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David J. Bodine and Kristen L. Rasmussen

Abstract

This study examines organizational changes and periods of rapid forward propagation in an MCS on 6 July 2015 in South Dakota. The MCS case was the focus of a Plains Elevated Convection at Night (PECAN) IOP. Data from the Sioux Falls WSR-88D and a high-resolution WRF simulation are analyzed to examine two periods of rapid forward propagation (or surges) and organizational changes. During the first surge (surge A), the northern portion of the convective line propagates eastward faster than the southern portion, and the northern portion of the leading line transitions from a single convective core to a multicellular structure as it merges with convection initiation. Radar reflectivity factor Z and graupel concentrations decrease above the melting layer, while at lower altitudes Z increases. The MCS cold pool also intensifies and deepens beneath an expanded region of high rainwater content and subsaturated air. Throughout surge A, a mesoscale circulation with strong rear-to-front near-surface flow and front-to-rear midlevel flow is also evident. By the end of surge A, the leading edge of the MCS cold pool is beneath developing convection initiation ahead of the original convective line while the original convective updraft weakened and moved rearward. This MCS evolution is similar to discrete propagation events discussed in past studies, except with new convection developing along an intersecting convective band. During surge B, the MCS transitions from a multicellular structure to a single, intense updraft. Smaller microphysical and thermodynamic changes are observed within the MCS during surge B compared to surge A, and the mesoscale circulation continues to develop.

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Andrew Mahre, Tian-You Yu, and David J. Bodine

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As the existing NEXRAD network nears the end of its life cycle, intense study and planning are underway to design a viable replacement system. Ideally, such a system would offer improved temporal resolution compared to NEXRAD, without a loss in data quality. In this study, scan speedup techniques—such as beam multiplexing (BMX) and radar imaging—are tested to assess their viability in obtaining high-quality rapid updates for a simulated long-range weather radar. The results of this study—which uses a Weather Research and Forecasting (WRF) Model–simulated supercell case—show that BMX generally improves data quality for a given scan time or can provide a speedup factor of 1.69–2.85 compared to NEXRAD while maintaining the same level of data quality. Additionally, radar imaging is shown to improve data quality and/or decrease scan time when selectively used; however, deleterious effects are observed when imaging is used in regions with sharp reflectivity gradients parallel to the beam spoiling direction. Consideration must be given to the subsequent loss of sensitivity and beam broadening. Finally, imaging is shown to have an effect on the radar-derived mesocyclone strength (ΔV) of a simulated supercell. Because BMX and radar imaging are most easily achieved with an all-digital phased array radar (PAR), these results make a strong argument for the use of all-digital PAR for high-resolution weather observations. It is believed that the results from this study can inform decisions about possible scanning strategies and design of a NEXRAD replacement system for high-resolution weather radar data.

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Casey B. Griffin, David J. Bodine, and Robert D. Palmer

Abstract

Tornadoes are capable of lofting large pieces of debris that present irregular shapes, near-random orientations, and a wide range of dielectric constants to polarimetric radars. The unique polarimetric signature associated with lofted debris is called the tornadic debris signature (TDS). While ties between TDS characteristics and tornado- and storm-scale kinematic processes have been speculated upon or investigated using photogrammetry and single-Doppler analyses, little work has been done to document the three-dimensional wind field associated with the TDS.

Data collected by the Oklahoma City, Oklahoma (KTLX), and Norman, Oklahoma (KOUN), WSR-88D S-band radars as well as the University of Oklahoma’s (OU) Advanced Radar Research Center’s Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) C-band radar are used to construct single- and dual-Doppler analyses of a tornadic supercell that produced an EF4 tornado near the towns of Moore and Choctaw, Oklahoma, on 10 May 2010. This study documents the spatial distribution of polarimetric radar variables and how each variable relates to kinematic fields such as vertical velocity and vertical vorticity. Special consideration is given to polarimetric signatures associated with subvortices within the tornado. An observation of negative differential reflectivity () at the periphery of tornado subvortices is presented and discussed. Finally, dual-Doppler wind retrievals are compared to single-Doppler axisymmetric wind fields to illustrate the merits of each method.

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David J. Bodine, Robert D. Palmer, and Guifu Zhang

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Statistical properties of tornado debris signatures (TDSs) are investigated using S- and C-band polarimetric radar data with comparisons to damage surveys and satellite imagery. Close proximity of the radars to the 10 May 2010 Moore–Oklahoma City, Oklahoma, tornado that was rated as a 4 on the enhanced Fujita scale (EF4) provides a large number of resolution volumes, and good temporal and spatial matching for dual-wavelength comparisons. These comparisons reveal that S-band TDSs exhibit a higher radar reflectivity factor (Z HH) and copolar cross-correlation coefficient (ρ hv) than do C-band TDSs. Higher S-band ρ hv may result from a smaller ratio of non-Rayleigh scatterers to total scatterers due to the smaller electrical sizes of debris and, consequently, reduced resonance effects. A negative Z DR signature is observed at 350 m AGL at both the S and C bands as the tornado passes over a vegetated area near a large body of water. Another interesting signature is a positive (negative) shift in propagation differential phase (ΦDP) at S band (C band), which could result from increased phase folding at C band. With increasing height above 350 m AGL, the S- and C-band Z HH decreases and ρ hv increases, indicating a decrease in debris size. To investigate relationships between polarimetric variables and tornado wind fields, range profiles of radial and tangential wind speeds are obtained using two radars. Velocity profiles reveal radial divergence within vortex core flow through 700 m AGL collocated with the TDS. Formation of a weak-echo hole and higher ρ hv in the vortex center aloft suggests debris centrifuging, outward motion of scatterers due to radial divergence (i.e., two-cell vortex flow), or both.

