Plains Elevated Convection At Night (PECAN)

Description:

The Plains Elevated Convection At Night (PECAN) special collection contains articles related to the PECAN field campaign, conducted over the Great Plains during June-July 2015. This campaign assembled a rich array of observations from lower-tropospheric profiling systems, mobile radars and mesonets, and aircraft, in order to better understand nocturnal mesoscale convective systems (MCSs) and their relationship with the stable boundary layer, the low-level jet (LLJ), and atmospheric bores. More specifically, PECAN aimed to study (a) pristine nocturnal convection initiation and the initial upscale growth of deep convection; (b) the mechanisms in which the mesoscale environment modulates the initiation, structure, propagation, and evolution of bores, solitons, and other trapped wave disturbances, and the inherent role of these disturbances in the maintenance of nocturnal MCSs; (c) the structure and evolution of the nocturnal LLJ; (d) the dynamical and microphysical structure of nocturnal MCSs; and (e) the prediction of nocturnal CI, MCSs, and, more generally, the diurnal cycle of warm season precipitation. Papers in this collection cover such topics as: instruments used for the first time or in a novel way in PECAN; the microphysics and/or the dynamics of MCSs and associated severe weather aspects; the dynamics of MCS outflow boundaries, such as density currents, bores, and solitons; the initiation of nocturnal deep convection; dynamics of the Great Plains low-level jet; nocturnal boundary-processes in the presence of a LLJ; numerical simulations of any of the above-listed meteorological topics at a range of scales, with the purpose of improving understanding as well as predictability; novel data assimilation projects and observing system simulation experiments using PECAN data, especially its mesoscale network of lower-tropospheric profiling systems.

PECAN was funded primarily by NSF, with additional funding from NOAA, NASA, DOE, and the Canadian Natural Sciences and Engineering Research Council.

Collection organizers:
David Parsons, University of Oklahoma
Bart Geerts, University of Wyoming
Tammy M. Weckwerth, NCAR
Conrad L. Ziegler, NOAA National Severe Storms Lab
David D. Turner, NOAA National Severe Storms Lab

Plains Elevated Convection At Night (PECAN)

Dylan W. Reif
,
Howard B. Bluestein
, and
David B. Parsons

Abstract

This study creates a composite sounding for nocturnal convection initiation (CI) events under weakly forced conditions and utilizes an idealized numerical simulation to assess the impact of atmospheric bores on these environments. Thirteen soundings were used to create this composite sounding. Common conditions associated with these weakly forced environments include a nocturnal low-level jet and a Brunt–Väisälä frequency of 0.011 s−1 above 900 hPa. The median lift needed for parcels to realize any convective instability is 490 m, the median convective available potential energy of these convectively unstable parcels is 992 J kg−1, and the median initial pressure of these parcels is 800 hPa. An idealized numerical simulation was utilized to examine the potential influence of bores on CI in an environment based on composite sounding. The characteristics of the simulated bore were representative of observed bores. The vertical velocities associated with this simulated bore were between 1 and 2 m s−1, and the net upward displacement of parcels was between 400 and 650 m. The vertical displacement of air parcels has two notable phases: lift by the bore itself and smaller-scale lift that occurs 100–150 km ahead of the bore passage. The prebore lift is between 50 and 200 m and appears to be related to low-frequency waves ahead of the bores. The lift with these waves was maximized in the low to midtroposphere between 1 and 4 km AGL, and this lift may play a role in assisting CI in these otherwise weakly forced environments.

Restricted access
Anders A. Jensen
,
Gregory Thompson
,
Kyoko Ikeda
, and
Sarah A. Tessendorf

Abstract

Methods to improve the representation of hail in the Thompson–Eidhammer microphysics scheme are explored. A new two-moment and predicted density graupel category is implemented into the Thompson–Eidhammer scheme. Additionally, the one-moment graupel category’s intercept parameter is modified, based on hail observations, to shift the properties of the graupel category to become more hail-like since the category is designed to represent both graupel and hail. Finally, methods to diagnose maximum expected hail size at the surface and aloft are implemented. The original Thompson–Eidhammer version, the newly implemented two-moment and predicted density graupel version, and the modified (to be more hail-like) one-moment version are evaluated using a case that occurred during the Plains Elevated Convection at Night (PECAN) field campaign, during which hail-producing storms merged into a strong mesoscale convective system. The three versions of the scheme are evaluated for their ability to predict hail sizes compared to observed hail sizes from storm reports and estimated from radar, their ability to predict radar reflectivity signatures at various altitudes, and their ability to predict cold-pool features like temperature and wind speed. One key benefit of using the two-moment and predicted density graupel category is that the simulated reflectivity values in the upper levels of discrete storms are clearly improved. This improvement coincides with a significant reduction in the areal extent of graupel aloft, also seen when using the updated one-moment scheme. The two-moment and predicted density graupel scheme is also better able to predict a wide variety of hail sizes at the surface, including large (>2-in. diameter) hail that was observed during this case.

