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Robert J. Trapp, David J. Stensrud, Michael C. Coniglio, Russ S. Schumacher, Michael E. Baldwin, Sean Waugh, and Don T. Conlee

Abstract

The Mesoscale Predictability Experiment (MPEX) was a field campaign conducted 15 May through 15 June 2013 within the Great Plains region of the United States. One of the research foci of MPEX regarded the upscaling effects of deep convective storms on their environment, and how these feed back to the convective-scale dynamics and predictability. Balloon-borne GPS radiosondes, or “upsondes,” were used to sample such environmental feedbacks. Two of the upsonde teams employed dual-frequency sounding systems that allowed for upsonde observations at intervals as fast as 15 min. Because these dual-frequency systems also had the capacity for full mobility during sonde reception, highly adaptive and rapid storm-relative sampling of the convectively modified environment was possible. This article documents the mobile sounding capabilities and unique sampling strategies employed during MPEX.

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Michael C. Coniglio, Kimberly L. Elmore, John S. Kain, Steven J. Weiss, Ming Xue, and Morris L. Weisman

Abstract

This study assesses forecasts of the preconvective and near-storm environments from the convection-allowing models run for the 2008 National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) spring experiment. Evaluating the performance of convection-allowing models (CAMs) is important for encouraging their appropriate use and development for both research and operations. Systematic errors in the CAM forecasts included a cold bias in mean 2-m and 850-hPa temperatures over most of the United States and smaller than observed vertical wind shear and 850-hPa moisture over the high plains. The placement of airmass boundaries was similar in forecasts from the CAMs and the operational North American Mesoscale (NAM) model that provided the initial and boundary conditions. This correspondence contributed to similar characteristics for spatial and temporal mean error patterns. However, substantial errors were found in the CAM forecasts away from airmass boundaries. The result is that the deterministic CAMs do not predict the environment as well as the NAM. It is suggested that parameterized processes used at convection-allowing grid lengths, particularly in the boundary layer, may be contributing to these errors.

It is also shown that mean forecasts from an ensemble of CAMs were substantially more accurate than forecasts from deterministic CAMs. If the improvement seen in the CAM forecasts when going from a deterministic framework to an ensemble framework is comparable to improvements in mesoscale model forecasts when going from a deterministic to an ensemble framework, then an ensemble of mesoscale model forecasts could predict the environment even better than an ensemble of CAMs. Therefore, it is suggested that the combination of mesoscale (convection parameterizing) and CAM configurations is an appropriate avenue to explore for optimizing the use of limited computer resources for severe weather forecasting applications.

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Ryan A. Sobash, John S. Kain, David R. Bright, Andrew R. Dean, Michael C. Coniglio, and Steven J. Weiss

Abstract

With the advent of convection-allowing NWP models (CAMs) comes the potential for new forms of forecast guidance. While CAMs lack the required resolution to simulate many severe phenomena associated with convection (e.g., large hail, downburst winds, and tornadoes), they can still provide unique guidance for the occurrence of these phenomena if “extreme” patterns of behavior in simulated storms are strongly correlated with observed severe phenomena. This concept is explored using output from a series of CAM forecasts generated on a daily basis during the spring of 2008. This output is mined for the presence of extreme values of updraft helicity (UH), a diagnostic field used to identify supercellular storms. Extreme values of the UH field are flagged as simulated “surrogate” severe weather reports and the spatial correspondence between these surrogate reports and actual observed severe reports is determined. In addition, probabilistic forecasts [surrogate severe probabilistic forecasts (SSPFs)] are created from each field’s simulated surrogate severe reports using a Gaussian smoother. The simulated surrogate reports are capable of reproducing the seasonal climatology observed within the field of actual reports. The SSPFs created from the surrogates are verified using ROC curves and reliability diagrams and the sensitivity of the verification metrics to the smoothing parameter in the Gaussian distribution is tested. The SSPFs produce reliable forecast probabilities with minimal calibration. These results demonstrate that a relatively straightforward postprocessing procedure, which focuses on the characteristics of explicitly predicted convective entities, can provide reliable severe weather forecast guidance. It is anticipated that this technique will be even more valuable when implemented within a convection-allowing ensemble forecasting system.

