensuing overnight convection, its enhanced spatial and temporal resolution may be exploited to gain additional insight into physical processes governing the CI and subsequent growth of convection.

Our simulation uses version 3.7.1 of the Advanced Research core of the Weather Research and Forecasting Model (ARW; Skamarock and Klemp 2008, Powers et al. 2017). This 24-h simulation is initialized at 1800 UTC 23 June 2015 with initial conditions and 3-h lateral boundary conditions from the North American Regional Reanalysis (Mesinger et al. 2006).

The simulation uses two domains (Fig. 4) with two-way interactive feedbacks, and has 39 vertical levels with greatest vertical resolution near the ground and vertical grid spacings of 200–250 m near the LLJ and 400–500 m in the middle troposphere (3–5 km MSL). The outer domain has 340 × 340 horizontal grid points with 10-km spacing, and the nest contains 701 × 601 horizontal grid points with 2-km spacing. An adaptive time step used in the simulation is adjusted based on the Courant number in the domains (Hutchinson 2009), and varies between 30 and 120 s, and 6 and 24 s in the outer and inner domains, respectively.

Fig. 4.
Fig. 4.

Horizontal domains for the WRF-ARW simulation. The outer domain D01 has 10-km horizontal grid spacing and the inner domain D02 is a two-way interactive nest with 2-km horizontal grid spacing. Surface elevations are indicated by the gray shadings.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The fine resolution of the inner domain obviates the need for cumulus parameterization. The Grell and Freitas (2014) cumulus scheme is used in the outer domain. Both domains use the Rapid Radiative Transfer Model for Global Climate Models (RRTMG; Iacono et al. 2008) longwave and shortwave radiation schemes, the Mellor–Yamada–Janjić PBL scheme (Janjić 1994, 2001), the Thompson et al. (2008) bulk microphysics scheme, and the Noah land surface model (Ek et al. 2003).

4. Observations of the environment of nocturnal convection initiation

a. Early evening background environment

The late evening deep CI over Iowa (Fig. 2b) is preceded by altocumulus (AC) cloud bands that began 4–5 h earlier near the Nebraska–Iowa border (Fig. 5a). The AC are of interest because such clouds sometimes precede elevated deep convection (e.g., Corfidi et al. 2008). Extending westward from the AC cloud bands is a denser midtropospheric overcast (Fig. 5), from which the smaller-scale east-central Nebraska CI event (Fig. 2b) later develops.

Fig. 5.
Fig. 5.

0110 UTC 24 Jun 2015 GOES-13 (a) 1-km visible satellite imagery, and (b) 4-km infrared imagery illustrating cloud features described in the text. The annotation KOAX in (a) indicates the location of the 2311 UTC 23 Jun Omaha, NE, sounding described in the text and plotted in Fig. 7.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The precursor AC bands are oriented from ~300° (Fig. 5a), which is approximately parallel to the 0000 UTC large-scale 700-hPa frontal zone (Fig. 6a) in which they form. Concurrent infrared satellite imagery during the early evening reveals typical cloud-top temperatures of −5° to −10°C (Fig. 5b), which according to the 2311 UTC 23 June Omaha, Nebraska (KOAX), sounding (location in Fig. 5a) indicates cloud tops near 500 hPa. Maximum relative humidities of 85%–90% occur near 715 hPa in this sounding (Fig. 7a, red curve). If cloud bases occur at that level, the cloud layer would be ~3 km deep. The vertical shear through this layer in the KOAX sounding is 4.5 m s−1 km−1 from 315°, which is broadly similar to the ~300° band orientation.

Fig. 6.
Fig. 6.

700-hPa subjective analysis at 0000 UTC 24 Jun 2015. (a) Geopotential height (solid blue contours, 30-m intervals), isotherms (dashed red contours, 2°C intervals), and horizontal winds plotted using the standard meteorological convention with half barb = 5 kt (2.54 m s−1) and full barb = 10 kt (5.17 m s−1). Station model contains temperatures (in °C) and geopotential heights (in meters). The rectangular region indicates the region of subsequent convection initiation in Figs. 2b and 2c. (b) Average relative humidity in the 675–725-hPa layer at sounding locations (solid blue contours with 50% and 75% threshold values), and 700-hPa kinematically derived (section 3) pressure vertical velocity (red contours with 2 μb s−1 contour intervals, negative values dashed) using values at radiosonde triangle centroids (black dots).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

Fig. 7.
Fig. 7.

Observed (red) and simulated (blue) vertical profiles of (a) relative humidity, (b) zonal, and (c) meridional winds at 2311 UTC 23 Jun 2015 from the location of the Omaha, Nebraska (KOAX, Figs. 2, 3, 5a, and 13) National Weather Service radiosonde site.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

Analysis of the NWS radiosonde data (launched from 2301 to 2317 UTC 23 June), combined with a single nearly contemporaneous 2331 UTC 23 June PECAN sounding from FP4 (Fig. 3), indicates that these early evening cloud bands form within a region of enhanced midtropospheric moisture associated with large-scale ascent (Fig. 6b). The 700-hPa ω (Fig. 6b) is derived kinematically (section 3b) using 28 independent (i.e., nonoverlapping) radiosonde triangles defined by the locations of the plotted wind observations in Fig. 6b 2 with ω valid at the triangle centroids (black dots). The 700-hPa ascent maximum in southeast Nebraska (Fig. 6b) is located along the south side of the baroclinic zone situated within the confluent jet entrance (Fig. 6a). This is also a location of significant warm advection (Fig. 6a). Together, these factors suggest that the diagnosed ascent maximum located on the southwest edge (i.e., slightly upstream) of where the AC bands and subsequent deep CI occur may be influenced by quasigeostrophic forcing, which we examine using model output in section 5c.

b. Nocturnal CI environment

The analysis of the previous subsection illustrated favorable midtropospheric forcing and large-scale ascent during the beginning of the evening, prior to the late-evening/overnight intensification of the LLJ. However, deep convection did not initiate in eastern Nebraska and western and central Iowa (Fig. 2a) until ~0500 UTC (midnight local time). The several hour lag between the onset of late afternoon/early evening altocumulus bands and subsequent deep CI (Fig. 8) motivates examination of the role of the interaction of the evolving LLJ with the frontal zone in providing additional forcing upstream of the region that later experiences deep CI.

Fig. 8.
Fig. 8.

Brightness temperature from GOES-14 4-km thermal IR satellite at (a) 0339, (b) 0439, (c) 0539, and (d) 0639 UTC 24 Jun 2015. Annotations in (c) refer to convection initiation events described in the text.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

1) Mesoscale frontal structure and vertical motions

Vertical cross sections (Fig. 9) along transect AA′ (see Fig. 3 for location) depict the mid- to late evening evolution of the LLJ and frontal structure in a plane normal to the surface front. CI begins close to MG3 (Fig. 2a) located near the right edge of the vertical cross section near the end of this period. During these 3 h from 0300 to 0600 UTC, the height of the frontal inversion decreases within the vertical cross section (cf. Figs. 9a,b). This evolution is consistent with strong warm advection near the LLJ occurring above the frontal surface. The LLJ becoming oriented along isentropes that slope upward toward the northeast in the vertical cross section is consistent with the significant mesoscale isentropic ascent illustrated in the conceptual model (Fig. 1) presented in the introduction.

