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Tornadoes produced by right-moving supercells (RM) and quasi-linear convective systems (QLCS) are compared across the contiguous United States for the period 2003–2021, based on the maximum F/EF-scale rating per hour on a 40-km horizontal grid. The frequency of QLCS tornadoes has increased dramatically since 2003 while the frequency of RM tornadoes has decreased during that same period. Prior work noting that the most common damage rating for QLCS tornadoes at night is EF1 persists in this larger, independent sample. A comparison of WSR-88D radar attributes between RM and QLCS tornadoes shows no appreciable differences between EF0 tornadoes produced by either convective mode. Differences become apparent for EF1–2 tornadoes, where rotational velocity is larger and velocity couplet diameter is smaller for RM tornadoes compared to QLCS tornadoes. The frequency of tornadic debris signatures (TDS) in dual polarization data is also larger for EF1–2 RM tornadoes when controlling for tornadoes sampled relatively close to the radar sites, and during daylight versus overnight. The weaker rotational velocities, broader velocity couplet diameters, and lower frequencies of TDSs both close to the radar and at night for QLCS EF1 tornadoes suggest that a combination of inadequate radar sampling and occasional misclassification of wind damage may be responsible for the irregularities in the historical record of QLCS tornado reports.

Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–18) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance. Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment, which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (1 n mi; 1 n mi = 1.852 km) circulations in a poor (STP = 0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

The elastic modulus and hydrophilicity of cross-linked poly(dimethylsiloxane) (PDMS) are tunable via cross-linker concentration and the addition of a simple surfactant, C12E4, before curing. However, the surfactant concentration, [C12E4], reduces the elastic modulus (73% lower for 6.3% w/w) because it reduces the extent of curing. This is likely because the hygroscopic surfactant results in water poisoning of the catalyst. Three distinct time-dependent hydrophilicity profiles were identified using water contact angle analysis with [C12E4] determining which profile was observed. This indicates the concentration-dependent phase behavior of C12E4 within PDMS films. Changes in phase behavior were identified using small-angle neutron scattering (SANS) and a compatibility study. No surface excess or surface segregation of surfactant was observed at the PDMS–air interface. However, a surface excess revealed by neutron reflectivity against a D2O interface indicates that the increase in hydrophilicity results from the migration of C12E4 to the film interface when exposed to water.

All tornado reports across the contiguous United States from 2003-2011 were filtered for the maximum damage rating on an hourly grid with 40-km horizontal spacing. Convective mode was assigned to each grid-hour tornado event via manual examination of full volumetric WSR-88D data, and supercell-related environmental parameters accompanied each grid-hour tornado event from the hourly objective analyses calculated and archived at the Storm Prediction Center. Only tornado events associated with right-moving supercells (RM) or quasi-linear convective systems (QLCS) were considered in this work, which resulted in a sample of 8837 tornado grid-hour events. Spatial distributions of supercell-related parameters were constructed for the RM and QLCS tornado events. Sample sizes were increased by accumulating tornado events within a 120-km neighborhood to each 40-km grid box. All neighborhoods with ≥10 events were retained for percentile rank distributions of the supercell-related parameters, and then smoothed using a Gaussian kernel with a 120-km influence radius. Regional variations in buoyancy and lifting condensation level (LCL) are apparent-RM tornadoes are more common with greater buoyancy and higher LCL heights across the Great Plains compared to the Mississippi Valley region. QLCS tornadoes tend to be focused across the Ohio and Mississippi Valleys, in environments with weaker buoyancy and lower LCL heights. Vertical wind shear parameters are typically well within the parameter space associated with tornadic RM for both the RM and QLCS tornado events. The significant tornado parameter shows improved discrimination between weak and significant RM tornadoes, compared to individual kinematic or thermodynamic parameters.

This study analyzes the behavior of storm-scale circulations preceding initial tornadogenesis in 179 Kansas and Nebraska storms. Manually determined assessments of radar data for storm-scale circulations preceding the tornadoes are performed as far back in time prior to the tornado as a circulation is apparent, with average rotational velocity (Vrot), circulation diameter, and circulation clarity documented for the 0.5° elevation scan. These data are simultaneously combined with an indication of environmental conditions (as represented by the significant tornado parameter) to determine the tornado probability at each of these times based on a recently developed probabilistic model. By aggregating these parameters in time-range bins, subsequent statistical analyses portray the bulk variability of circulation characteristics and tornado probabilities preceding tornadogenesis. The blended approach for assessing tornado potential yields a stronger relative increase in tornado probabilities leading up to tornadogenesis than the sub-component of average Vrot; this is especially true within 15 min before tornadogenesis. Additionally, significant tornadoes are associated with more substantial increase in tornado probabilities preceding tornadogenesis compared to weak tornadoes, and smaller lead time to tornadogenesis for weak tornadoes. Also, a cycling pattern may appear in velocities prior to significant tornadoes, along with a relative decrease in pretornadic circulation diameter, especially for significant tornadoes. These findings are intended to highlight some of the behaviors of storm-scale circulations and their corresponding environments, which can be used to reinforce meteorologists’ tornado threat assessment. Extending this work to encompass more convective-mode variability, null cases, and geographic expanse will be necessary for more overarching applicability.

