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Recurring polarimetric radar signatures in supercells include deep and persistent differential reflectivity (ZDR) columns, hail inferred in low-level scans, and the ZDR arc signature. Prior investigations of supercell polarimetric signatures reveal positive correlations between the ZDR column depth and cross-sectional area and quantitative characteristics of the radar reflectivity field. This study expands upon prior work by examining temporal associations between supercell polarimetric radar signatures, incorporating a dataset of relatively discrete, right-moving supercells from the continental United States observed by the Weather Surveillance Radar 1988-Doppler (WSR-88D) network. Cross-correlation coefficients were calculated between the ZDR column area and depth and the base-scan hail area, ZDR arc area, and mean ZDR arc value. These correlation values were computed with a positive and negative lag time of up to 45 min. Results of the lag correlation analysis are consistent with prior observations indicative of storm cycling, including temporal associations between ZDR columns and inferred hail signatures/ZDR arcs in both tornadic and nontornadic supercells, but were most pronounced in tornadic storms.

Nonmeteorological scatter, including debris lofted by tornadoes, may be detected using the polarimetric radar variables. For the 17 months from January 2012 to May 2013, radar data were examined for each tornado reported in the domain of an operational polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). Characteristics of the tornadic debris signature (TDS) were recorded when a signature was present. Approximately 16% of all tornadoes reported inStorm Datawere associated with a debris signature, and this proportion is shown to vary regionally. Signatures were more frequently seen with tornadoes that were rated higher on the enhanced Fujita (EF) scale, with tornadoes causing higher reported total property damage, with tornadoes that were closer to the radar and thus intercepted by the beam at lower altitude, and associated with tornadoes with greater total pathlength. Tornadic debris signatures were most common in spring, when more strong tornadoes occur, and in autumn, when natural debris is more available. Debris-signature areal extent is shown to increase consistently with EF-scale rating and tornado longevity. Vertical extent of a TDS is shown to be greatest for strong, long-lived tornadoes with large radii of damaging wind. Land cover is also shown to exhibit some control over TDS characteristics—in particular, a large percentage of tornadoes with substantial track over urban land cover exhibited a TDS and do so very quickly after reported tornadogenesis, as compared with tornadoes over other land-cover classifications. TDS characteristics over grassland and cropland tended to be similar.

Values of polarimetric radar variables may vary substantially between and through tornadic debris signature (TDS) events. Tornadoes with higher intensity ratings are associated with higher average and extreme values of reflectivity factor at horizontal polarizationZ HHand lower values of copolar cross-correlation coefficientρ hv. Although values of these variables often fluctuate through reported tornado life cycles,Z HHrepeatably decreases andρ hvrepeatably increases across the volume scan immediately following reported tornado demise. Land cover has a relatively small effect on values of the polarimetric variables within TDSs, although near-radar urban TDSs may exhibit relatively highZ HHvalues. TDS areal extent is typically larger aloft than near the surface, although this trend may reverse in the most intense tornadoes. Maximum altitude to which a TDS is visible is more strongly a function of tornado intensity than of land cover or ambient shear and instability. Debris often disappears once lofted but may also be observed to spread out downstream with the storm-relative flow or to fall out along the parent storm’s northwest flank in a debris fallout signature (DFS). DFS characteristics, although variable, most commonly includeZ HHvalues of 30–35 dBZ,ρ hvvalues of 0.60–0.80, and values of differential reflectivityZ DRthat are repeatably near 0 dB.

Classic supercell storms occur in a generally well understood environment characterized by instability and vertical wind shear. Within this broadly favorable environment, large day-to-day variability in environmental parameters may lead to widely varying radar presentation of storms. Of interest here is whether specific storm structures exhibit repeatable characteristics in similar environments and whether radar presentation can be predicted with knowledge of environmental characteristics. Specifically, this paper focuses on (i) updraft characteristics inferred using differential reflectivity Z DR columns, (ii) characteristics of storm-relative inflow inferred using Z DR arcs, and (iii) areal extent and cyclicality of polarimetrically inferred hailfall at low levels. Variability of these radar features is compared among storms in similar environments and among a larger subset of storms across highly varying environments. The similarity of storms in similar and different environments is quantified, and tornadic and nontornadic storms are compared. Associations between inferred updraft, inflow, and hailfall characteristics and environmental variables are discussed. Storm features generally exhibit greater similarity among storms in similar environments than across environments, although exceptions occur. The results indicate that many radar features of classic supercells may be useful to learn about microphysical variability across environments.