Fig. 9.
Fig. 9.

Vertical cross section constructed using PECAN radiosonde data along line AA′ in Fig. 3 at (a) 0300 and (b) 0600 UTC 24 Jun 2015. The leading edge of the warm front is located at x = 0 km, with negative (positive) distances located equatorward (poleward) of where the warm front intersects the surface. Solid black contours (2-K intervals) are of virtual potential temperature. Water vapor mixing ratio (g kg−1) is shaded (see side legend), winds are plotted using the standard meteorological convention (half barb = 5 kt, full barb = 10 kt), and the warm front is plotted as in Fig. 1.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The two PECAN radiosonde triangles in Fig. 3 are used to produce vertical motion estimates during LLJ intensification (~0430 UTC) for the mesoscale region extending from the leading edge of the surface front to the northeast (right) edge of the vertical cross section (Fig. 9). The estimated kinematic and isentropic vertical motion profiles (Fig. 10) have upward motion maxima (ω minima) of similar strength located in the lower troposphere at ~850 hPa and ~880–850 hPa, respectively. These locations are slightly above the top of the frontal surface from x = 0 to x = 200 km in the vertical cross section (cf. Fig. 9). The greater smoothness of the kinematic profiles results from ω being diagnosed from a vertical integration in (2). In contrast, the isentropic ω is calculated on individual Δp = 5-hPa pressure surfaces and is sensitive to vertical variations of the mesoscale averaged static stability, which appears in the denominator of (4).

Fig. 10.
Fig. 10.

Mesoscale pressure vertical velocity estimates diagnosed from the radiosonde triangles depicted in Fig. 3.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

2) Thermodynamic evolution

Pronounced warming and drying occurs in the 850–750-hPa layer during the late evening in the CI proximity soundings MG3 (Fig. 11a) and MG1 (Fig. 11b) despite concurrent upward motion (Fig. 10) over the upstream mesoscale region defined by the MG3–MP4–MP1 and MG3–MG1–MP1 triangles (Fig. 3). The drying contributed to significant 0300–0600 UTC decreases in CAPE for air parcels within this layer (Figs. 11c,d).

Fig. 11.
Fig. 11.

Evolution of temperature, dewpoint, and horizontal winds on 24 Jun 2015 from the PECAN mobile profiling sites (a) MG3 and (b) MG1, and evolutions of convective available potential energy (CAPE) and convective inhibition (CIN) at (c) MG3 and (d) MG1 (locations shown in Figs. 2 and 3). In (c),(d), the CAPE and CIN values are for 500-m-deep averaged air parcels, which are centered at the origination altitudes (km AGL) on the y axis. The portions of the CIN profiles to the left of the solid vertical CIN = 5 J kg−1 line in (c),(d) indicate atmospheric layers with small CIN.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The 0300–0600 UTC water vapor mixing ratio decreases in the 850–750-hPa layer at MG3 (Fig. 11a) and MG1 (Fig. 11b) are consistent with northeastward advection of warm, dry air (Fig. 12a), near the top of the upward sloping LLJ (Fig. 12b). The warm, dry air arriving from upstream had lower θe (~342–345 K) than that observed at 0300 UTC at MG1 (Fig. 12b), which explains the 850–750-hPa CAPE decreases (Figs. 11c,d). This contrasts with the situation in Trier and Parsons (1993, their Fig. 11b), where moistening occurred in a similarly deep layer near the LLJ maximum above an upward sloping frontal surface, and contributed to CIN reductions and large CAPE increases.

Fig. 12.
Fig. 12.

(a) 800-hPa winds and analysis of potential temperature (red contours, 2-K intervals) and water vapor mixing ratio (blue contours, 1 g kg−1 intervals) from PECAN radiosondes, (b) vertical cross section of equivalent potential temperature (color shadings) and horizontal winds in the plane of the vertical cross section (red contours, 2.5 m s−1 intervals, dashed values negative) along transect AA′ of (a) at 0300 UTC 24 Jun 2015. The annotations MG3 and MG1 in (a) denote the locations of radiosonde data presented in Figs. 11a and 11b, respectively. The locations of the PECAN radiosonde sites in (b) are displayed in Fig. 3.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

In contrast to the 850–750-hPa layer, a shallower layer from 900 to 850 hPa (~0.5 to 1.0 km AGL) experiences significant CAPE increases between 0300 and 0600 UTC (Figs. 11c,d). At 0600 UTC this lowest enhanced CAPE layer in the MG3 and MG1 vertical profiles (Figs. 11c,d) corresponds reasonably well to the θe maxima responsible for elevated layers of potential instability found by Hitchcock et al. (2019) in 98 of 295 (~1/3) PECAN preconvective soundings. However, this layer is unlikely to be the first to participate in the CI over eastern Nebraska (Figs. 2b,c) because of its significant CIN of > 100 J kg−1 (Figs. 11c,d) near the time of CI (0530–0600 UTC).

The layers most supportive of CI in MG3 (Fig. 11a) and MG1 (Fig. 11b) are highly elevated, beginning near 700 hPa in both soundings and extending to ~650 hPa. These layers are nearly saturated by 0300 UTC 24 June (Figs. 11a,b), which is consistent with the sounding locations being near the southern edge of the earlier midtropospheric cloudiness (Fig. 5b) that was associated with large-scale ascent (Fig. 6b). These layers begin roughly 1.5 km above the wind speed maximum of the nocturnal LLJ and contain approximate westerly flow (Figs. 11a,b).

Though the CIN becomes negligibly small throughout the 2.5–3.0-km AGL layer in both soundings by 0300 UTC (Figs. 11c,d), the CI near MG3 (Fig. 2b) does not begin until about 2.5-h later. One possible reason for this is the strong inversion beginning at ~650 hPa with very dry air above it (Fig. 11a, blue curves), which could possibly deplete updraft buoyancy through effects of entrainment. By 0600 UTC, when CI was underway near MG3 (Fig. 2b), the dry inversion layer had been removed (Fig. 11a, red curves). By then, the most unstable layer with ~2000 J kg−1 of CAPE and negligible CIN is located from 2.75 to 3.25 km AGL, which is even higher than at 0300 UTC (Fig. 11c). Similar changes occur at MG1 (Fig. 11d), though the lifting of the dry stable layer, located above the elevated unstable layer, is less dramatic (Fig. 11b) than at MG3 (Fig. 11a).

The elevated westerlies with favorable thermodynamic conditions appear most strongly linked to the midtropospheric synoptic pattern (Fig. 6a). Nevertheless, it is noteworthy that deep CI is delayed until the intensification phase of the nocturnal LLJ. This suggests that while perhaps not directly responsible for the inflow to the elevated CI, the nocturnal LLJ could still influence CI through its effect on enhancements to the mesoscale vertical motion (Fig. 10). This possibility is explored in the next section by analyzing output from the ARW model simulation.

