This article investigates errors in forecasts of the environment near an elevated mesoscale convective system (MCS) in Iowa on 24-25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. The eastern flank of this MCS produced an outflow boundary (OFB) and moved southeastward along this OFB as a squall line. The western flank of the MCS remained quasi stationary approximately 100 km north of the system's OFB and produced localized flooding. A total of 16 radiosondes were launched near the MCS's eastern flank and 4 were launched near the MCS's western flank.Convective available potential energy (CAPE) increased and convective inhibition (CIN) decreased substantially in observations during the 4 h prior to the arrival of the squall line. In contrast, the model analyses and forecasts substantially underpredicted CAPE and overpredicted CIN owing to their underrepresentation of moisture. Numerical simulations that placed the MCS at varying distances too far to the northeast were analyzed. MCS displacement error was strongly correlated with models' underrepresentation of low-level moisture and their associated overrepresentation of the vertical distance between a parcel's initial height and its level of free convection (Dz LFC , which is correlated with CIN). The overpredicted Dz LFC in models resulted in air parcels requiring unrealistically far northeastward travel in a region of gradual meso-a-scale lift before these parcels initiated convection. These results suggest that erroneous MCS predictions by NWP models may sometimes result from poorly analyzed low-level moisture fields.

Eight years’ worth of day 1 and 4.5 years’ worth of day 2–3 probabilistic convective outlooks from the Storm Prediction Center (SPC) are converted to probability grids spanning the continental United States (CONUS). These results are then evaluated using standard probabilistic forecast metrics including the Brier skill score and reliability diagrams. Forecasts are gridded in two different ways: one with a high-resolution grid and interpolation between probability contours and another on an 80-km-spaced grid without interpolation. Overall, the highest skill is found for severe wind forecasts and the lowest skill is observed for tornadoes; for significant severe criteria, the opposite discrepancy is observed, with highest forecast skill for significant tornadoes and approximately no overall forecast skill for significant severe winds. Highest climatology-relative skill is generally observed over the central and northern Great Plains and Midwest, with the lowest—and often negative—skill seen in the West, southern Texas, and the Atlantic Southeast. No discernible year-to-year trend in skill was identified; seasonally, forecasts verified the best in the spring and late autumn and worst in the summer and early autumn. Forecasts are also evaluated in CAPE-versus-shear parameter space; forecasts struggle most in very low shear but also in high-shear, low-CAPE environments. In aggregate, forecasts for all variables verified more skillfully using interpolated probability grids, suggesting utility in interpreting forecasts as a continuous field. Forecast reliability results depend substantially on the interpretation of the forecast fields, but day 1 and day 2–3 tornado outlooks consistently exhibit an underforecast bias.

This research uses convection-allowing ensemble forecasts to address aspects of the predictability of an extreme rainfall event that occurred in south-central Texas on 25 May 2013, which was poorly predicted by operational and experimental numerical models and caused a flash flood in San Antonio that resulted in three fatalities. Most members of the ensemble had large errors in the location and magnitude of the heavy rainfall, but one member approximately reproduced the observed rainfall distribution. On a regional scale a flow-dependent diurnal cycle in ensemble spread growth is observed with large growth associated with afternoon convection, but the growth rate then reduced after convection dissipates the next morning rather than continuing to grow. Experiments that vary the magnitude of the perturbations to the initial and lateral boundary conditions reveal flow dependencies on the scales responsible for the ensemble growth and the degree to which practical (i.e., deficiencies in observing systems and numerical models) and intrinsic predictability limits (i.e., moist convective dynamic error growth) affect a particular convective event. Specifically, it was found that large-scale atmospheric forcing tends to dominate the ensemble spread evolution, but small-scale error growth can be of near-equal importance in certain convective scenarios where interaction across scales is prevalent and essential to the local precipitation processes. In a similar manner, aspects of the “upscale error growth” and “downscale error cascade” conceptual models are seen in the experiments, but neither completely explains the spread characteristics seen in the simulations.

In some prominent extreme precipitation and flash flood events, radar and rain gauge observations have suggested that the heaviest short-term rainfall accumulations (up to 177 mm h−1) were associated with supercells or mesovortices embedded within larger convective systems. In this research, we aim to identify the influence that rotation has on the storm-scale processes associated with heavy precipitation. Numerical model simulations conducted herein were inspired by a rainfall event that occurred in central Texas in October 2015 where the most extreme rainfall accumulations were collocated with meso-β-scale vortices. Five total simulations were performed to test the sensitivity of precipitation processes to rotation. A control simulation, based on a wind profile from the aforementioned event, was compared with two experiments with successively weaker low-level shear. With greater environmental low-level shear, more precipitation fell, in both a point-maximum and an area-averaged sense. Intense, rotationally induced low-level vertical accelerations associated with the dynamic nonlinear perturbation vertical pressure gradient force were found to enhance the low- to midlevel updraft strength and total vertical mass flux and allowed access to otherwise inhibited sources of moisture and CAPE in the higher-shear simulations. The dynamical accelerations, which increased with the intensity of the low-level shear, dominated over buoyant accelerations in the low levels and were responsible for inducing more intense low-level updrafts that were sustained despite a stable boundary layer.

While both tornadoes and flash floods individually present public hazards, when the two threats are both concurrent and collocated (referred to here as TORFF events), unique concerns arise. This study aims to evaluate the climatological and meteorological characteristics associated with TORFF events over the continental United States. Two separate datasets, one based on overlapping tornado and flash flood warnings and the other based on observations, were used to arrive at estimations of the instances when a TORFF event was deemed imminent and verified to have occurred, respectively. These datasets were then used to discern the geographical and meteorological characteristics of recent TORFF events. During 2008-14, TORFF events were found to be publicly communicated via overlapping warnings an average of 400 times per year, with a maximum frequency occurring in the lower Mississippi River valley. Additionally, 68 verified TORFF events between 2008 and 2013 were identified and subsequently classified based on synoptic characteristics and radar observations. In general, synoptic conditions associated with TORFF events were found to exhibit similar characteristics of typical tornadic environments, but the TORFF environment tended to be moister and have stronger synoptic-scale forcing for ascent. These results indicate that TORFF events occur with appreciable frequency and in complex meteorological scenarios. Furthermore, despite these identified differences, TORFF scenarios are not easily distinguishable from tornadic events that fail to produce collocated flash flooding, and present difficult challenges both from the perspective of forecasting and public communication.