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Matthew D. Flournoy, Anthony W. Lyza, Martin A. Satrio, Madeline R. Diedrichsen, Michael C. Coniglio, and Sean Waugh

Abstract

In this study, we present a climatology of observed cell mergers along the paths of 342 discrete, right-moving supercells and their association with temporal changes in low-level mesocyclone strength (measured using azimuthal shear). Nearly half of the examined supercells experience at least one cell merger. The frequency of cell merger occurrence varies somewhat by geographical region and the time of day. No general relationship exists between cell merger occurrence and temporal changes in low-level azimuthal shear; this corroborates prior studies in showing that the outcome of a merger is probably sensitive to storm-scale and environmental details not captured in this study. Interestingly, we find a significant inverse relationship between pre-merger azimuthal shear and the subsequent temporal evolution of azimuthal shear. In other words, stronger low-level mesocyclones are more likely to weaken after cell mergers, and weaker low-level mesocyclones are more likely to strengthen. We also show that shorter-duration cell merger “events” (comprised of multiple individual mergers) are more likely to be associated with a steady or weakening low-level mesocyclone, while longer-duration cell merger events (3–4 individual mergers) are more likely to be associated with a strengthening low-level mesocyclone. These findings suggest what physical processes may influence the outcome of a merger in different scenarios and that the impact of these processes on low-level mesocyclone strength may change depending on storm maturity. We establish a baseline understanding of the supercell-cell merger climatology and highlight areas for future research in how to better anticipate the outcomes of cell mergers.

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Stacey M. Hitchcock, Russ S. Schumacher, Gregory R. Herman, Michael C. Coniglio, Matthew D. Parker, and Conrad L. Ziegler

Abstract

During the Plains Elevated Convection at Night (PECAN) field campaign, 15 mesoscale convective system (MCS) environments were sampled by an array of instruments including radiosondes launched by three mobile sounding teams. Additional soundings were collected by fixed and mobile PECAN integrated sounding array (PISA) groups for a number of cases. Cluster analysis of observed vertical profiles established three primary preconvective categories: 1) those with an elevated maximum in equivalent potential temperature below a layer of potential instability; 2) those that maintain a daytime-like planetary boundary layer (PBL) and nearly potentially neutral low levels, sometimes even well after sunset despite the existence of a southerly low-level wind maximum; and 3) those that are potentially neutral at low levels, but have very weak or no southerly low-level winds. Profiles of equivalent potential temperature in elevated instability cases tend to evolve rapidly in time, while cases in the potentially neutral categories do not. Analysis of composite Rapid Refresh (RAP) environments indicate greater moisture content and moisture advection in an elevated layer in the elevated instability cases than in their potentially neutral counterparts. Postconvective soundings demonstrate significantly more variability, but cold pools were observed in nearly every PECAN MCS case. Following convection, perturbations range between −1.9 and −9.1 K over depths between 150 m and 4.35 km, but stronger, deeper stable layers lead to structures where the largest cold pool temperature perturbation is observed above the surface.

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Melissa A. Wagner, Robert K. Doe, Chuyuan Wang, Erik Rasmussen, Michael C. Coniglio, Kimberly L. Elmore, Robert C. Balling Jr., and Randall S. Cerveny

Abstract

Topography can have a significant influence on tornado intensity and direction by altering the near-surface inflow. However, past research involving topographic influence on tornadoes has shown significant variety in investigative approaches and conclusions. This study uses unpiloted aerial systems (UAS)–based high-resolution imagery, UAS-based 3D-modeling products, and correlation analyses to examine topographical influences on a portion of the 1 May 2018 Tescott, Kansas, EF3 tornado (EF indicates the enhanced Fujita scale). Two new metrics, visible difference vegetative index (VDVI) gap and VDVI aspect ratio, are introduced to quantify damage severity using UAS-based imagery and elevation information retrieved from a UAS-based digital surface model (DSM). Areas of enhanced scour are seen along the track in areas of local elevation maxima. Correlation analysis shows that damage severity, as measured by both VDVI gap and VDVI aspect ratio, is well correlated with increasing elevation. The VDVI gap is only weakly correlated with slope, and the VDVI aspect ratio is not correlated with slope. These findings are statistically significant at p < 0.05. As the tornado weakened in intensity, the path became nonlinear, traversing between two local elevation maxima. It is hypothesized that fast-moving intense flow formed and weakened as elevation increased over the short spatial distance. This research shows that topography and surface conditions are two of many important variables that should be considered when performing tornado-damage site investigations. It also illustrates the importance of UASs in detailed tornado analysis. VDVI gap and VDVI aspect ratio can provide insight into damage severity as a function of topography.