5. Convection-allowing ARW simulation

a. Overview of simulated CI and comparison with observations

Similar to the observations (Fig. 2a), a mature MCS is present at 0400 UTC 24 June along the western edge of the simulated surface frontal zone near the Colorado–Nebraska–Kansas border (Fig. 13a). By 0600 UTC, a northwest (NW)–southeast (SE)-oriented area of convection had initiated several hundred kilometers north of the surface front (Fig. 13b), and it later became the dominant MCS (Fig. 13d), also similar to observations (Figs. 2b–d). The most striking difference between the observations and the simulation is the absence, in the simulation, of the MCS that was observed overnight near the elevated terrain of the Black Hills (Figs. 2c,d). However, we are most interested in the CI leading to the formation of the easternmost nocturnal MCS. The similar horizontal scale, approximate location and timing of the simulated CI to that observed suggests it is unlikely affected by the model’s inability to simulate the MCS located ~1000 km upstream.

Fig. 13.
Fig. 13.

Simulated maximum column reflectivity, surface potential temperature (2-K contour intervals), and surface horizontal winds (plotting convention as in Figs. 2 and 6, except that circles are replaced with wind symbols having no barbs where speeds are <2.5 kt) in D02 at (a) 0400, (b) 0600, (c) 0700, and (d) 0900 UTC 24 Jun 2015. The rectangular region in (b) indicates the location of the area-averaged time-pressure sections of Fig. 15. Annotations indicate the locations of radiosonde data discussed in the text.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The simulated NW–SE-oriented convection over Iowa (Fig. 13b) is analogous to that which occurs in the observations (Fig. 2b), though it comprises only a single band (instead of the two observed), and has a southwestward displacement from observations of ~50–100 km. The smaller area of observed CI near MG3 (Fig. 2b) lacks a clear analog in the model (Fig. 13b).

Differences in the structure and intensity of the upstream nocturnal LLJ, and corresponding differences in relative humidity are possible contributors to CI differences between the model and observations. At MG1, which is approximately 50 (125) km upstream of the simulated (observed) CI, the simulated LLJ is 3–5 m s−1 weaker than that observed during the period of CI (Fig. 14a). Near the time of CI, both the model and observations have multiple peaks in relative humidity (Fig. 14b) and contain relative minima near the location of the jet maximum (cf. Fig. 14a). However, the dry layer in the model is shallower than in observations, and unlike in the observations, the highest relative humidities are found beneath the LLJ wind speed maximum in the model. The greater strength of the observed jet than in the ARW simulation is consistent with Smith et al. (2019) who, for a wider range of conditions throughout PECAN, found similarly weaker amplitudes of LLJs simulated with ARW.

Fig. 14.
Fig. 14.

Observed (red) and simulated (blue) (a) horizontal winds from 220° azimuth (approximately parallel to the southwesterly nocturnal LLJ) and (b) relative humidity from the PECAN radiosonde MG1 location (see Fig. 3) at 0600 UTC 24 Jun 2015.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The frequency and regularity of model output allows examination of the evolution of environmental conditions over the region of simulated deep CI (rectangle in Fig. 13b). Though the nearest radiosonde observations during the intensification phase of the nocturnal LLJ are from MG1, the 0000 UTC NWS Omaha sounding (KOAX) documents the environment supporting early evening altocumulus and is adjacent to the subsequent simulated deep CI region (Fig. 13b). Here, the early evening elevated layer of large relative humidity (Fig. 7a, red curve) was well simulated (Fig. 7a, blue curve) and is consistent with the observed early evening AC (Fig. 5) that presaged the nocturnal CI. Neither the observed nor simulated vertical profiles of horizontal winds (Figs. 7b,c) contain a significant LLJ at this earlier time.

Persistent weak area-averaged upward motion is associated with warm advection within the 750–600-hPa layer during the early evening (Fig. 15a) over the region of subsequent simulated deep CI (Fig. 13b). During this early evening period (~2300–0200 UTC) there is modest simulated CAPE of 500–1000 J kg−1 and a temporary reduction in CIN (Fig. 15b) for air parcels within this highly elevated layer. More dramatic CAPE increases and CIN decreases occur in the 775–675-hPa layer prior to and during the onset of CI (Fig. 15b), which follows the intensification of warm advection within a shallower layer between 800 and 750 hPa (Fig. 15a). This warm advection, with enhancement of area-averaged upward motion above it, coincides with upstream intensification of the LLJ. The CI is within the LLJ terminus region, which does not contain strong low-level southerlies or southwesterlies prior to CI (Fig. 15).

Fig. 15.
Fig. 15.

Evolution of simulated horizontal winds (plotting convention as in Figs. 2, 6, and 13) and (a) vertical velocity (color shading), horizontal potential temperature advection (green contours, 4 × 10−5 K s−1 intervals, negative values dashed), and (b) convective available potential energy (color shading) and convective inhibition (10, 20, 40, and 80 J kg−1 red contours), each averaged over the rectangular inset of Fig. 13b.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The only layer susceptible to imminent deep CI according to the upstream soundings MG3 (Figs. 11a,c) and MG1 (Figs. 11b,d) begins ~1.5 km above the speed maximum of the nocturnal LLJ. The area-averaged time–height section from the rectangular region experiencing CI in the simulation (Fig. 13b) suggests a similar situation with the intersection of small CIN and moderate-to-large CAPE at the ~0540 UTC onset of simulated CI also occurring within the westerlies above 750 hPa (Fig. 15b).

Though details of the observed and simulated CI differ, both exhibit significant common features. These include highly elevated (Z ≥ 2 km AGL) air parcels within westerly flow that are susceptible to deep CI, but with CI delayed until the intensification phase of the nocturnal LLJ. In the next subsection we use model trajectories to more clearly establish the likely sources of the inflow to deep CI and the thermodynamic evolution occurring along the inflow.

b. Trajectory analysis

Nine-hour trajectories were produced using 3-min model output and are calculated backward from 6-km MSL updraft cores during both the initiation (Fig. 16a) and later maturing stage (Fig. 16b) of the simulated NW–SE-oriented mesoscale deep convective band (Fig. 13).

Fig. 16.
Fig. 16.

(a) 0600 UTC 24 Jun 2015 6-km MSL reflectivity, and 9-h trajectories calculated backward from 6-km MSL convective updraft cores at 0600 UTC 24 Jun within D02 of the WRF-ARW simulation. (b) As in (a), but for 0830 UTC 24 Jun 6-km MSL reflectivity, and 9-h trajectories calculated backward from 6-km MSL convective updraft cores at 0830 UTC 24 Jun. The black contours in (a) are potential temperature contours representing the south (leading) edge of surface warm front at 2200 UTC 23 Jun 2015, 1 h prior to the termination (i.e., southern extent) of the backward trajectories. The annotated locations are locations of radiosonde observations shown in Figs. 7, 9, 11, and 12. The large arrows indicate the position from which the trajectory path is calculated backward and the smaller arrows indicate hourly positions of the trajectories.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

1) Initiation phase

The initiation trajectories each originate within the daytime PBL in locations close to or slightly south of the midafternoon surface frontal zone in Kansas. Their motion (Fig. 16a) is northward during the late afternoon and early evening, but becomes eastward during the final 3 h before entering developing updrafts.

The western (red) trajectories that comprise the northwestern half of the initiating band (Fig. 16a) are lifted sharply and undergo ~1.5–2-km vertical displacements at the surface front prior to 0000 UTC (Fig. 17a). After the abrupt lifting, these trajectories remain significantly subsaturated (Fig. 17c) and have little additional upward displacements until their final eastward legs (Fig. 16a), which begin after 0215 UTC and are characterized by 3-h rises of ~0.5-km before entering convective updrafts (Fig. 17a). During the gradual ascent on their eastward leg the average relative humidity increases from 75% to approximately 100% (Fig. 17c) and the CIN becomes negligible (Fig. 17e). The high relative humidities with negligible CIN in a highly elevated layer with westerly flow feeding the CI is consistent with the upstream PECAN radiosondes (Fig. 11).