Errors in operational forecasts of return flow events (RFEs) over the Gulf of Mexico have dictated the search for sources of these errors. Based on earlier studies, likely candidates for these errors are: incorrect parameterization of turbulent transfer processes at the air-sea interface, uncertain vertical motion above the mixed layer, and incorrect initial conditions. We investigate these possible sources of error by performing numerical experiments with a Monte Carlo ensemble prediction model applied to a well-observed case in February 1988. In essence, we examine uncertainty in prediction due to uncertainty in the model’s elements of control. A mixed-layer model with roughly 50 elements of control is used to determine forecast uncertainty due to initial conditions alone, boundary conditions alone, parameterization alone, as well as the full complement of uncertainty in these elements of control. The uncertainty is calculated at points along a predetermined outflow trajectory that originates over shelf waters in the northeastern Gulf, passes north of the Yucatan Peninsula, and terminates in the west-central Gulf-all points along the trajectory are characterized by convective heating at the sea-air interface. Results from the numerical experiments led to the following results: 1) parameterization of physical processes exerts the greatest influence on forecast uncertainty, and 2) the water-vapor mass in the mixed-layer column is uncertain by a factor of two at the trajectory’s terminal point. The latter result confirms forecasters’ long-held view that vapor return is the most suspect product in operational prediction of RFEs. In addition to these numerical experiments with the 1988 case, a recent RFE is examined in the context of operational model performance at the National Center for Environmental Prediction (NCEP). The paper ends with discussion of steps to be taken that hold promise for improved operational prediction of RFEs over the Gulf of Mexico.

Nocturnal significant-tornado events are investigated in association with a similar synoptic pattern in the spring, over the central and southern Great Plains, from 1999–2009. This pattern is characterized by a well-defined midlevel trough over the Intermountain West, with prevailing southwesterly winds at 500 hPa over the central United States. The underlying topography of the region contributes to the development or deepening of a lee cyclone over the High Plains with the rapid intensification of a low-level jet stream (LLJS) observed around 0000–0300 UTC. The LLJS development is as much as 3–6 h sooner and driven by different dynamical processes than that documented with the nocturnal boundary-layer wind maximum (NBLWM). In the 15 documented tornado cases, ratings of the nocturnal tornadoes exceed that of any antecedent, daytime occurrence. To determine which aspects of the local environment are critical to nocturnal tornado development within the context of the identified synoptic pattern, a similar sample of 18 nontornadic cases was compiled during the same time period. Rapid Update Cycle-2 (RUC-2) soundings representative of the warm sector environment revealed that the most important differences between the tornadic and nontornadic cases involved low-level thermodynamic profiles. Comparison of several thermodynamic parameters indicates that low-level static stability is a strong discriminator between the tornadic and nontornadic cases, with the tornadic cases characterized by larger mixing ratios, smaller convective inhibition, and a lower level of free convection.

Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew T–logp diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10 000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3 × 3 nodes, resulting in a set of nine hodographs and nine skew T–logp diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and midlevel lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.

A sample of damage-surveyed tornadoes in the contiguous United States (2009–17), containing specific wind speed estimates from damage indicators (DIs) within the Damage Assessment Toolkit dataset, were linked to radar-observed circulations using the nearest WSR-88D data in Part I of this work. The maximum wind speed associated with the highest-rated DI for each radar scan, corresponding 0.5° tilt angle rotational velocity Vrot, significant tornado parameter (STP), and National Weather Service (NWS) convective impact-based warning (IBW) type, are analyzed herein for the sample of cases in Part I and an independent case sample from parts of 2019–20. As Vrot and STP both increase, peak DI-estimated wind speeds and IBW warning type also tend to increase. Different combinations of Vrot, STP, and population density—related to ranges of peak DI wind speed—exhibited a strong ability to discriminate across the tornado damage intensity spectrum. Furthermore, longer duration of high Vrot (i.e., ≥70 kt) in significant tornado environments (i.e., STP ≥ 6) corresponds to increasing chances that DIs will reveal the occurrence of an intense tornado (i.e., EF3+). These findings were corroborated via the independent sample from parts of 2019–20, and can be applied in a real-time operational setting to assist in determining a potential range of wind speeds. This work provides evidence-based support for creating an objective and consistent, real-time framework for assessing and differentiating tornadoes across the tornado intensity spectrum.

The Storm Prediction Center (SPC) has developed a database of damage-surveyed tornadoes in the contiguous United States (2009–17) that relates environmental and radar-derived storm attributes to damage ratings that change during a tornado life cycle. Damage indicators (DIs), and the associated wind speed estimates from tornado damage surveys compiled in the Damage Assessment Toolkit (DAT) dataset, were linked to the nearest manual calculations of 0.5° tilt angle maximum rotational velocity Vrot from single-site WSR-88D data. For each radar scan, the maximum wind speed from the highest-rated DI, Vrot, and the significant tornado parameter (STP) from the SPC hourly objective mesoscale analysis archive were recorded and analyzed. Results from examining Vrot and STP data indicate an increasing conditional probability for higher-rated DIs (i.e., EF-scale wind speed estimate) as both STP and Vrot increase. This work suggests that tornadic wind speed exceedance probabilities can be estimated in real time, on a scan-by-scan basis, via Vrot and STP for ongoing tornadoes.