Biological scatterers, consisting of birds and insects, may become trapped near the circulation center of tropical cyclones, particularly if a well-developed eyewall is present. These scatterers may be observed using weather radar, where they may appear to the radar operator as areas of light precipitation. Polarimetric radar characteristics of these scatterers, informed by additional observations of known bioscatter, include a combination of very high differential reflectivity (3–7.9 dB) and very low copolar correlation coefficient (0.3–0.8). Polarimetric radar observations of bioscatter are presented for Hurricane Irene (2011) and Hurricane Sandy (2012). In these storms, the bioscatter signature first appeared at the 0.5° elevation angle at a distance of 100–120 km from the radar. The signature appeared on successively higher tilts as the circulation center neared the radar, and its areal coverage in constant altitude plan position indicator (CAPPI) slices was primarily governed by the distribution of convection in the eye and by the timing of landfall. The highest altitude at which the signature appears may represent the inversion level within certain tropical cyclone eyes. For Hurricane Irene, inland observations of oceanic bird species support biological transport. Knowledge of the bioscatter signature has value to meteorologists monitoring tropical cyclones within the range of a polarimetric radar, possible value for estimating inversion height changes within the eyes of well-structured tropical cyclones, and value to biologists who wish to estimate the magnitude of biological transport in tropical cyclones.

Supercell thunderstorms produce a variety of hazards, including tornadoes. A supercell will often exist for some time prior to producing a tornado, while other supercells never become tornadic. In this study, a series of hypotheses is tested regarding the ability of S-band polarimetric radar fields to distinguish pretornadic from nontornadic supercell storms. Several quantified polarimetric radar metrics are examined that are related to storm inflow, updraft, and hailfall characteristics in samples of 19–30 pretornadic and 18–31 nontornadic supercells. The results indicate that pretornadic supercells are characterized by smaller hail extent and echo appendages with larger mean drop size. Additionally, differential reflectivity ZDR column size is larger and less variable in the pretornadic storms in the 25–30 min prior to initial tornadogenesis. Many of the results indicate relatively small polarimetric differences that will likely be difficult to translate to operational use. Hail extent and ZDR column size, however, may exhibit operationally useful differences between pretornadic and nontornadic supercells.

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

The dryline is an important focal point for convection initiation. Although drylines most commonly occur on the southern Great Plains, dryline passages and subsequent severe weather outbreaks have been documented in the Mississippi River valley. This study presents a 15-yr (1999–2013) climatology of these Mississippi River valley drylines and associated severe weather. Additionally, synoptic patterns are identified that may result in drylines moving atypically far eastward into the Mississippi River valley. In total, 39 Mississippi River valley drylines (hereafter referred to as MRV drylines) were identified from the North American Regional Reanalysis (NARR) dataset through the study period. Mean and anomaly synoptic composites were created for these drylines. MRV dryline events typically occur under synoptically active conditions with an amplified upper-air pattern, a 500-hPa shortwave trough to the west or northwest of the dryline, and a strong surface cyclone to the north. These boundaries are often misanalyzed or inconsistently analyzed as cold fronts, stationary fronts, or trough axes on surface maps; of the 33 cases of identified MRV drylines for which the Weather Prediction Center archived analyses were available, only 6 were correctly analyzed as drylines. Drylines moving into the Mississippi River valley often result in severe weather outbreaks in the Mississippi River valley, the Midwest, and the southeastern United States.

A family of four waterspouts was produced by a convective cell over western Lake Michigan on 12 September 2013. This storm initiated along a boundary north of a mesolow in a low-level cold-air advection regime, and developed supercell characteristics once the second waterspout was in progress. Polarimetric characteristics of the storm, and of the development of supercell character, are presented. These observations represent the first documented polarimetric radar observations of waterspout-producing convection in the Great Lakes region. Unusually high differential reflectivity values accompanied this storm and its initiating boundary. The high values along the boundary are partially explained by a high density of dragonflies. High differential reflectivity values were present through much of the storm of interest despite very low aerosol concentration at low levels in the lake-influenced air mass. Finally, this case illustrates the importance of environmental awareness on waterspout-favorable days, especially when boundaries are nearby to serve as a potential source of enhanced environmental vertical vorticity.

Seasonal bird migration occurs on large spatial scales and is influenced by many factors including weather conditions. Weather can include thunderstorms, which may force migrants to land or cause them to reroute a migration path. In this study, a sample of isolated thunderstorms was analyzed from the domains of three weather radars in the central United States to test hypotheses regarding the influence of thunderstorms on the distribution of migrants. Migrating bird density was often reduced in the wake of storms, and this wake reduction was typically more pronounced for larger, more intense and faster‐moving storms, particularly in eastern Nebraska. Wind conditions more strongly influence the distribution and density of migrating birds in fall than in spring, providing evidence that migrating birds respond to environmental signals more readily in the fall. This finding supports the concept that birds are more strongly obligated to cover distance in the spring and arrive in their breeding range on time. Wind conditions at the surface were generally more important to migrant density and distribution than wind conditions closer to flight level. Isolated nocturnal thunderstorms and the low‐level wind field may influence the distribution of migrating birds. This manuscript provides evidence that thunderstorm wakes may be associated with lower migrant density, and this effect may be increased for larger and more intense storms. Wind conditions more strongly influence migrant density and distributions in the fall than in the spring.