Fig. 17.
Fig. 17.

Diagnostics along the (left) back trajectories emanating from the simulated convection initiation in Fig. 16a, and the (right) simulated back trajectories emanating from the simulated mature convective band in Fig. 16b. Nine-hour time series of trajectory height from (a) 2100 UTC 23 Jun–0600 UTC 24 Jun, and (b) 2330 UTC 23 Jun–0830 UTC 24 Jun. Six-hour (c) 0000–0600 UTC 24 Jun and (d) 0230–0830 UTC 24 Jun time series of averaged trajectory diagnostics of pressure (solid) and relative humidity (dotted). Six-hour (e) 0000–0600 UTC 24 Jun and (f) 0230–0830 UTC 24 Jun time series of averaged trajectory diagnostics of CAPE (solid) and CIN (dotted). Red and blue colors represent diagnostics along the west and east located trajectories, respectively, in (left) Fig. 16a and (right) Fig. 16b. The dashed vertical lines in (a),(b) indicate the times at which the trajectory diagnostics plotted below begin. The shaded time intervals on the left (right) correspond to those of the vertical displacement plots for example trajectories in Figs. 21a–c (Figs. 21d–f).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

A regional maximum in late afternoon surface water vapor mixing ratio, q, occurs along and immediately north of the surface front (Fig. 18a). The western trajectories that originate south of MP1 (Fig. 16a) are significantly drier (q ≈ 13–14 g kg−1) than the eastern trajectories (q ≈ 16–18 g kg−1), owing to the component of the horizontal moisture gradient that is oriented along the front (Fig. 18a). The eastern (blue) trajectories enter convective updrafts along the southeastern part of the CI band after 2–3 h eastward moving legs that are similar to the western trajectories (Fig. 16a). However, because of larger relative humidities at their origin farther east, the air along eastern trajectories requires smaller vertical displacements to produce CI than the air along western trajectories. These trajectories enter convective updrafts at lower altitudes (Fig. 17a) where average pressures are ~80 hPa higher (Fig. 17c).

Fig. 18.
Fig. 18.

Surface horizontal winds and objectively analyzed water vapor mixing ratio (green contours, 2 g kg−1 intervals) at 2200 UTC 23 Jun 2015 for (a) domain D02 of the simulation and (b) observations. The wind plotting convention is as in Fig. 2. The red line with semicircle symbols indicates the concurrent approximate position of the surface warm front over Kansas.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

A corresponding analysis of observed 2200 UTC 23 June surface q (Fig. 18b) reveals a mesoscale maximum oriented along the surface front that is similar to that simulated (Fig. 18a). In the origination region of the western trajectories south of MP1, the simulated and observed values of q are similar (Figs. 18a,b). However, the west (W)–east (E) variations of q along the surface front are smaller in the observations, leading to ~1–2 g kg−1 moisture surpluses for the simulated eastern trajectories in their origination locations in eastern Kansas (Fig. 16a, blue curves). Since absolute moisture is well conserved along these trajectories (not shown), this initial moist bias along the eastern trajectories could contribute to the southward position errors (up to ~100 km) in the eastern portions of the simulated CI and mature convective bands, in a manner similar to that discussed by Peters et al. (2017) for their simulations of a PECAN nocturnal MCS which occurred over the same general region the following night.

Unlike the conceptual model of Fig. 1, the current trajectory analysis, which takes into account the three-dimensional flow, indicates that the ascending eastward-moving trajectories feeding the CI (particularly the western ones) are situated well above the LLJ wind speed maximum. However, the LLJ could still influence the CI since the CI occurs above the northeast edge of the horizontal convergence zone at the LLJ terminus (Fig. 19b), which contributes to the upward motion within the overlying westerlies (Fig. 19d). The spatial pattern of horizontal convergence evolves rapidly during the evening (cf. Figs. 19a,b) as the LLJ strengthens and moves northward. Similar to recent studies in PECAN (e.g., Shapiro et al. 2018; Gebauer et al. 2018; Smith et al. 2019), the most pronounced LLJ veering occurs along its northeastern flank, which may locally enhance convergence to the south, where significant horizontal convergence occurs across the entire width of the LLJ terminus (Fig. 19b).

Fig. 19.
Fig. 19.

Simulated horizontal winds (knots), isotachs (shaded in m s−1, 1 m s−1 = 1.94 kt), and horizontal convergence (blue contours of −2.5, −5, −7.5, and −10 × 10−5 s−1) over a portion of domain D02 for 0215 UTC 24 Jun 2015 (left) at (a) 825 and (c) 750 hPa, and for 0515 UTC 24 Jun 2015 (right) at (b) 825 and (d) 750 hPa. The wind plotting convention is as in Fig. 6. The red curves with arrows indicate paths of 3-h segments of example CI trajectories from 0215 to 0515 UTC 24 Jun 2015, whose vertical displacements during this time interval are displayed in Figs. 21a–c. The asterisks in (a),(d) signify the horizontal location of trajectories at 0215 and 0515 UTC, where trajectory pressures are similar to the pressure levels of the plots (see Figs. 21a–c).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

2) Maturing phase

Similar to the earlier CI trajectories (Fig. 16a), the air along later trajectories entering the maturing MCS (Fig. 16b) is lifted to approximate saturation prior to entering convective updrafts (Figs. 17b,d). The higher initial relative humidity for the eastern family of trajectories is another aspect that is similar to the earlier CI trajectories.

However, these later trajectories have lower average relative humidity (Fig. 17d) than the CI trajectories (Fig. 17c) at the beginning of their gradual ascent into convective updrafts. The lower simulated relative humidity is partly related to weaker ascent at the leading edge of the surface front during the evening, and is also consistent with the observed nocturnal drying that occurs near and above the LLJ wind speed maximum (Figs. 11a,b). Despite the initial dryness (Fig. 17d) and large CIN (Fig. 17f), the air along these later trajectories eventually becomes approximately saturated with negligible CIN because of significant gradual upward displacements (Fig. 17b), which are somewhat greater than those for the CI trajectories (Fig. 17a).

The MG3 (0430 UTC)–MP4 (0437 UTC)–MP1 (0400 UTC) PECAN radiosonde triangle surrounds the western (red) family of trajectories that move toward the maturing deep convection from ~0300 to 0630 UTC (Figs. 16b and 17b). Within this mesoscale triangle, kinematic and isentropic ω (section 3b) profiles calculated from both the PECAN radiosonde data and corresponding model output at the triangle vertices (Fig. 20) have a similar relationship to each other at 850 hPa, which is the approximate height of the observed LLJ wind speed maximum (Fig. 14a). Here, isentropic ω explains 50%–75% of the total (i.e., kinematic) ω, which itself has slightly larger magnitude in the observations (Fig. 20). At higher altitudes (lower pressures) above the LLJ speed maximum, isentropic ω accounts for significantly less of the total ω.

Fig. 20.
Fig. 20.

