Explore the vast range of titles available.

To better understand and forecast nocturnal thunderstorms and their hazards, an expansive network of fixed and mobile observing systems was deployed in the summer of 2015 for the Plains Elevated Convection at Night (PECAN) field experiment to observe low-level jets, convection initiation, bores, and mesoscale convective systems. On 5–6 July 2015, mobile radars and ground-based surface and upper-air profiling systems sampled a nocturnal, quasi-linear convective system (QLCS) over South Dakota. The QLCS produced several severe wind reports and an EF-0 tornado. The QLCS and its environment leading up to the mesovortex that produced this tornado were well observed by the PECAN observing network. In this study, observations from radiosondes, Doppler radars, and aircraft are assimilated into an ensemble analysis and forecasting system to analyze this event with a focus on the development of the observed tornadic mesovortex. All ensemble members simulated low-level mesovortices with one member in particular generating two mesovortices in a manner very similar to that observed. Forecasts from this member were analyzed to examine the processes increasing vertical vorticity during the development of the tornadic mesovortex. Cyclonic vertical vorticity was traced to three separate airstreams: the first from southerly inflow that was characterized by tilting of predominantly crosswise horizontal vorticity along the gust front, the second from the north that imported streamwise horizontal vorticity directly into the low-level updraft, and the third from a localized downdraft/rear-inflow jet in which the horizontal vorticity became streamwise during descent. The cyclonic vertical vorticity then intensified rapidly through intense stretching as the parcels entered the low-level updraft of the developing mesovortex.

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

This study evaluates forecasts of thermodynamic variables from five convection-allowing configurations of the Weather Research and Forecasting Model (WRF) with the Advanced Research core (WRF-ARW). The forecasts vary only in their planetary boundary layer (PBL) scheme, including three “local” schemes [Mellor–Yamada–Janjić (MYJ), quasi-normal scale elimination (QNSE), and Mellor–Yamada–Nakanishi–Niino (MYNN)] and two schemes that include “nonlocal” mixing [the asymmetric cloud model version 2 (ACM2) and the Yonei University (YSU) scheme]. The forecasts are compared to springtime radiosonde observations upstream from deep convection to gain a better understanding of the thermodynamic characteristics of these PBL schemes in this regime. The morning PBLs are all too cool and dry despite having little bias in PBL depth (except for YSU). In the evening, the local schemes produce shallower PBLs that are often too shallow and too moist compared to nonlocal schemes. However, MYNN is nearly unbiased in PBL depth, moisture, and potential temperature, which is comparable to the background North American Mesoscale model (NAM) forecasts. This result gives confidence in the use of the MYNN scheme in convection-allowing configurations of WRF-ARW to alleviate the typical cool, moist bias of the MYJ scheme in convective boundary layers upstream from convection. The morning cool and dry biases lead to an underprediction of mixed-layer CAPE (MLCAPE) and an overprediction of mixed-layer convective inhibition (MLCIN) at that time in all schemes. MLCAPE and MLCIN forecasts improve in the evening, with MYJ, QNSE, and MYNN having small mean errors, but ACM2 and YSU having a somewhat low bias. Strong observed capping inversions tend to be associated with an underprediction of MLCIN in the evening, as the model profiles are too smooth. MLCAPE tends to be overpredicted (underpredicted) by MYJ and QNSE (MYNN, ACM2, and YSU) when the observed MLCAPE is relatively small (large).

The word “derecho” was first used by Gustavus Hinrichs in 1888 to distinguish the widespread damaging windstorms that occurred on occasion over the mid–Mississippi Valley region of the United States from damaging winds associated with tornadoes. The term soon fell into disuse, however, and did not reappear in the literature until Robert Johns and William Hirt resurrected it in the mid-1980s. While the present definition of derecho served well during the early years of the term’s reintroduction to the meteorological community, it has several short-comings. These have become more apparent in recent years as various studies shed light on the physical processes responsible for the production of widespread damaging winds. In particular, the current definition’s emphasis on the coverage of storm damage reports at the expense of identifying the convective structures and physical processes deemed responsible for the reports has led to the term being applied to wind events beyond those for which it originally was intended. The revised definition of a derecho proposed herein is intended to focus more specifically on those types of windstorms that are most damaging and potentially life threatening because of their intensity, sustenance, and degree of organization. The proposal is not intended to be final or all encompassing, but rather an initial step toward ultimately realizing a more complete, physically based taxonomy that also addresses other forms of damaging-windproducing convective systems.

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.

Cold pools are a key element in the organization of precipitating convective systems, yet knowledge of their typical surface characteristics is largely anecdotal. To help to alleviate this situation, cold pools from 39 mesoscale convective system (MCS) events are sampled using Oklahoma Mesonet surface observations. In total, 1389 time series of surface observations are used to determine typical rises in surface pressure and decreases in temperature, potential temperature, and equivalent potential temperature associated with the cold pool, and the maximum wind speeds in the cold pool. The data are separated into one of four convective system life cycle stages: first storms, MCS initiation, mature MCS, and MCS dissipation. Results indicate that the mean surface pressure rises associated with cold pools increase from 3.2 hPa for the first storms’ life cycle stage to 4.5 hPa for the mature MCS stage before dropping to 3.3 hPa for the dissipation stage. In contrast, the mean temperature (potential temperature) deficits associated with cold pools decrease from 9.5 (9.8) to 5.4 K (5.6 K) from the first storms to the dissipation stage, with a decrease of approximately 1 K associated with each advance in the life cycle stage. However, the daytime and early evening observations show mean temperature deficits over 11 K. A comparison of these observed cold pool characteristics with results from idealized numerical simulations of MCSs suggests that observed cold pools likely are stronger than those found in model simulations, particularly when ice processes are neglected in the microphysics parameterization. The mean deficits in equivalent potential temperature also decrease with the MCS life cycle stage, starting at 21.6 K for first storms and dropping to 13.9 K for dissipation. Mean wind gusts are above 15 m s−1 for all life cycle stages. These results should help numerical modelers to determine whether the cold pools in high-resolution models are in reasonable agreement with the observed characteristics found herein. Thunderstorm simulations and forecasts with thin model layers near the surface are also needed to obtain better representations of cold pool surface characteristics that can be compared with observations.

Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by the Center for Analysis and Prediction of Storms during the spring of 2009 are evaluated using area under the relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined for ensemble size n from 1 to 17 members and for spatial scales ranging from 4 to 200 km. Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing ROC areas for each n to those of the full 17-member ensemble revealed that more members are required to reach statistically indistinguishable PQPF skill relative to the full ensemble as forecast lead time increases and spatial scale decreases. These results appear to reflect the broadening of the forecast probability distribution function (PDF) of future atmospheric states associated with decreasing spatial scale and increasing forecast lead time. They also illustrate that efficient allocation of computing resources for convection-allowing ensembles requires careful consideration of spatial scale and forecast length desired.

Hundreds of supercell proximity soundings obtained for field programs over the central United States are analyzed to reconcile differences in recent studies and to refine our knowledge of supercell environments. The large, storm-centric observation-based dataset and high vertical resolution of the sounding data provide an unprecedented look at supercell environments. Not surprisingly, storm-relative environmental helicity (SRH) is found to be larger in tornadic soundings than in nontornadic soundings. The primary finding that departs from previous studies is that storm-relative winds contribute substantially to the larger SRH. Stronger ground-relative winds and more rightward-deviant storm motions contribute to the larger storm-relative winds for the tornadic soundings. Spatial analyses of the soundings reveal lower near-ground pressure perturbations and stronger low- to midlevel cyclonic flow for the tornadic soundings, which suggests stronger mesocyclones, perhaps explaining the more rightward-deviant motions. Differences in the mean critical angle between the tornadic and nontornadic soundings are small and do not contribute to the larger mean SRH, but the tornadic soundings do have fewer instances of smaller (<60°) critical angles. Furthermore, the critical angle is shown to be a function of azimuth from the updraft. Other results include a low-to-the-ground (~250 m on average) hodograph kink for both the tornadic and nontornadic soundings and few notable differences in thermodynamic quantities, except for the expected lower LCLs related to higher RH for the tornadic soundings, somewhat smaller 0–3 km lapse rates in tornadic environments related to weaker/shallower capping inversions, and larger 0–3 km CAPE in near-field environments.

This study documents the complex environment and early evolution of the remarkable derecho that traversed portions of the central United States on 8 May 2009. Central to this study is the comparison of the 8 May 2009 derecho environment to that of other mesoscale convective systems (MCSs) that occurred in the central United States during a similar time of year. Synoptic-scale forcing was weak and thermodynamic instability was limited during the development of the initial convection, but several mesoscale features of the environment appeared to contribute to initiation and upscale growth, including a mountain wave, a midlevel jet streak, a weak midlevel vorticity maximum, a “Denver cyclone,” and a region of upper-tropospheric inertial instability. The subsequent MCS developed in an environment with an unusually strong and deep low-level jet (LLJ), which transported exceptionally high amounts of low-level moisture northward very rapidly, destabilized the lower troposphere, and enhanced frontogenetical circulations that appeared to aid convective development. The thermodynamic environment ahead of the developing MCS contained unusually high precipitable water (PW) and very large midtropospheric lapse rates, compared to other central plains MCSs. Values of downdraft convective available potential energy (DCAPE), mean winds, and 0–6-km vertical wind shear were not as anomalously large as the PW, lapse rates, and LLJ. In fact, the DCAPE values were lower than the mean values in the comparison dataset. These results suggest that the factors contributing to updraft strength over a relatively confined area played a significant role in generating the strong outflow winds at the surface, by providing a large volume of hydrometeors to drive the downdrafts.

A total of 257 supercell proximity soundings obtained for field programs over the central United States are compared with profiles extracted from the SPC mesoscale analysis system (the SFCOA) to understand how errors in the SFCOA and in its baseline model analysis system—the RUC/RAP—might impact climatological assessments of supercell environments. A primary result is that the SFCOA underestimates the low-level storm-relative winds and wind shear, a clear consequence of the lack of vertical resolution near the ground. The near-ground (≤500 m) wind shear is underestimated similarly in near-field, far-field, tornadic, and nontornadic supercell environments. The near-ground storm-relative winds, however, are underestimated the most in the near-field and in tornadic supercell environments. Underprediction of storm-relative winds is, therefore, a likely contributor to the lack of differences in storm-relative winds between nontornadic and tornadic supercell environments in past studies that use RUC/RAP-based analyses. Furthermore, these storm-relative wind errors could lead to an under emphasis of deep-layer SRH variables relative to shallower SRH in discriminating nontornadic from tornadic supercells. The mean critical angles are 5°–15° larger and farther from 90° in the observed soundings than in the SFCOA, particularly in the near field, likely indicating that the ratio of streamwise to crosswise horizontal vorticity is often smaller than that suggested by the SFCOA profiles. Errors in thermodynamic variables are less prevalent, but show low-level CAPE to be too low closer to the storms, a dry bias above the boundary layer, and the absence of shallow near-ground stable layers that are much more prevalent in tornadic supercell environments.