Corey K. Potvin

Assessing the Impacts of Proximity Sounding Criteria on the Climatology of Significant Tornado Environments

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 associat...

Use of a Vertical Vorticity Equation in Variational Dual-Doppler Wind Analysis

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 pseudoobservations 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 lowlevel 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 frozenturbulence 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.

An Improved Method for Estimating Radar Echo-Top Height

It is demonstrated that the traditional method, in widespread use on Next Generation Weather Radar (NEXRAD) and other radar systems, to compute echo-top heights results in both under- and overestimates. It is proposed that echo tops be computed by interpolating between elevation scans that bracket the echo-top threshold. The traditional and proposed techniques are evaluated using simulated radar samples of a modeled thunderstorm and by sampling a high-resolution range‐height indicator (RHI) of a real thunderstorm. It is shown that the proposed method results in smaller errors when higher-elevation scans are available.

Assessing Errors in Variational Dual-Doppler Wind Syntheses of Supercell Thunderstorms Observed by Storm-Scale Mobile Radars

AbstractDual-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) dual-Doppler wind retrieval technique. The sensitivity of the analyzed kinematics and dynamics to the dual-Doppler 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...

3DVAR versus Traditional Dual-Doppler Wind Retrievals of a Simulated Supercell Thunderstorm

AbstractUse 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, i...

Using a Low-Order Model to Detect and Characterize Tornadoes in Multiple-Doppler Radar Data

A new multiple-Doppler radar analysis technique is presented for the objective detection and characterization of tornado-like vortices. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near-environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which compose a broadscale flow), and a modified combined Rankine vortex (representing the tornado). The vortex and its environment are allowed to translate. The parameters in the low-order model are determined by minimizing a cost function that accounts for the discrepancy between the model and observed radial winds. Since vortex translation is taken into account, the cost function can be evaluated over time as well as space, and thus the observations can be used at the actual times and locations where they were acquired. The technique is first tested using analytically simulated observations whose wind field and error characteristics are systematically varied. An Advanced Regional Prediction System (ARPS) high-resolution numerical simulation of a supercell and associated tornado is then used to emulate an observation dataset. The method is tested with two virtual radars for several radarsampling strategies. Finally, the technique is applied to a dataset of real dual-Doppler observations of a tornado that struck central Oklahoma on 8 May 2003. The method shows skill in retrieving the tornado path and radar-grid-scale features of the horizontal wind field in the vicinity of the tornado. The best results are obtained using a two-step procedure in which the broadscale flow is retrieved first.

Assessing Ensemble Forecasts of Low-Level Supercell Rotation within an OSSE Framework

AbstractUnder the envisioned warn-on-forecast (WoF) paradigm, ensemble model guidance will play an increasingly critical role in the tornado warning process. While computational constraints will likely preclude explicit tornado prediction in initial WoF systems, real-time forecasts of low-level mesocyclone-scale rotation appear achievable within the next decade. Given that low-level mesocyclones are significantly more likely than higher-based mesocyclones to be tornadic, intensity and trajectory forecasts of low-level supercell rotation could provide valuable guidance to tornado warning and nowcasting operations. The efficacy of such forecasts is explored using three simulated supercells having weak, moderate, or strong low-level rotation. The results suggest early WoF systems may provide useful probabilistic 30–60-min forecasts of low-level supercell rotation, even in cases of large radar–storm distances and/or narrow cross-beam angles. Given the idealized nature of the experiments, however, they are bes...

Sensitivity of Idealized Supercell Simulations to Horizontal Grid Spacing: Implications for Warn-on-Forecast

AbstractThe Warn-on-Forecast (WoF) program aims to deploy real-time, convection-allowing, ensemble data assimilation and prediction systems to improve short-term forecasts of tornadoes, flooding, lightning, damaging wind, and large hail. Until convection-resolving (horizontal grid spacing Δx < 100 m) systems become available, however, resolution errors will limit the accuracy of ensemble model output. Improved understanding of grid spacing dependence of simulated convection is therefore needed to properly calibrate and interpret ensemble output, and to optimize trade-offs between model resolution and other computationally constrained parameters like ensemble size and forecast lead time.Toward this end, the authors examine grid spacing sensitivities of simulated supercells over Δx of 333 m–4 km. Storm environment and physics parameterization are varied among the simulations. The results suggest that 4-km grid spacing is too coarse to reliably simulate supercells, occasionally leading to premature storm dem...

Impact of a Vertical Vorticity Constraint in Variational Dual-Doppler Wind Analysis: Tests with Real and Simulated Supercell Data

AbstractOne 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 dual-Doppler 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 ...

Spatially Variable Advection Correction of Radar Data. Part II: Test Results

Abstract The spatially variable advection-correction/analysis procedure introduced in Part I is tested using analytical reflectivity blobs embedded in a solid-body vortex, and Terminal Doppler Weather Radar (TDWR) and Weather Surveillance Radar-1988 Doppler (WSR-88D) data of a tornadic supercell thunderstorm that passed over central Oklahoma on 8 May 2003. In the TDWR tests, plan position indicator (PPI) data at two volume scan times are input to the advection-correction procedure, with PPI data from a third scan time, intermediate between the two input times, that is used to validate the results. The procedure yields analyzed reflectivity fields with lower root-mean-square errors and higher correlation coefficients than those reflectivity fields that were advection corrected with any constant advection speed.