Mesoscale pressure vertical velocity diagnosed for the MG3 (0431 UTC)–MP4 (0437 UTC)–MP1 (0400 UTC) triangle region (solid brown triangle location in Fig. 3) from radiosonde observations (solid) and model output (dotted). The red profiles indicate the full ω values diagnosed kinematically and the blue profiles indicate the isentropic part of ω, as discussed in the text.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

Though evolving somewhat in its character, persistent mesoscale ascent along inflow trajectories clearly plays a critical role in both initiating and maintaining the simulated elevated deep convection. In the next subsection we analyze likely sources of the mesoscale ascent.

c. Analysis of simulated mesoscale ascent

As noted in the introduction, one mechanism often invoked to explain gradual vertical displacements in the vicinity of surface fronts is steady isentropic upglide or frontal overrunning by the LLJ (e.g., Weckwerth et al. 2019). The contribution to vertical displacements Δz from isentropic upglide along the trajectory is given by
Δz=−us∂z∂θ∂θ∂sΔt,
where us is the local horizontal wind speed along the trajectory, and −(∂z/∂θ)(∂θ/∂s) is the slope of the isentropes along the trajectory direction, s. For calculations using (6), the vertical displacement from upglide (Δz) is that which would occur under steady (∂θ/∂t = 0), isentropic (θ˙=0) conditions along trajectories during a time interval of Δt = 180 s, which is the model output frequency. The temporally integrated contribution from isentropic upglide (blue curves) is compared to the total vertical displacement (red curves) for examples of both CI (Figs. 21a–c) and mature convective band (Figs. 21d–f) inflow trajectories during the 3- and 3.5-h periods of persistent mesoscale ascent (shadings in Figs. 17a,b), respectively. The example trajectories (Fig. 21) were selected based on small magnitudes of θ˙<0.2 K h−1 along their paths, and were restricted to the western families of trajectories (red curves in Figs. 16a,b) whose initial PBL moisture values corresponded more closely to observations (cf. Fig. 18).
Fig. 21.
Fig. 21.

Total vertical displacements (red dotted curves) and those due to isentropic upglide (solid blue curves) diagnosed from temporal integrations of (6) in the text for segments of (a)–(c) example CI trajectories (Fig. 16a) during the shaded time intervals in Figs. 17a, 17c, and 17e and (d)–(f) example mature convective band trajectories (Fig. 16b) during the shaded time intervals in Figs. 17b, 17d, and 17f. Each of the six example trajectories are selected from the western families of trajectories (red curves in Figs. 16a,b).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

The simulated total vertical displacements in Fig. 21 have high frequency undulations that could be related to short-wavelength gravity waves (e.g., Wilson et al. 2018). However, the persistent mesoscale ascent along their paths is more important to net increases in relative humidity and reduction of CIN that lead to eventual CI (Figs. 17a,c,e). In both the CI and mature phases of the convective band, there are 5%–15% increases in relative humidity during the earliest ~2 h of mesoscale ascent along these inflow trajectories (Fig. 21).

Instantaneous vertical velocity is proportional to the local slopes of the integrated vertical displacement curves in Fig. 21. With this in mind, it is evident that the vertical displacements are well explained by overrunning during the first ~2 h of the mesoscale ascent. However, additional vertical displacements and relative humidity increases are necessary before deep convection ensues along these trajectories (Fig. 21), and these additional vertical displacements clearly exceed those which can be accounted for by overrunning. In particular, there are examples of both CI and mature convective band trajectories where overrunning accounts for ½ or less of the integrated 3–3.5-h vertical displacements (Figs. 21c,e,f).

The excess vertical displacement beyond that expected solely from steady, isentropic upglide (i.e., overrunning), at greater altitudes closer to where deep convection occurs, is an aspect that is illustrated in the schematic diagram of Fig. 1. However, the current trajectory analysis indicates that much of this final enhanced mesoscale ascent may occur outside of the plane of Fig. 1, which is oriented parallel to the surface temperature gradient and LLJ wind speed maximum.

The much smaller percentage of the total vertical displacements being accounted for by overrunning in the ~75 min along the trajectories prior to CI (Figs. 21b,c) is consistent with unsteady conditions with local cooling in the region containing the final eastward legs of these trajectories (Fig. 22). For instance, a vertical average of model layers 11 and 12 (~760–710 hPa) indicates an approximate local cooling rate of ∂θ/∂t ≈ −0.35 K h−1, with static stability of ∂θ/∂z ≈ 4 K km−1 near the ends of CI trajectories 2 and 3 (Fig. 22). This, in turn, is associated with an ascent contribution of ~2.5 cm s−1 diagnosed from the local change (second term) on the right side of the thermodynamic equation for vertical motion:
w=θ˙−⁡(∂θ/∂t)−us⁡(∂θ/∂s)⁡(∂θ/∂z),
and comprises the majority of the average total ascent rate along the trajectories of w ≈ 4 cm s−1 during 0400–0515 UTC (Figs. 21b,c). Both the initial CI (Fig. 13b) and the mature convective band (Fig. 13d) are oriented along this band of precursor local cooling (Fig. 22).
Fig. 22.
Fig. 22.

Simulated layer averages of static stability (gray shadings) and hourly local potential temperature change (blue contours, 0.25-K contour interval, negative values dashed, zero contour omitted) through model levels 11 and 12 for a portion of D02 at 0430 UTC 24 Jun 2015. The red curves with arrows indicate the 3-h paths of example western CI trajectories (eastern portions of red curves in Fig. 16a) from 0215 or 0515 UTC 24 Jun 2015, whose vertical displacements are displayed in Figs. 21a–c. Model levels 11 and 12 are located between ~760–710 hPa in the cooling region along the easternmost 1/3 of the plotted trajectories.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

Some of the simulated time-averaged mesoscale ascent (ω < 0) in the westerly flow (Fig. 23a) along the final leg of the CI trajectories (cf. Fig. 22) is explained by the quasigeostrophic component of ω (Fig. 23b). Here, ω is calculated using the Q-vector formulation of the omega equation (e.g., Holton 1992) with a terrain-following lower boundary condition. The location of this upward motion maximum on the south side of the potential temperature gradient is consistent with a thermally direct vertical circulation related to geostrophic deformation within the baroclinic zone located in the entrance region of the 700-hPa jet (Fig. 23b). This situation diagnosed from the simulations during the mid- to late evening prior to CI is consistent with the earlier large-scale forcing diagnosed from NWS radiosonde observations (Fig. 6).

Fig. 23.
Fig. 23.

(a) Simulated time-averaged D02 full pressure vertical velocity ω (color shading), horizontal winds, and potential temperature (dashed gray contours with 2-K intervals) at 700 hPa. (b) Simulated D02 quasigeostrophic ω (color shading), potential temperature (dashed gray contours with 2-K intervals), and geopotential height (bold gray contours) with 20-m contour intervals at 700 hPa. The single bold green contours indicate simulated maximum column reflectivity >35 dBZ at 0700 UTC 24 Jun, which is 2 h later than the end of the 0200–0500 UTC interval for the time-averaged fields.

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0218.1

As noted earlier, the time–height section in Fig. 15a indicates persistent simulated midtropospheric vertical motion, which suggests a potentially important role of this synoptic forcing on preconditioning the CI region for subsequent deep convection. However, CI does not begin until the intensification and veering of the nocturnal LLJ, which led to enhanced horizontal convergence near its northern terminus beneath the westerlies (Fig. 19d), which are ascending at mesoscale vertical velocities greater than that associated with steady isentropic upglide.