Free access
Samuel K. Degelia
and
Xuguang Wang

Abstract

The observation error covariance partially controls the weight assigned to an observation during data assimilation (DA). True observation error statistics are rarely known and likely vary depending on the meteorological state. However, operational DA systems often apply static methods that assign constant observation errors across a dataset. Previous studies show that these methods can degrade forecast quality when assimilating ground-based remote sensing datasets. To improve the impact of assimilating such observations, we propose two novel methods for estimating the observation error variance for high-frequency thermodynamic profilers. These methods include an adaptive observation error inflation technique and the Desroziers method that directly estimates the observation error variances using paired innovation and analysis residuals. Each method is compared for a nocturnal mesoscale convective system (MCS) observed during the Plains Elevated Convection at Night (PECAN) experiment. In general, we find that these novel methods better represent the large variability of observation error statistics for high-frequency profiles collected by Atmospheric Emitted Radiance Interferometers (AERIs). When assimilating AERIs by statically inflating retrieval error variances, the trailing stratiform region of the MCS is degraded compared to a baseline simulation with no AERI data assimilated. Assimilating the AERIs using the adaptive inflation or Desroziers method results in better maintenance of the trailing stratiform region and additional suppression of spurious convection. The forecast improvements from these novel methods are primarily linked to increased error variances for some moisture retrievals. These results indicate the importance of accurately estimating observation error statistics for convective-scale DA and suggest that accounting for flow dependence can improve the impacts from assimilating remote sensing datasets.

Free access
Hristo G. Chipilski
,
Xuguang Wang
,
David B. Parsons
,
Aaron Johnson
, and
Samuel K. Degelia

Abstract

There is a growing interest in the use of ground-based remote sensors for numerical weather prediction, which is sparked by their potential to address the currently existing observation gap within the planetary boundary layer. Nevertheless, open questions still exist regarding the relative importance of and synergy among various instruments. To shed light on these important questions, the present study examines the forecast benefits associated with several different ground-based profiling networks using 10 diverse cases from the Plains Elevated Convection at Night (PECAN) field campaign. Aggregated verification statistics reveal that a combination of in situ and remote sensing profilers leads to the largest increase in forecast skill, in terms of both the parent mesoscale convective system and the explicitly resolved bore. These statistics also indicate that it is often advantageous to collocate thermodynamic and kinematic remote sensors. By contrast, the impacts of networks consisting of single profilers appear to be flow-dependent, with thermodynamic (kinematic) remote sensors being most useful in cases with relatively low (high) convective predictability. Deficiencies in the data assimilation method as well as inherent complexities in the governing moisture dynamics are two factors that can further limit the forecast value extracted from such networks.

Full access
James N. Marquis
,
Adam C. Varble
,
Paul Robinson
,
T. Connor Nelson
, and
Katja Friedrich

Abstract

Data from scanning radars, radiosondes, and vertical profilers deployed during three field campaigns are analyzed to study interactions between cloud-scale updrafts associated with initiating deep moist convection and the surrounding environment. Three cases are analyzed in which the radar networks permitted dual-Doppler wind retrievals in clear air preceding and during the onset of surface precipitation. These observations capture the evolution of (i) the mesoscale and boundary layer flow, and (ii) low-level updrafts associated with deep moist convection initiation (CI) events yielding sustained or short-lived precipitating storms. The elimination of convective inhibition did not distinguish between sustained and unsustained CI events, though the vertical distribution of convective available potential energy may have played a role. The clearest signal differentiating the initiation of sustained versus unsustained precipitating deep convection was the depth of the low-level horizontal wind convergence associated with the mesoscale flow feature triggering CI, a sharp surface wind shift boundary, or orographic upslope flow. The depth of the boundary layer relative to the height of the LFC failed to be a consistent indicator of CI potential. Widths of the earliest detectable low-level updrafts associated with sustained precipitating deep convection were ~3–5 km, larger than updrafts associated with surrounding boundary layer turbulence (~1–3 km wide). It is hypothesized that updrafts of this larger size are important for initiating cells to survive the destructive effects of buoyancy dilution via entrainment.