In supercell environments, previous authors have shown strong connections between the vertical wind shear magnitude, updraft width, and entrainment. Based on these results, it is hypothesized that the influences of entrainment-driven dilution on buoyancy and maximum updraft vertical velocity w in supercell environments are a predictable function of the vertical wind shear profile. It is also hypothesized that the influences of pressure perturbation forces on maximum updraft w are small because of a nearly complete offset between upward dynamic pressure forces and downward buoyant pressure forces. To address these hypotheses, we derive a formula for the maximum updraft w that incorporates the effects of entrainment-driven dilution on buoyancy but neglects pressure gradient forces. Solutions to this formula are compared with output from previous numerical simulations. This formula substantially improves predictions of maximum updraft w over past CAPE-derived formulas for maximum updraft w, which supports the first hypothesis. Furthermore, integrated vertical accelerations along trajectories show substantial offsets between dynamic and buoyant pressure forces, supporting the second hypothesis. It is argued that the new formula should be used in addition to CAPE-derived measures for w in forecast and research applications when accurate diagnosis of updraft speed is required.

The relationship between storm-relative helicity (SRH) and streamwise vorticity ωs is frequently invoked to explain the often robust connections between effective inflow layer (EIL) SRH and various supercell updraft properties. However, the definition of SRH also contains storm-relative (SR) flow, and the separate influences of SR flow and ωs on updraft dynamics are therefore convolved when SRH is used as a diagnostic tool. To clarify this issue, proximity soundings and numerical experiments are used to disentangle the separate influences of EIL SR flow and ωs on supercell updraft characteristics. Our results suggest that the magnitude of EIL ωs has little influence on whether supercellular storm mode occurs. Rather, the transition from nonsupercellular to supercellular storm mode is largely modulated by the magnitude of EIL SR flow. Furthermore, many updraft attributes such as updraft width, maximum vertical velocity, vertical mass flux at all levels, and maximum vertical vorticity at all levels are largely determined by EIL SR flow. For a constant EIL SR flow, storms with large EIL ωs have stronger low-level net rotation and vertical velocities, which affirms previously established connections between ωs and tornadogenesis. EIL ωs also influences storms’ precipitation and cold-pool patterns. Vertical nonlinear dynamic pressure acceleration (NLDPA) is larger at low levels when EIL ωs is large, but differences in NLDPA aloft become uncorrelated with EIL ωs because storms’ midlevel dynamic pressure perturbations are substantially influenced by the tilting of midlevel vorticity. Our results emphasize the importance of considering EIL SR flow in addition to EIL SRH in the research and forecasting of supercell properties.

A method for predicting the optimal conditions for polymer extrusion, which relies only on gramscale laboratory experiments for two commercial polystyrene samples with two molecular weights is demonstrated by oscillatory rheology. These enable a shear viscosity map vs. temperature and shear rate to be constructed, together with the positions for the major molecular timescales. Alternative methods for characterising rheology, including melt flow index and capillary rheology measurements were also employed, but these do not give the same level of understanding of flow behaviour. The capillary tests generates die swell and this complex behaviour can be seen to collapse onto a single line regardless of temperature when plotted using the Rouse–Weissenberg number. The full shear viscosity map, together with the polymer timescales serves as a design tool to predict processing behaviour for melt processors. The work represents and builds on major academic-industry collaborative research programmes.

The compatibility and surface behavior of squalane–polybutadiene mixtures are studied by experimental cloud point and neutron reflectivity measurements, statistical associating fluid theory (SAFT), and molecular dynamics (MD) simulations. A SAFT-γ Mie model is shown to be successful in capturing the cloud point curves of squalane–polybutadiene and squalane–cis-polybutadiene binary mixtures, and the same SAFT-γ Mie model is used to develop a thermodynamically consistent top-down coarse-grained force field to describe squalane–polybutadiene. Coarse-grained molecular dynamics simulations are performed to study surface behavior for different concentrations of squalane, with the system exhibiting surface enrichment and a wetting transition. Simulated surface profiles are compared with those obtained by fitting to neutron reflectivity data obtained from thin films composed of deuterated squalane (d-sq)–polybutadiene. The presented top-down parametrization methodology is a fast and thermodynamically reliable approach for predicting properties of oligomer–polymer mixtures, which can be challenging for either theory or MD simulations alone.