6. Summary

In this paper we have examined an elevated nocturnal MCS that occurred up to several hundred kilometers north of a surface warm front using proximity soundings from PECAN and output from a convection-allowing ARW simulation. In past studies both initiation and maintenance of this type of organized deep convection has frequently been interpreted using the paradigm of frontal overrunning by the southerly nocturnal LLJ (e.g., Trier and Parsons 1993; Moore et al. 2003; Peters and Schumacher 2014; Peters et al. 2017). This viewpoint typically invokes the concept of two-dimensional upglide along a steady pattern of isentropes (Fig. 1) as a lifting mechanism that allows upstream conditionally unstable air parcels to reach their LFC.

Our results from the current study have been interpreted within the context of this simple conceptual model and we now summarize both similarities and differences that have been found. Consistent with the conceptual model, the deep CI leading to the nocturnal MCS occurs near 0500 UTC (midnight local time) in phase with the intensification of the Great Plains nocturnal LLJ. However, the deep convection initiates from within a mesoscale region of altocumulus clouds that developed several hours earlier during the late afternoon and early evening. Enhanced midtropospheric moisture supporting the precursor cloudiness was attributed to large-scale ascent in the entrance region of a 700-hPa jet streak and was linked to quasigeostrophic forcing. Furthermore, both upstream PECAN radiosonde measurements and model back trajectories indicate that storms within the initiating deep convective band are fed by westerlies from a layer beginning about 1 to 1.5 km above the LLJ wind speed maximum.

Though it does not appear to have a primary role on inflow to deep convection during the CI stages, the LLJ may still play an important role on CI timing in the current case. Here, the westerly inflow to the CI lies above the northeastward limit (or terminus) of the LLJ. This implies that horizontal convergence in the layer below could be enhancing upward displacements in the overlying westerlies that feed the initiating deep convection.

The southerly-to-southwesterly LLJ contributes more directly to the inflow of the maturing deep convection overnight as the surface front becomes shallower and lifting at its leading edge is less intense than during the daytime. During this later stage, the front and LLJ have kinematic features that resemble the conceptual model in Fig. 1. But unlike in the Trier and Parsons (1993) study upon which this conceptual model is based, the LLJ imports warm and relatively dry air into the region north of the surface front. Both model trajectories and PECAN radiosondes indicate pronounced local drying overnight within the LLJ upstream of the elevated deep convection. However, the warm and dry air has sufficient moist static energy to sustain deep convection and CIN is eroded because of up to ~1-km-deep upward displacements during its 6-h movement above and north of the surface front. In the model, this results in trajectory parcels originating near the upstream LLJ speed maximum reaching their LFC, but not until they have translated several hundred kilometers northeast of the leading edge of the surface front.

Vertical motion calculations with PECAN radiosonde data and ARW model output (including trajectories) together indicate that significantly upstream of deep convection mesoscale ascent is well explained by three-dimensional isentropic upglide (section 3b). However, such isentropic upglide accounts for only roughly ½ of the total vertical displacements along inflow trajectories to deep convection, and does not explain critically important additional mesoscale ascent in the final 60–90 min prior to deep CI.

Thus, while the “frontal-overrunning” model (e.g., Fig. 1) is a useful pedagogical framework for elevated nocturnal CI north of surface fronts, other environmental factors need to be carefully considered to best anticipate the timing and precise location of CI for individual cases. In addition to the temperature and moisture characteristics of the upstream air mass south of the front (e.g., Moore et al. 2003; Peters et al. 2017), environmental characteristics such as large-scale midtropospheric forcing, enhancements to mesoscale convergence near the LLJ terminus, and three-dimensional flow effects may often be crucial. Our analysis highlights the critical need for enhancements to our current capability of tracking three-dimensional moisture streams in the vicinity of fronts and LLJs in real time for CI forecasting purposes.

The main area of CI investigated in the current case was slightly downstream of the PECAN network. However, new remote sensing instruments tested during the field campaign, including Raman lidars, microwave radiometers, atmospheric emitted radiance interferometers, and water vapor micropulse differential absorption lidars (e.g., Turner and Löhnert 2014; Blumberg et al. 2015; Weckwerth et al. 2016; Wu et al. 2016) could provide crucial moisture measurements at greater temporal frequency than currently available for monitoring of moisture near elevated CI.

Acknowledgments

The authors thank all participants in the Plains Elevated Convection at Night (PECAN) field project, from which much of the data used in this paper were obtained. David Ahijevych (NCAR) is acknowledged for his assistance in constructing the surface analyses in Fig. 2. The manuscript benefited from the comments of three anonymous reviwers and the editor Russ Schumacher (Colorado State University), and an earlier internal review by Morris Weisman (NCAR/Mesoscale and Microscale Meteorology Laboratory). Funding for this research was provided by the Changing Cold Regions Network (CCRN), the Canada Foundation for Innovation, and the Natural Sciences and Engineering Research Council of Canada Discovery Grant. The work was partially supported by National Science Foundation funds for the U.S. Weather Research Program (USWRP), which supports NCAR’s Short Term Explicit Prediction (STEP) program. The National Center for Atmospheric Research is sponsored by the National Science Foundation.

REFERENCES

  • Augustine, J. A., and F. Caracena, 1994: Lower tropospheric precursors to nocturnal MCS development over the central United States. Wea. Forecasting, 9, 116–135, https://doi.org/10.1175/1520-0434(1994)009<0116:LTPTNM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bellamy, J. C., 1949: Objective calculations of divergence, vertical velocity, and vorticity. Bull. Amer. Meteor. Soc., 30, 45–49, https://doi.org/10.1175/1520-0477-30.2.45.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Blumberg, W. G., D. D. Turner, U. Löhnert, and S. Castleberry, 2015: Ground-based temperature and humidity profiling using spectral infrared and microwave observations. Part II: Actual retrieval performance in clear-sky and cloudy conditions. J. Appl. Meteor. Climatol., 54, 2305–2319, https://doi.org/10.1175/JAMC-D-15-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Clark. R., 2016: FP3 Ellis, KS radiosonde data, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 27 January 2016, https://doi.org/10.5065/D6GM85DZ.