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Craig S. Schwartz, John S. Kain, Steven J. Weiss, Ming Xue, David R. Bright, Fanyou Kong, Kevin W. Thomas, Jason J. Levit, Michael C. Coniglio, and Matthew S. Wandishin

Abstract

During the 2007 NOAA Hazardous Weather Testbed Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced a daily 10-member 4-km horizontal resolution ensemble forecast covering approximately three-fourths of the continental United States. Each member used the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model core, which was initialized at 2100 UTC, ran for 33 h, and resolved convection explicitly. Different initial condition (IC), lateral boundary condition (LBC), and physics perturbations were introduced in 4 of the 10 ensemble members, while the remaining 6 members used identical ICs and LBCs, differing only in terms of microphysics (MP) and planetary boundary layer (PBL) parameterizations. This study focuses on precipitation forecasts from the ensemble.

The ensemble forecasts reveal WRF-ARW sensitivity to MP and PBL schemes. For example, over the 7-week experiment, the Mellor–Yamada–Janjić PBL and Ferrier MP parameterizations were associated with relatively high precipitation totals, while members configured with the Thompson MP or Yonsei University PBL scheme produced comparatively less precipitation. Additionally, different approaches for generating probabilistic ensemble guidance are explored. Specifically, a “neighborhood” approach is described and shown to considerably enhance the skill of probabilistic forecasts for precipitation when combined with a traditional technique of producing ensemble probability fields.

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Stanley B. Trier, Glen S. Romine, David A. Ahijevych, Robert J. Trapp, Russ S. Schumacher, Michael C. Coniglio, and David J. Stensrud

Abstract

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

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

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Craig S. Schwartz, John S. Kain, Steven J. Weiss, Ming Xue, David R. Bright, Fanyou Kong, Kevin W. Thomas, Jason J. Levit, and Michael C. Coniglio

Abstract

During the 2007 NOAA Hazardous Weather Testbed (HWT) Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced convection-allowing forecasts from a single deterministic 2-km model and a 10-member 4-km-resolution ensemble. In this study, the 2-km deterministic output was compared with forecasts from the 4-km ensemble control member. Other than the difference in horizontal resolution, the two sets of forecasts featured identical Advanced Research Weather Research and Forecasting model (ARW-WRF) configurations, including vertical resolution, forecast domain, initial and lateral boundary conditions, and physical parameterizations. Therefore, forecast disparities were attributed solely to differences in horizontal grid spacing. This study is a follow-up to similar work that was based on results from the 2005 Spring Experiment. Unlike the 2005 experiment, however, model configurations were more rigorously controlled in the present study, providing a more robust dataset and a cleaner isolation of the dependence on horizontal resolution. Additionally, in this study, the 2- and 4-km outputs were compared with 12-km forecasts from the North American Mesoscale (NAM) model. Model forecasts were analyzed using objective verification of mean hourly precipitation and visual comparison of individual events, primarily during the 21- to 33-h forecast period to examine the utility of the models as next-day guidance. On average, both the 2- and 4-km model forecasts showed substantial improvement over the 12-km NAM. However, although the 2-km forecasts produced more-detailed structures on the smallest resolvable scales, the patterns of convective initiation, evolution, and organization were remarkably similar to the 4-km output. Moreover, on average, metrics such as equitable threat score, frequency bias, and fractions skill score revealed no statistical improvement of the 2-km forecasts compared to the 4-km forecasts. These results, based on the 2007 dataset, corroborate previous findings, suggesting that decreasing horizontal grid spacing from 4 to 2 km provides little added value as next-day guidance for severe convective storm and heavy rain forecasters in the United States.

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Matthew A. Campbell, Ariel E. Cohen, Michael C. Coniglio, Andrew R. Dean, Stephen F. Corfidi, Sarah J. Corfidi, and Corey M. Mead

Abstract

The goal of this study is to document differences in the convective structure and motion of long-track, severe-wind-producing MCSs from short-track severe-wind-producing MCSs in relation to the mean wind. An ancillary goal is to determine if these differences are large enough that some criterion for MCS motion relative to the mean wind could be used in future definitions of “derechos.” Results confirm past investigations that well-organized MCSs, including those that produce derechos, tend to move faster than the mean wind, exhibiting a significantly larger degree of propagation (component of MCS motion in addition to the component contributed by the mean flow). Furthermore, well-organized systems that produce shorter-track swaths of damaging winds likewise tend to move faster than the mean wind with a significant propagation component along the mean wind. Therefore, propagation in the direction of the mean wind is not necessarily a characteristic that can be used to distinguish derechos from nonderechos. However, there is some indication that long-track damaging wind events that occur without large-scale or persistent bow echoes and mesoscale convective vortices (MCVs) require a strong propagation component along the mean wind direction to become long lived. Overall, however, there does not appear to be enough separation in the motion characteristics among the MCS types to warrant the inclusion of a mean-wind criterion into the definition of a derecho at this time.

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