The surface properties of epoxy resin coatings influence their function as substrates for subsequent coats. Variation in ambient cure conditions (temperature and relative humidity, RH), stoichiometry (ratio of epoxy: amine) and delay time between epoxy component mixing and film casting ("induction time") significantly altered the surface properties of ambient cured epoxy resin coatings (Dow Epoxy Novolac D.E.N. 431, resorcinol diglycidyl ether and 4,4-diaminodicyclohexylmethane). Gravimetric analysis showed that increasing induction time significantly reduced surface layer formation (carbamation) of cured epoxy resin coatings at 80% RH but had no measurable effect at 40% RH and below. RMS surface roughness increased with increasing RH and decreased with increasing induction time and ambient cure temperature, at two stoichiometric extremes. However, the net change in surface area arising from these conditions was not sufficient to significantly alter the equilibrium contact angles or wetting regime. We conclude that the observed significant variation in surface wettability was more likely to depend on variation in surface chemistry than roughness; stoichiometry was the variable which most significantly influenced surface wettability, average void volume and fractional free volume, while cure temperature significantly influenced the extent of cure at both stoichiometries. Off-stoichiometry formulation and elevated ambient cure temperature significantly increased system average void volume while fractional free volume decreased, which may be significant for the barrier properties of the final coating.

The response of severe local storms to environmental evolution across the early evening transition (EET) remains a forecasting challenge, particularly within the context of the Southeast US storm climatology, which includes the increased presence of low-CAPE environments and tornadic non-supercell modes. To disentangle these complex environmental interactions, Southeast severe convective reports spanning 2003-2018 are temporally binned relative to local sunset. Sounding-derived data corresponding to each report are used to characterize how the near-storm environment evolves across the EET, and whether these changes influence the mode, frequency, and tornadic likelihood of their associated storms. High-shear, high-CAPE (HSHC) environments are contrasted with high-shear, low-CAPE (HSLC) environments to highlight physical processes governing storm maintenance and tornadogenesis in the absence of large instability. Lastly, statistical analysis is performed to determine which aspects of the near-storm environment most effectively discriminate between tornadic (or significantly tornadic) and nontornadic storms towards constructing new sounding-derived forecast guidance parameters for multiple modal and environmental combinations. Results indicate that HSLC environments evolve differently than HSHC environments, particularly for non-supercell (e.g., quasi-linear convective system) modes. These low-CAPE environments sustain higher values of low-level shear and storm-relative helicity (SRH) and destabilize post-sunset – potentially compensating for minimal buoyancy. Furthermore, the existence of HSLC storm environments pre-sunset increases the likelihood of non-supercellular tornadoes post-sunset. Existing forecast guidance metrics such as the significant tornado parameter (STP) remain the most skillful predictors of HSHC tornadoes. However, HSLC tornado prediction can be improved by considering variables like precipitable water, downdraft CAPE, and effective inflow base.

A dataset maintained by the Storm Prediction Center (SPC) of 6300 tornado events from 2009–2015, consisting of radar-identified convective modes and near-storm environmental information obtained from Rapid Update Cycle and Rapid Refresh model analysis grids, has been augmented with additional radar information related to the low-level mesocyclones associated with tornado longevity, path-length, and width. All EF2–EF5 tornadoes, in addition to randomly selected EF0–EF1 tornadoes, were extracted from the SPC dataset, which yielded 1268 events for inclusion in the current study. Analysis of that data revealed similar values of the effective-layer significant tornado parameter for the longest-lived (60+ min) tornadic circulations, longest-tracked (≥ 68 km) tornadoes, and widest tornadoes (≥ 1.2 km). However, the widest tornadoes occurring west of –94° longitude were associated with larger mean-layer convective available potential energy, storm-top divergence, and low-level rotational velocity. Furthermore, wide tornadoes occurred when low-level winds were out of the southeast resulting in large low-level hodograph curvature and near-surface horizontal vorticity that was more purely streamwise compared to long-lived and long-tracked events. On the other hand, tornado path-length and longevity were maximized with eastward migrating synoptic-scale cyclones associated with strong southwesterly wind profiles through much of the troposphere, fast storm motions, large values of bulk wind difference and storm-relative helicity, and lower buoyancy.

This study examines the possibility that supercell tornado forecasts could be improved by utilizing the storm-relative helicity (SRH) in the lowest few hundred meters of the atmosphere (instead of much deeper layers). This hypothesis emerges from a growing body of literature linking the near-ground wind profile to the organization of the low-level mesocyclone and thus the probability of tornadogenesis. This study further addresses the ramifications of near-ground SRH to the skill of the significant tornado parameter (STP), which is probably the most commonly used environmental indicator for tornadic thunderstorms. Using a sample of 20 194 severe, right-moving supercells spanning a 13-yr period, sounding-derived parameters were compared using forecast verification metrics, emphasizing a high probability of detection for tornadic supercells while minimizing false alarms. This climatology reveals that the kinematic components of environmental profiles are more skillful at discriminating significantly tornadic supercells from severe, nontornadic supercells than the thermodynamic components. The effective-layer SRH has by far the greatest forecast skill among the components of the STP, as it is currently defined. However, using progressively shallower layers for the SRH calculation leads to increasing forecast skill. Replacing the effective-layer SRH with the 0–500 m AGL SRH in the formulation of STP increases the number of correctly predicted events by 8% and decreases the number of missed events and false alarms by 18%. These results provide promising evidence that forecast parameters can still be improved through increased understanding of the environmental controls on the processes that govern tornado formation.