    • Crossref
    • Export Citation

  • Colman, B. R., 1990: Thunderstorms above frontal surfaces in environments without positive CAPE. Part II: Organization and instability mechanisms. Mon. Wea. Rev., 118, 1123–1144, https://doi.org/10.1175/1520-0493(1990)118<1123:TAFSIE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Corfidi, S. F., S. J. Corfidi, and D. M. Schultz, 2008: Elevated convection and castellanus: Ambiguities, significance, and questions. Wea. Forecasting, 23, 1280–1303, https://doi.org/10.1175/2008WAF2222118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Doswell, C. A., III, and E. N. Rasmussen, 1994: The effect of neglecting the virtual temperature correction on CAPE calculations. Wea. Forecasting, 9, 625–629, https://doi.org/10.1175/1520-0434(1994)009<0625:TEONTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land-surface model advances in the NCEP operational mesoscale Eta model. J. Geophys. Res., 108, 8851, https://doi.org/10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation

  • Gebauer, J. G., A. Shapiro, E. Fedorovich, and P. Klein, 2018: Convection initiation caused by heterogeneous low-level jets over the Great Plains. Mon. Wea. Rev., 146, 2615–2637, https://doi.org/10.1175/MWR-D-18-0002.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Geerts, B., and Coauthors, 2017: The 2015 Plains Elevated Convection at Night field project. Bull. Amer. Meteor. Soc., 98, 767–786, https://doi.org/10.1175/BAMS-D-15-00257.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Grell, G. A., and S. R. Freitas, 2014: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Haghi, K. R., and Coauthors, 2019: Bore-ing into nocturnal convection. Bull. Amer. Meteor. Soc., 100, 1103–1121, https://doi.org/10.1175/BAMS-D-17-0250.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hitchcock, S. M., R. S. Schumacher, G. R. Herman, M. C. Coniglio, M. D. Parker, and C. L. Ziegler, 2019: Evolution of pre- and postconvective environment profiles from mesoscale convective systems during PECAN. Mon. Wea. Rev., 147, 2329–2354, https://doi.org/10.1175/MWR-D-18-0231.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Holdridge, D., and D. Turner, 2015: FP6 Hesston, KS radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 24 June 2015, https://doi.org/10.5065/D6765CD0.

    • Crossref
    • Export Citation

  • Holton, J. R., 1992: An Introduction to Dynamic Meteorology. 3rd ed. Academic Press, 511 pp.

  • Hutchinson, T. A., 2009: An adaptive time-step for increased model efficiency. 19th Conf. on Numerical Weather Prediction, Omaha, NE, Amer. Meteor. Soc., 19A.1, https://ams.confex.com/ams/23WAF19NWP/techprogram/paper_153842.htm.

  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shepard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by longwave greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further development of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927–944, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Janjić, Z. I., 2001: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso Model. NCEP Office Note 437, 61 pp., http://www.emc.ncep.noaa.gov/officenotes/newernotes/on437.pdf.

  • Johnson, A., and X. Wang, 2019: Multicase assessment of the impacts of horizontal and vertical grid spacing, and turbulence closure model, on subkilometer-scale simulations of atmospheric bores during PECAN. Mon. Wea. Rev., 147, 1533–1555, https://doi.org/10.1175/MWR-D-18-0322.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kane, R. J., Jr., C. R. Chelius, and J. M. Fritsch, 1987: Precipitation characteristics of mesoscale convective weather systems. J. Climate Appl. Meteor., 26, 1345–1357, https://doi.org/10.1175/1520-0450(1987)026<1345:PCOMCW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Klein, P., D. Turner, E. Smith, and J. Gebauer, 2016: Mobile PISA 1 OU/NSSL CLAMPS radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 14 April 2016, https://doi.org/10.5065/D6416VDH.

    • Crossref
    • Export Citation

  • Knupp, K., 2015: Mobile PISA 2 UAH MIPS radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 1 June 2016, https://doi.org/10.5065/D6MC8X3V.

    • Crossref
    • Export Citation

  • Maddox, R. A., 1980: Mesoscale convective complexes. Bull. Amer. Meteor. Soc., 61, 1374–1387, https://doi.org/10.1175/1520-0477(1980)061<1374:MCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Maddox, R. A., 1983: Large scale meteorological conditions associated with midlatitude mesoscale convective complexes. Mon. Wea. Rev., 111, 1475–1493, https://doi.org/10.1175/1520-0493(1983)111<1475:LSMCAW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360, https://doi.org/10.1175/BAMS-87-3-343.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Moore, J. T., F. H. Glass, C. E. Graves, S. M. Rochette, and M. J. Singer, 2003: The environment of warm-season elevated thunderstorms associated with heavy rainfall over the central United States. Wea. Forecasting, 18, 861–878, https://doi.org/10.1175/1520-0434(2003)018<0861:TEOWET>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • NCDC, 2015: Storm Data. Vol. 57, No. 6, 864 pp.

  • O’Brien, J. J., 1970: Alternative solutions to the classical vertical velocity problem. J. Appl. Meteor., 9, 197–203, https://doi.org/10.1175/1520-0450(1970)009<0197:ASTTCV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Parker, M. D., 2008: Responses of simulated squall lines to low-level cooling. J. Atmos. Sci., 65, 1323–1341, https://doi.org/10.1175/2007JAS2507.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Peters, J. M., and R. S. Schumacher, 2014: Objective categorization of heavy-rain producing MCS synoptic types by rotated principle component analysis. Mon. Wea. Rev., 142, 1716–21 737, https://doi.org/10.1175/MWR-D-13-00295.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Peters, J. M., E. R. Nielsen, M. D. Parker, S. M. Hitchcock, and R. S. Schumacher, 2017: The impact of low-level moisture errors on model forecasts of an MCS observed during PECAN. Mon. Wea. Rev., 145, 3599–3624, https://doi.org/10.1175/MWR-D-16-0296.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Powers, J., and Coauthors, 2017: The Weather Research and Forecasting (WRF) Model: Overview, system efforts, and future directions. Bull. Amer. Meteor. Soc., 98, 1717–1737, https://doi.org/10.1175/BAMS-D-15-00308.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Reif, D. W., and H. B. Bluestein, 2017: A 20-year climatology of nocturnal convection initiation over the central and southern Great Plains during the warm season. Mon. Wea. Rev., 145, 1615–1639, https://doi.org/10.1175/MWR-D-16-0340.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schumacher, R. S., 2015: Sensitivity of precipitation accumulation in elevated convective systems to small changes in low-level moisture. J. Atmos. Sci., 72, 2507–2524, https://doi.org/10.1175/JAS-D-14-0389.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schumacher, R. S., and R. H. Johnson, 2005: Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Mon. Wea. Rev., 133, 961–976, https://doi.org/10.1175/MWR2899.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schumacher, R. S., and J. M. Peters, 2017: Near-surface thermodynamic sensitivities in simulated extreme-rain-producing mesoscale convective systems. Mon. Wea. Rev., 145, 2177–2200, https://doi.org/10.1175/MWR-D-16-0255.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Shapiro, A., E. Fedorovich, and J. G. Gebauer, 2018: Mesoscale ascent in nocturnal low-level jets. J. Atmos. Sci., 75, 1403–1427, https://doi.org/10.1175/JAS-D-17-0279.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys., 227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Smith, E. N., J. G. Gebauer, P. M. Klein, E. Fedorovich, and J. A. Gibbs, 2019: The Great Plains low-level jet during PECAN: Observed and simulated characteristics. Mon. Wea. Rev., 147, 1845–1869, https://doi.org/10.1175/MWR-D-18-0293.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stelten, S., and W. A. Gallus Jr., 2017: Pristine nocturnal convective initiation: A climatology and preliminary examination of predictability. Wea. Forecasting, 32, 1613–1635, https://doi.org/10.1175/WAF-D-16-0222.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 5095–5115, https://doi.org/10.1175/2008MWR2387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Trier, S. B., and D. B. Parsons, 1993: Evolution of environmental conditions preceding the development of a nocturnal mesoscale convective complex. Mon. Wea. Rev., 121, 1078–1098, https://doi.org/10.1175/1520-0493(1993)121<1078:EOECPT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Trier, S. B., and C. A. Davis, 2007: Mesoscale convective vortices observed during BAMEX. Part II: Influences on secondary deep convection. Mon. Wea. Rev., 135, 2051–2075, https://doi.org/10.1175/MWR3399.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Trier, S. B., J. W. Wilson, D. A. Ahijevych, and R. A. Sobash, 2017: Mesoscale vertical motions near nocturnal convection initiation in PECAN. Mon. Wea. Rev., 145, 2919–2941, https://doi.org/10.1175/MWR-D-17-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Turner, D. D., and U. Löhnert, 2014: Information content and uncertainties in thermodynamic profiles and liquid cloud properties retrieved from ground-based Atmospheric Emitted Radiance Interferometer (AERI). J. Appl. Meteor. Climatol., 53, 752–771, https://doi.org/10.1175/JAMC-D-13-0126.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • UCAR/NCAR–Earth Observing Laboratory, 2015:FP1 ARM Central Facility radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 13 January 2017, https://data.eol.ucar.edu/dataset/485.021.

