No abstract

Proximity sounding studies typically seek to optimize several trade-offs that involve somewhat arbitrary definitions of how to define a ''proximity sounding.'' More restrictive proximity criteria, which presumably produce results that are more characteristic of the near-storm environment, typically result in smaller sample sizes that can reduce the statistical significance of the results. Conversely, the use of broad proximity criteria will typically increase the sample size and the apparent robustness of the statistical analysis, but the sounding data may not necessarily be representative of near-storm environments, given the presence of mesoscale variability in the atmosphere. Previous investigations have used a wide range of spatial and temporal proximity criteria to analyze severe storm environments. However, the sensitivity of storm environment climatologies to the proximity definition has not yet been rigorously examined.In this study, a very large set (;1200) of proximity soundings associated with significant tornado reports is used to generate distributions of several parameters typically used to characterize severe weather environments. Statistical tests are used to assess the sensitivity of the parameter distributions to the proximity criteria.The results indicate that while soundings collected too far in space and time from significant tornadoes tend to be more representative of the larger-scale environment than of the storm environment, soundings collected too close to the tornado also tend to be less representative due to the convective feedback process. The storm environment itself is thus optimally sampled at an intermediate spatiotemporal range referred to here as the Goldilocks zone. Implications of these results for future proximity sounding studies are discussed.

On 29–30 May 2012, the Deep Convective Clouds and Chemistry experiment observed a supercell thunderstorm on the southern end of a broken line of severe storms in Oklahoma. This study focuses on an approximately 70 min period during which three mobile Doppler radars operated and a balloon‐borne electric field meter, radiosonde, and particle imager flew through the storm. An overview of the relationships among flash rates, very high frequency (VHF) source densities, and Doppler‐radar‐derived storm parameters is presented. Furthermore, the evolution of the flash distribution relative to the midlevel storm's kinematics and microphysics is examined at two times during a period of rapid storm intensification. The timing of increases in VHF counts in the 8–10 km above ground level (agl) layer, which contained the largest VHF source counts, is similar to the timing of increases in updraft mass flux, in updraft volume, and in graupel volume at approximately 5–9 km agl. Although some increases in VHF source counts had little or no corresponding increase in one or more of the other storm parameters, at least one other parameter had an increase near the time of every VHF increase, a pattern which suggests a common dependence on updraft pulses, as expected from the noninductive graupel‐ice electrification mechanism. A classic bounded weak lightning region was observed initially during storm intensification, but late in the period it appeared to be due to a wake in the flow around the updraft, rather than due to a precipitation cascade around the updraft core as is usually observed.

The utility of the anelastic vertical vorticity equation in a weak-constraint (least squares error) variational dual-Doppler wind analysis procedure is explored. The analysis winds are obtained by minimizing a cost function accounting for the discrepancies between observed and analyzed radial winds, errors in the mass conservation equation, errors in the anelastic vertical vorticity equation, and spatial smoothness constraints. By using Taylor’s frozen-turbulence hypothesis to shift analysis winds to observation points, discrepancies between radially projected analysis winds and radial wind observations can be calculated at the actual times and locations the data are acquired. The frozen-turbulence hypothesis is also used to evaluate the local derivative term in the vorticity equation. Tests of the analysis procedure are performed with analytical pseudo-observations of an array of translating and temporally decaying counterrotating updrafts and downdrafts generated from a Beltrami flow solution of the Navier–Stokes equations. The experiments explore the value added to the analysis by the vorticity equation constraint in the common scenario of substantial missing low-level data (radial wind observations at heights beneath 1.5 km are withheld from the analysis). Experiments focus on the sensitivity of the most sensitive analysis variable—the vertical velocity component—to values of the weighting coefficients, volume scan period, number of volume scans, and errors in the estimated frozen-turbulence pattern-translation components. Although the vorticity equation constraint is found to add value to many of these analyses, the analysis can become significantly degraded if estimates of the pattern-translation components are largely in error or if the frozen-turbulence hypothesis itself breaks down. However, tests also suggest that these negative impacts can be mitigated if data are available in a rapid-scan mode.