The southeastern United States has become a prime area of focus in tornado-related literature due, in part, to the abundance of tornadoes occurring in high-shear low-CAPE (HSLC) environments. Through this analysis of 4133 tornado events and 16 429 tornado warnings in the southeastern United States, we find that tornadoes in the Southeast do indeed have, on average, higher shear and lower CAPE than tornadoes elsewhere in the contiguous United States (CONUS). We also examine tornado warning skill in the form of probability of detection (POD; percent of tornadoes receiving warning prior to tornado occurrence) and false alarm ratio (FAR; percent of tornado warnings for which no corresponding tornado is detected), and find that, on average, POD is better and FAR is worse for tornadoes in the Southeast than for the CONUS as a whole. These measures of warning skill remain consistent even when we consider only HSLC tornadoes. The Southeast also has nearly double the CONUS percentage of deadly tornadoes, with the highest percentage of these deadly tornadoes occurring during the spring, the winter, and around local sunset. On average, however, the tornadoes with the lowest POD also tend to be those that are weakest and least likely to be deadly; for the most part, the most dangerous storms are indeed being successfully warned.

Helical nanofibres play key roles in many biological processes. Entanglements between helices can aid gelation by producing thick, interconnected fibres, but the details of this process are poorly understood. Here, we describe the assembly of an achiral oligo(urea) peptidomimetic compound into supramolecular helices. Aggregation of adjacent helices leads to the formation of fibrils, which further intertwine to produce high-fidelity braids with periodic crossing patterns. A braid theory analysis suggests that braiding is governed by rigid topological constraints, and that branching occurs due to crossing defects in the developing braids. Mixed-chirality helices assemble into relatively complex, odd-stranded braids, but can also form helical bundles by undergoing inversions of chirality. The oligo(urea) assemblies are also highly sensitive to chiral amplification, proposed to occur through a majority-rules mechanism, whereby trace chiral materials can promote the formation of gels containing only homochiral helices.

Probabilistic ensemble-derived tornado forecasts generated from convection-allowing models often use hourly maximum updraft helicity (UH) alone or in combination with environmental parameters as a proxy for right-moving (RM) supercells. However, when UH occurrence is a condition for tornado probability generation, false alarm areas can occur from UH swaths associated with nocturnal mesoscale convective systems, which climatologically produce fewer tornadoes than RM supercells. This study incorporates UH timing information with the forecast near-storm significant tornado parameter (STP) to calibrate the forecast tornado probability. To generate the probabilistic forecasts, three sets of observed climatological tornado frequencies given an RM supercell and STP value are incorporated with the model output, two of which use UH timing information. One method uses the observed climatological tornado frequency for a given 3-h window to generate the probabilities. Another normalizes the observed climatological tornado frequency by the number of hail, wind, and tornado reports observed in that 3-h window compared to the maximum number of reports in any 3-h window. The final method is independent of when UH occurs and uses the observed climatological tornado frequency encompassing all hours. The normalized probabilities reduce the false alarm area compared to the other methods but have a smaller area under the ROC curve and require a much higher percentile of the STP distribution to be used in probability generation to become reliable. Case studies demonstrate that the normalized probabilities highlight the most likely area for evening RM supercellular tornadoes, decreasing the nocturnal false alarm by assuming a linear convective mode.

We are at an interesting time in the understanding of alpha herpesvirus latency and reactivation and their implications to human disease. Conceptual advances have come from both animal and neuronal culture models. This review focuses on the concept that the tegument protein and viral transactivator VP16 plays a major role in the transition from latency to the lytic cycle. During acute infection, regulation of VP16 transactivation balances spread in the nervous system, establishment of latent infections and virulence. Reactivation is dependent on this transactivator to drive entry into the lytic cycle. In vivo de novo expression of VP16 protein is mediated by sequences conferring pre-immediate early transcription embedded in the normally leaky late promoter. In vitro, alternate mechanisms regulating VP16 expression in the context of latency have come from the SCG neuron culture model and include the concepts that (i) generalized transcriptional derepression of the viral genome and sequestration of VP16 in the cytoplasm for ~48 hours (Phase I) precedes and is required for VP16-dependent reactivation (Phase II), and (ii) a histone methyl/phospho switch during Phase I is required for Phase II reactivation. The challenge to the field is reconciling these data into a unified model of virus reactivation. The task of compiling this review was uncomfortably humbling, as if cataloging the stars in the universe. While not completely dark, our night sky is missing a multitude of studies which are among the many points of light contributing to our field. This article is a focused review in which we discuss from the vantage point of our expertise, just a handful of concepts that have or are emerging. A lookback at some of the pioneering work that grounds our field is also included.