  • UCAR/NCAR–Earth Observing Laboratory, 2016a: MP4 NCAR/EOL QC soundings, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 31 August 2015, https://doi.org/10.5065/D6707ZNV.

    • Crossref
    • Export Citation

  • UCAR/NCAR–Earth Observing Laboratory, 2016b: FP4 NCAR/EOL QC soundings, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 26 August 2015, https://doi.org/10.5065/D63776XH.

    • Crossref
    • Export Citation

  • UCAR/NCAR–Earth Observing Laboratory, 2016c: FP5 NCAR/EOL QC soundings, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 13 January 2017, https://doi.org/10.5065/D6ZG6QF7

    • Crossref
    • Export Citation

  • Vermeesch, K., 2015: FP2 Greensburg, KS radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 13 January 2017, https://doi.org/10.5065/D6FQ9TPH.

    • Crossref
    • Export Citation

  • Wagner, T., E. Olson, N. Smith, and W. Feltz, 2016: Mobile PISA 3 UW/SSEC SPARC radiosonde data, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 28 October 2015, https://doi.org/10.5065/D6VH5M7B.

    • Crossref
    • Export Citation

  • Weckwerth, T. M., K. Weber, D. D. Turner, and S. M. Spuler, 2016: Validation of a water vapor micropulse differential absorption lidar (DIAL). J. Atmos. Oceanic Technol., 33, 2353–2372, https://doi.org/10.1175/JTECH-D-16-0119.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Weckwerth, T. M., J. M. Hanesiak, J. W. Wilson, S. B. Trier, S. K. Degelia, W. A. Gallus Jr., R. D. Roberts, and X. Wang, 2019: Nocturnal convection initiation during PECAN 2015. Bull. Amer. Meteor. Soc., 100, 2223–2239, https://doi.org/10.1175/BAMS-D-18-0299.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., S. B. Trier, D. W. Reif, R. D. Roberts, and T. M. Weckwerth, 2018: Nocturnal elevated convection initiation of the PECAN 4 July hailstorm. Mon. Wea. Rev., 146, 243–262, https://doi.org/10.1175/MWR-D-17-0176.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wu, D., and Coauthors, 2016: Airborne compact rotational Raman lidar for temperature measurement. Opt. Express, 24, A1210–A1214, https://doi.org/10.1364/OE.24.0A1210.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ziegler, C., M. Coniglio, M. Parker, and R. Schumacher, 2016: CSU/NCSU/NSSL MGAUS radiosonde data, version 3.0. UCAR/NCAR–Earth Observing Laboratory, accessed 1 June 2016, https://doi.org/10.5065/D6W66HXN.

    • Crossref
    • Export Citation
1

The reader should note these smaller-scale lifting mechanisms can also be effective at triggering CI outside of frontal environments (e.g., Johnson and Wang 2019; Weckwerth et al. 2019).

2

The kinematic ω calculations also use NWS radiosonde data from Glasgow, MT (48.21°N, 106.63°W); Bismarck, ND (46.77°N, 100.76°W); and International Falls, MN (48.57°N, 93.40°W), each located beyond the northern boundary of Fig. 6b.

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Augustine, J. A., and F. Caracena, 1994: Lower tropospheric precursors to nocturnal MCS development over the central United States. Wea. Forecasting, 9, 116–135, https://doi.org/10.1175/1520-0434(1994)009<0116:LTPTNM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bellamy, J. C., 1949: Objective calculations of divergence, vertical velocity, and vorticity. Bull. Amer. Meteor. Soc., 30, 45–49, https://doi.org/10.1175/1520-0477-30.2.45.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Blumberg, W. G., D. D. Turner, U. Löhnert, and S. Castleberry, 2015: Ground-based temperature and humidity profiling using spectral infrared and microwave observations. Part II: Actual retrieval performance in clear-sky and cloudy conditions. J. Appl. Meteor. Climatol., 54, 2305–2319, https://doi.org/10.1175/JAMC-D-15-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Clark. R., 2016: FP3 Ellis, KS radiosonde data, version 2.0. UCAR/NCAR–Earth Observing Laboratory, accessed 27 January 2016, https://doi.org/10.5065/D6GM85DZ.

    • Crossref
    • Export Citation

  • Colman, B. R., 1990: Thunderstorms above frontal surfaces in environments without positive CAPE. Part II: Organization and instability mechanisms. Mon. Wea. Rev., 118, 1123–1144, https://doi.org/10.1175/1520-0493(1990)118<1123:TAFSIE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Corfidi, S. F., S. J. Corfidi, and D. M. Schultz, 2008: Elevated convection and castellanus: Ambiguities, significance, and questions. Wea. Forecasting, 23, 1280–1303, https://doi.org/10.1175/2008WAF2222118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Doswell, C. A., III, and E. N. Rasmussen, 1994: The effect of neglecting the virtual temperature correction on CAPE calculations. Wea. Forecasting, 9, 625–629, https://doi.org/10.1175/1520-0434(1994)009<0625:TEONTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land-surface model advances in the NCEP operational mesoscale Eta model. J. Geophys. Res., 108, 8851, https://doi.org/10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation

  • Gebauer, J. G., A. Shapiro, E. Fedorovich, and P. Klein, 2018: Convection initiation caused by heterogeneous low-level jets over the Great Plains. Mon. Wea. Rev., 146, 2615–2637, https://doi.org/10.1175/MWR-D-18-0002.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Geerts, B., and Coauthors, 2017: The 2015 Plains Elevated Convection at Night field project. Bull. Amer. Meteor. Soc., 98, 767–786, https://doi.org/10.1175/BAMS-D-15-00257.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Grell, G. A., and S. R. Freitas, 2014: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Haghi, K. R., and Coauthors, 2019: Bore-ing into nocturnal convection. Bull. Amer. Meteor. Soc., 100, 1103–1121, https://doi.org/10.1175/BAMS-D-17-0250.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hitchcock, S. M., R. S. Schumacher, G. R. Herman, M. C. Coniglio, M. D. Parker, and C. L. Ziegler, 2019: Evolution of pre- and postconvective environment profiles from mesoscale convective systems during PECAN. Mon. Wea. Rev., 147, 2329–2354, https://doi.org/10.1175/MWR-D-18-0231.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Holdridge, D., and D. Turner, 2015: FP6 Hesston, KS radiosonde data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 24 June 2015, https://doi.org/10.5065/D6765CD0.

    • Crossref