Dual-Doppler wind retrieval is an invaluable tool in the study of convective storms. However, the nature of the errors in the retrieved three-dimensional wind estimates and subsequent dynamical analyses is not precisely known, making it difficult to assign confidence to inferred storm behavior. Using an Observing System Simulation Experiment (OSSE) framework, this study characterizes these errors for a supercell thunderstorm observed at close range by two Doppler radars. Synthetic radar observations generated from a high-resolution numerical supercell simulation are input to a three-dimensional variational data assimilation (3DVAR) dualDoppler wind retrieval technique. The sensitivity of the analyzed kinematics and dynamics to the dualDoppler retrieval settings, hydrometeor fall speed parameterization errors, and radar cross-beam angle and scanning strategy is examined.Imposing the commonly adopted assumptions of spatially constant storm motion and intrinsically steady flow produces large errors at higher altitudes. On the other hand, reasonably accurate analyses are obtained at lower and middle levels, even when the majority of the storm lies outside the 308 dual-Doppler lobe. Lowlevel parcel trajectories initiated around the main updraft and rear-flank downdraft are generally qualitatively accurate, as are time series of circulation computed around material circuits. Omitting upper-level radar observations to reduce volume scan times does not substantially degrade the lower-and middle-level analyses, which implies that shallower scanning strategies should enable an improved retrieval of supercell dynamics. The results suggest that inferences about supercell behavior based on qualitative features in 3DVAR dualDoppler and subsequent dynamical retrievals may generally be reliable.

Abstract. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with those from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-meansquare differences between the two sources are of the order of 1 and 2 m s −1 , respectively, and time-height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s −1 . The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. The results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.

One of the greatest challenges to dual-Doppler retrieval of the vertical wind is the lack of low-level divergence information available to the mass conservation constraint. This study examines the impact of a vertical vorticity equation constraint on vertical velocity retrievals when radar observations are lacking near the ground. The analysis proceeds in a three-dimensional variational data assimilation (3DVAR) framework with the anelastic form of the vertical vorticity equation imposed along with traditional data, mass conservation, and smoothness constraints. The technique is tested using emulated radial wind observations of a supercell storm simulated by the Advanced Regional Prediction System (ARPS), as well as real dualDoppler observations of a supercell storm that occurred in Oklahoma on 8 May 2003. Special attention is given to procedures to evaluate the vorticity tendency term, including spatially variable advection correction and estimation of the intrinsic evolution. Volume scan times ranging from 5 min, typical of operational radar networks, down to 30 s, achievable by rapid-scan mobile radars, are considered. The vorticity constraint substantially improves the vertical velocity retrievals in our experiments, particularly for volume scan times smaller than 2 min.

Use of the three-dimensional variational data assimilation (3DVAR) framework in dual-Doppler wind analysis (DDA) offers several advantages over traditional techniques. Perhaps the most important is that the errors that result from explicit integration of the mass continuity equation in traditional methods are avoided. In this study, observing system simulation experiments (OSSEs) are used to compare supercell thunderstorm wind retrievals from a 3DVAR DDA technique and three traditional DDA methods. The 3DVAR technique produces better wind retrievals near the top of the storm than the traditional methods in the experiments. This is largely attributed to the occurrence of severe errors aloft in the traditional retrievals whether the continuity equation integration proceeds upward (due to vertically accumulating errors), downward (due to severe boundary condition errors arising from uncertainty in the horizontal divergence field aloft), or in both directions. Smaller, but statistically significant, improvement occurs near the ground using the 3DVAR method. When lack of upper-level observations prevents application of a top boundary condition in the traditional DDA framework, the 3DVAR approach produces better analyses at all levels. These results strongly suggest the 3DVAR DDA framework is generally preferable to traditional formulations.