Due to their inherently high surface energy, polar end-functionalised polymers do not normally adsorb to the external surfaces of blends. However, adsorption of polar functionalities can be induced rapidly by annealing in a polar environment such as glycerol prior to quenching to a glassy state. Blended films of carboxy end-functionalised deuteriopolystyrene (dPS-COOH) with hydrogenous polystyrene (hPS) were annealed at 150 °C under glycerol. Nuclear reaction analysis was used to quantify the surface excess of dPS-COOH retained at the surface after quenching the films to below the glass transition temperature. Incorporation of multiple COOH groups onto a single chain end greatly increases the affinity of these chains to the interface with glycerol. Here we have shown that even a difunctional material, dPS-2COOH, is much more surface active than either the singly functionalised dPS-COOH or the difunctional ester from which it was prepared. Self-consistent mean field theory yielded thermodynamic ‘sticking energy’ values per functionality at the polystyrene–glycerol surface of 1.3–1.7 kBT for carboxy groups and 0.3 kBT for ester groups.

The vertical depth distributions of amine oxide surfactants, N,N-dimethyldodecyl amine N-oxide (DDAO) and N,N-dimethyltetradecyl amine N-oxide (DTAO), in poly(vinyl alcohol) (PVA) films were explored using neutron reflectometry (NR). In both binary and plasticized films, the two deuterated surfactants formed a single monolayer on the film surface with the remaining surfactant homogeneously distributed throughout the bulk of the film. Small-angle neutron scattering and mechanical testing revealed that these surfactants acted like plasticizers in the bulk, occupying the amorphous regions of PVA and reducing its glass-transition temperature. NR revealed little impact of plasticizer (glycerol) incorporation on the behavior of these surfactants in PVA. The surfactant molecular area in the segregated monolayer was smaller for DTAO than for DDAO, indicating that the larger molecule was more densely packed at the surface. Surface tension was used to assess the solution behavior of these surfactants and the effect of glycerol incorporation. Determination of molecular area of each surfactant on the solution surface revealed that the structures of the surface monolayers are remarkably consistent when water is placed by the solid PVA. Incorporation of glycerol caused a decrease of molecular area for DDAO and increase in molecular area for DTAO both in solution and in PVA. This suggests that the head group interactions, which normally limit the minimum area per adsorbed molecule, are modified by the length of the alkyl tail.

This aims to establish design rules for the influence of complex polymer matrices on the surface properties of small molecules. Here, we consider the dependence of the surface behaviour of some model additives on polymer matrix hydrophobicity. With stoichiometric control over hydrolysis, we generate systematic changes in matrix chemistry from non-polar, hydrophobic PVAc to its hydrolysed and hydrophilic analogue, PVA. With the changing degree of hydrolysis (DH), the behaviour of additives can be switched in terms of compatibility and surface activity. Sorbitol, a polar sugar-alcohol of inherently high surface energy, blooms to the surface of PVAc, forming patchy domains on surfaces. With the increasing DH of the polymer matrix, its surface segregation decreases to the point where sorbitol acts as a homogeneously distributed plasticiser in PVA. Conversely, and despite its low surface energy, octanoic acid (OA) surprisingly causes the increased wettability of PVAc. We attribute these observations to the high compatibility of OA with PVAc and its ability to reorient upon exposure to water, presenting a hydrophilic COOH-rich surface. The surfactant sodium dodecyl sulfate (SDS) does not show such a clear dependence on the matrix and formed wetting layers over a wide range of DH. Interestingly, SDS appears to be most compatible with PVAc at intermediate DH, which is consistent with the amphiphilic nature of both species under these conditions. Thus, we show that the prediction of the segregation is not simple and depends on multiple factors including hydrophobicity, compatibility, blockiness, surface energy, and the mobility of the components.

Between 2003 and 2015, there were 5343 outbreak tornadoes and 9389 isolated tornadoes reported in the continental United States. Here, the near-storm environmental parameter-space distributions of these two categories are compared via kernel density estimation, and the seasonal, diurnal, and geographical features of near-storm environments of these two sets of events are compared via self-organizing maps (SOMs). Outbreak tornadoes in a given geographical region tend to be characterized by greater 0–1-km storm-relative helicity and 0–6-km vector shear magnitude than isolated tornadoes in the same geographical region and also have considerably higher tornado warning-based probability of detection (POD) than isolated tornadoes. A SOM of isolated tornadoes highlights that isolated tornadoes with higher POD also tend to feature higher values of the significant tornado parameter (STP), regardless of the specific shape of the area of STP. For a SOM of outbreak tornadoes, when two outbreak environments with similarly high magnitudes but different patterns of STP are compared, the difference is primarily geographical, with one environment dominated by Great Plains and Midwest outbreaks and another dominated by outbreaks in the southeastern United States. Two specific tornado outbreaks are featured, and the events are placed into their climatological context with more nuance than typical single proximity sounding-based approaches would allow.

This study presents the development and testing of two statistical models that simulate tornado potential and wind speed. This study reports on the first-ever development of two multiple regression–based models to assist warning forecasters in statistically simulating tornado probability and tornado wind speed in a diagnostic manner based on radar-observed tornado signature attributes and one environmental parameter. Based on a robust database, the radar-based storm-scale circulation attributes (strength, height above ground, clarity) combine with the effective-layer significant tornado parameter to establish a tornado probability. The second model adds the categorical presence (absence) of a tornadic debris signature to derive the tornado wind speed. While the fits of these models are considered somewhat modest, their regression coefficients generally offer physical consistency, based on findings from previous research. Furthermore, simulating these models on an independent dataset and other past cases featured in previous research reveals encouraging signals for accurately identifying higher potential for tornadoes. This statistical application using large-sample-size datasets can serve as a first step to streamlining the process of reproducibly quantifying tornado threats by service-providing organizations in a diagnostic manner, encouraging consistency in messaging scientifically sound information for the protection of life and property.