Open access
Guo Lin
,
Coltin Grasmick
,
Bart Geerts
,
Zhien Wang
, and
Min Deng

Abstract

This observational study documents the consequences of a collision between two converging shallow atmospheric boundaries over the central Great Plains on the evening of 7 June 2015. This study uses data from a profiling airborne Raman lidar [the compact Raman lidar (CRL)] and other airborne and ground-based data collected during the Plains Elevated Convection at Night (PECAN) field campaign to investigate the collision between a weak cold front and the outflow from an MCS. The collision between these boundaries led to the lofting of high-CAPE, low-CIN air, resulting in deep convection, as well as an undular bore. Both boundaries behaved as density currents prior to collision. Because the MCS outflow boundary was denser and less deep than the cold-frontal air mass, the bore propagated over the latter. This bore was tracked by the CRL for about 3 h as it traveled north over the shallow cold-frontal surface and evolved into a soliton. This case study is unique by using the high temporal and spatial resolution of airborne Raman lidar measurements to describe the thermodynamic structure of interacting boundaries and a resulting bore.

Free access
Yun Lin
,
Jiwen Fan
,
Jong-Hoon Jeong
,
Yuwei Zhang
,
Cameron R. Homeyer
, and
Jingyu Wang

Abstract

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from these storms such as hail and tornadoes. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city, mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban–rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is more notable than either of the individual effects, emphasizing the importance of considering both effects in evaluating urbanization effects.

Full access
Brian J. Carroll
,
Belay B. Demoz
,
David D. Turner
, and
Ruben Delgado

Abstract

The 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging from 0 to 2 g kg−1 at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded an RMSE of 1.14 g kg−1 in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales on the order of ten to hundreds of kilometers.

Full access
Stacey M. Hitchcock
and
Russ S. Schumacher

Abstract

In a mesoscale convective system (MCS), convection that redevelops over (i.e., back-builds), and/or repeatedly passes over (i.e., trains) a region for an extended period of time can contribute to extreme rainfall and flash flooding. Past studies have indicated that both mesoscale ascent and lifting of the inflow layer by a cold pool or bore are important when this back-building/training convection is displaced from the leading line [sometimes called rearward off-boundary development (ROD)]. However, Plains Elevated Convection At Night (PECAN) field campaign observations suggest that the stability of the nocturnal boundary layer is highly variable and some MCSs with ROD have only a weak surface cold pool. Numerical simulations presented in this study suggest that in an environment with strong boundary layer stability, ROD can be supported by mechanisms other than those mentioned above. Simulations were initialized using a sounding from ahead of a PECAN MCS with a strong stable layer and ROD, and the three-dimensional simulation produced an MCS similar to that observed despite the homogeneous initial conditions. Some of the findings presented herein challenge existing understanding of nocturnal MCSs, and especially how downdrafts interact with a stable boundary layer. Notably, downdrafts can reach the surface, and different regions of the MCS may have different propagation mechanisms and different relevant inflow layers. Unlike previous studies of ROD, parcel lifting may be supported by an intrusion (an elevated layer of downdraft air) modified by the three-dimensional vertical wind shear.

Free access
Rachel L. Miller
,
Conrad L. Ziegler
, and
Michael I. Biggerstaff

Abstract

This case study analyzes a nocturnal mesoscale convective system (MCS) that was observed on 25–26 June 2015 in northeastern Kansas during the Plains Elevated Convection At Night (PECAN) project. Over the course of the observational period, a broken line of elevated nocturnal convective cells initiated around 0230 UTC on the cool side of a stationary front and subsequently merged to form a quasi-linear MCS that later developed strong, surface-based outflow and a trailing stratiform region. This study combines radar observations with mobile and fixed mesonet and sounding data taken during PECAN to analyze the kinematics and thermodynamics of the MCS from 0300 to 0630 UTC. This study is unique in that 38 consecutive multi-Doppler wind analyses are examined over the 3.5 h observation period, facilitating a long-duration analysis of the kinematic evolution of the nocturnal MCS. Radar analyses reveal that the initial convective cells and linear MCS are elevated and sustained by an elevated residual layer formed via weak ascent over the stationary front. During upscale growth, individual convective cells develop storm-scale cold pools due to pockets of descending rear-to-front flow that are measured by mobile mesonets. By 0500 UTC, kinematic analysis and mesonet observations show that the MCS has a surface-based cold pool and that convective line updrafts are ingesting parcels from below the stable layer. In this environment, the elevated system has become surface based since the cold pool lifting is sufficient for surface-based parcels to overcome the CIN associated with the frontal stable layer.

Free access