Background Congenital hyperinsulinism (CHI) is a rare, genetic disease which causes persistent hypoglycaemia, typically in new-borns. Patients with the diffuse disease variant often require near-total surgical removal of the pancreas, causing insulin-dependent diabetes mellitus (IDDM). The CHI economic burden is currently unknown. This study aimed to estimate the annual cost of illness (COI) of CHI patients in the UK from a service provider perspective (National Health Service, NHS and Personal Social Services), and to explore cost distribution within the patient population. Methods The model was based on standard practice of two CHI centres of excellence. Model inputs were informed by a pragmatic literature review, NHS Reference Costs (2015–2016) and the British National Formulary (2017). Only direct costs to the NHS and Personal Social Services were considered. A prevalence-based approach was used and annual costs incurred at all ages were calculated. A deterministic sensitivity analysis (DSA; run at 10%) identified major cost drivers. Results The COI of CHI patients to the NHS was £3,408,398.59 annually and average cost per patient was £2124.95. Cost distribution was skewed among CHI patients, with 5.9% of patients (95 patients in their first year of life) contributing to 61.8% (£2,105,491.07) of total costs. DSA results identified lack of response to first-line therapy and IDDM development post surgery (and associated healthcare costs) as major cost drivers. Conclusions Despite its rare disease status, estimated annual costs of CHI to the NHS were substantial. Development and management of post-surgical IDDM as a major cost driver highlights the need for effective treatments to mitigate such consequences and costs. Electronic supplementary material The online version of this article (10.1186/s13023-018-0867-6) contains supplementary material, which is available to authorized users.

During the 2014–15 academic year, the National Oceanic and Atmospheric Administration (NOAA) National Weather Service Storm Prediction Center (SPC) and the University of Oklahoma (OU) School of Meteorology jointly created the first SPC-led course at OU focused on connecting traditional theory taught in the academic curriculum with operational meteorology. This class, “Applications of Meteorological Theory to Severe-Thunderstorm Forecasting,” began in 2015. From 2015 through 2017, this spring–semester course has engaged 56 students in theoretical skills and related hands-on weather analysis and forecasting applications, taught by over a dozen meteorologists from the SPC, the NOAA National Severe Storms Laboratory, and the NOAA National Weather Service Forecast Offices. Following introductory material, which addresses many theoretical principles relevant to operational meteorology, numerous presentations and hands-on activities focused on instructors’ areas of expertise are provided to students. Topics include the following: storm-induced perturbation pressure gradients and their enhancement to supercells, tornadogenesis, tropical cyclone tornadoes, severe wind forecasting, surface and upper-air analyses and their interpretation, and forecast decision-making. This collaborative approach has strengthened bonds between meteorologists in operations, research, and academia, while introducing OU meteorology students to the vast array of severe thunderstorm forecast challenges, state-of-the-art operational and research tools, communication of high-impact weather information, and teamwork skills. The methods of collaborative instruction and experiential education have been found to strengthen both operational–academic relationships and students’ appreciation of the intricacies of severe thunderstorm forecasting, as detailed in this article.

Mussel-inspired, catechol-containing monomers are being increasingly utilised to design versatile, adhesive, functional copolymers. This work reports the synthesis and detailed characterisation of a novel terpolymer comprising dopamine methacrylamide (DMA), in order to produce surface coatings capable of acting as biosensors for, e.g., toxins. DMA is copolymerised with 2-hydroxyethyl methacrylate (HEMA) and glycidyl methacrylate (GMA) using free radical polymerisation. The copolymers are subsequently deposited as a thin film using spin-coating. It is demonstrated that a terpolymer comprising HEMA, GMA and DMA can immobilise an IgG antibody on the film surface. The terpolymer therefore has the potential to be used as a coating in biosensing devices. It is also demonstrated that the presence of DMA impacts the copolymer properties. In-situ ellipsometry is used to confirm the important role of the catechol group on copolymer adhesion and significant desorption was observed in the absence of DMA.

With a variety of programming languages and data formats available, widespread adoption of computing standards by the atmospheric science community is often difficult to achieve. The Sounding and Hodograph Analysis and Research Program in Python (SHARPpy) is an open-source, cross-platform, upper-air sounding analysis and visualization package. SHARPpy is based on the National Oceanic and Atmospheric Administration/Storm Prediction Center’s (NOAA/SPC) in-house analysis package, SHARP, and is the result of a collaborative effort between forecasters at the SPC and students at the University of Oklahoma’s School of Meteorology. The major aim of SHARPpy is to provide a consistent framework for sounding analysis that is available to all. Nearly all routines are written to be as consistent as possible with the methods researched, tested, and developed in the SPC, which sets this package apart from other sounding analysis tools. SHARPpy was initially demonstrated and released to the atmospheric community at the American Meteorological Society (AMS) Annual Meeting in 2012, and an updated and greatly expanded version was released at the AMS Annual Meeting in 2015. Since this release, SHARPpy has been adopted by a variety of operational and research meteorologists across the world. In addition, SHARPpy’s open-source nature enables collaborations between other developers, resulting in major additions to the program.

Previous work with observations from the NEXRAD (WSR-88D) network in the United States has shown that the probability of damage from a tornado, as represented by EF-scale ratings, increases as low-level rotational velocity increases. This work expands on previous studies by including reported tornadoes from 2014 to 2015, as well as a robust sample of nontornadic severe thunderstorms [≥1-in.- (2.54 cm) diameter hail, thunderstorm wind gusts ≥ 50 kt (25 m s−1), or reported wind damage] with low-level cyclonic rotation. The addition of the nontornadic sample allows the computation of tornado damage rating probabilities across a spectrum of organized severe thunderstorms represented by right-moving supercells and quasi-linear convective systems. Dual-polarization variables are used to ensure proper use of velocity data in the identification of tornadic and nontornadic cases. Tornado damage rating probabilities increase as low-level rotational velocity Vrot increases and circulation diameter decreases. The influence of height above radar level (or range from radar) is less obvious, with a muted tendency for tornado damage rating probabilities to increase as rotation (of the same Vrot magnitude) is observed closer to the ground. Consistent with previous work on gate-to-gate shear signatures such as the tornadic vortex signature, easily identifiable rotation poses a greater tornado risk compared to more nebulous areas of cyclonic azimuthal shear. Additionally, tornado probability distributions vary substantially (for similar sample sizes) when comparing the southeast United States, which has a high density of damage indicators, to the Great Plains, where damage indicators are more sparse.

In this work, self-organizing maps (SOMs) are used to investigate patterns of favorable near-storm environmental parameters in a 13-yr climatology of 14 814 tornado events and 44 961 tornado warnings across the continental United States. Establishing nine statistically distinct clusters of spatial distributions of the significant tornado parameter (STP) in the 480 km × 480 km region surrounding each tornado event or warning allows for the examination of each cluster in isolation. For tornado events, distinct patterns are associated more with particular times of day, geographical locations, and times of year. For example, the archetypal springtime dryline setup in the Great Plains emerges readily from the data. While high values of STP tend to correspond to relatively high probabilities of detection (PODs) and relatively low false alarm ratios (FARs), the majority of tornado events occur within a pattern of uniformly lower STP, with relatively high FAR and low POD. Overall, the two-dimensional plots produced by the SOM approach provide an intuitive way of creating nuanced climatologies of tornadic near-storm environments.

Compatibility between oligomers and polymers was systematically assessed using differential scanning calorimetry (DSC) and was correlated with similarity in saturation and solubility parameter. These measurements enabled validation of detailed volume of mixing calculations using Statistical Association Fluid Theory (SAFT-γ Mie) and molecular dynamics (MD) simulations, which can be used to predict behaviour beyond the experimentally accessible conditions. These simulations confirmed that squalane is somewhat more compatible with poly(isoprene), "PI" than poly(butadiene), "PB", and further enabled prediction of the temperature dependence of compatibility. Surface and interfacial segregation of a series of deuterated oligomers was quantified in rubbery polymer films: PI, PB and hydrogenated poly(isoprene) "hPI". A striking correlation was established between surface wetting transition and mixtures of low compatibility, such as oligo-dIB in PB or PI. Segregation was quantified normal to the surface by ion beam analysis and neutron reflectometry and in some cases lateral segregation was observable by AFM. While surface segregation is driven by disparity in molecular weight in highly compatible systems this trend reverses as critical point is approached, and surface segregation increases with increasing oligomer molecular weight.

In this study, a 13-yr climatology of tornado event and warning environments, including metrics of tornado intensity and storm morphology, is investigated with particular focus on the environments of tornadoes associated with quasi-linear convective systems and right-moving supercells. The regions of the environmental parameter space having poor warning performance in various geographical locations, as well as during different times of the day and year, are highlighted. Kernel density estimations of the tornado report and warning environments are produced for two parameter spaces: mixed-layer convective available potential energy (MLCAPE) versus 0–6-km vector shear magnitude (SHR6), and mixed-layer lifting condensation level (MLLCL) versus 0–1-km storm-relative helicity (SRH1). The warning performance is best in environments characteristic of severe convection (i.e., environments featuring large values of MLCAPE and SHR6). For tornadoes occurring during the early evening transition period, MLCAPE is maximized, MLLCL heights decrease, SHR6 and SRH1 increase, tornadoes rated as 2 or greater on the enhanced Fujita scale (EF2+) are most common, the probability of detection is relatively high, and false alarm ratios are relatively low. Overall, the parameter-space distributions of warnings and events are similar; at least in a broad sense, there is no systematic problem with forecasting that explains the high overall false alarm ratio, which instead seems to stem from the inability to know which storms in a given environment will be tornadic.