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Casey B. Griffin, David J. Bodine, and Robert Palmer

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This study utilizes data collected by the University of Oklahoma Advanced Radar Research Center’s Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) C-band radar as well as the federal KTLX and KOUN WSR-88D S-band radars to study a supercell that simultaneously produced a long-track EF-4 tornado and an EF-2 landspout tornado (EF indicates the enhanced Fujita scale) near Norman, Oklahoma, on 10 May 2010. Contrasting polarimetric characteristics of two tornadoes over similar land cover but with different intensities are documented. Also, the storm-scale sedimentation of debris within the supercell is investigated, which includes observations of rotation and elongation of a tornadic debris signature with height. A dual-wavelength comparison of debris at S and C bands is performed. These analyses indicate that lofted debris within the tornado was larger than debris located outside the damage path of the tornado and that debris size outside the tornado increased with height, likely as the result of centrifuging. Profiles of polarimetric variables were observed to become more vertically homogeneous with time.

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David J. Bodine, Robert D. Palmer, Takashi Maruyama, Caleb J. Fulton, Ye Zhu, and Boon Leng Cheong

Abstract

To obtain accurate radar-measured wind measurements in tornadoes, differences between air and Doppler velocities must be corrected. These differences can cause large errors in radar estimates of maximum tangential wind speeds, and large errors in single-Doppler retrievals of radial and vertical velocities. Since larger scatterers (e.g., debris) exhibit larger differences from air velocities compared to small scatterers (e.g., raindrops), the dominant scatterer type affecting radar measurements is examined. In this study, radar variables are simulated for common weather radar frequencies using debris and raindrop trajectories computed with a large-eddy simulation model and two electromagnetic scattering models. These simulations include a large range of raindrop and wood board sizes and concentrations, and reveal the significant frequency dependence of the equivalent reflectivity factor and Doppler velocity. At S band, dominant scatterers are wood boards, except when wood board concentrations are very low. In contrast, raindrops are the dominant scatterers at Ka and W bands even when large concentrations of wood boards are present, except for low raindrop concentrations. Dual-wavelength velocity differences exhibit high correlation with air and Doppler velocity differences for most cases, which may enable direct measurements of scatterer-induced Doppler velocity bias in tornadoes. Moreover, dual-wavelength ratios are shown to exhibit strong correlations with dominant scatterer size, except when Rayleigh scatterers are dominant. Finally, vertical velocity retrievals are shown to exhibit lower errors at high frequencies, and large errors remain at centimeter wavelengths even after debris centrifuging corrections are applied in cases with high debris concentration.

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David J. Bodine, Takashi Maruyama, Robert D. Palmer, Caleb J. Fulton, Howard B. Bluestein, and David C. Lewellen

Abstract

Past numerical simulation studies found that debris loading from sand-sized particles may substantially affect tornado dynamics, causing reductions in near-surface wind speeds up to 50%. To further examine debris loading effects, simulations are performed using a large-eddy simulation model with a two-way drag force coupling between air and sand. Simulations encompass a large range of surface debris fluxes that cause negligible to substantial impact on tornado dynamics for a high-swirl tornado vortex simulation.

Simulations are considered for a specific case with a single vortex flow type (swirl ratio, intensity, and translation velocity) and a fixed set of debris and aerodynamic parameters. Thus, it is stressed that these findings apply to the specific flow and debris parameters herein and would likely vary for different flows or debris parameters. For this specific case, initial surface debris fluxes are varied over a factor of 16 384, and debris cloud mass varies by only 42% of this range because a negative feedback reduces near-surface horizontal velocities. Debris loading effects on the axisymmetric mean flow are evident when maximum debris loading exceeds 0.1 kg kg−1, but instantaneous maximum wind speed and TKE exhibit small changes at smaller debris loadings (greater than 0.01 kg kg−1). Initially, wind speeds are reduced in a shallow, near-surface layer, but the magnitude and depth of these changes increases with higher debris loading. At high debris loading, near-surface horizontal wind speeds are reduced by 30%–60% in the lowest 10 m AGL. In moderate and high debris loading scenarios, the number and intensity of subvortices also decrease close to the surface.

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Alan Shapiro, Joshua G. Gebauer, Nathan A. Dahl, David J. Bodine, Andrew Mahre, and Corey K. Potvin

Abstract

Techniques to mitigate analysis errors arising from the nonsimultaneity of data collections typically use advection-correction procedures based on the hypothesis (frozen turbulence) that the analyzed field can be represented as a pattern of unchanging form in horizontal translation. It is more difficult to advection correct the radial velocity than the reflectivity because even if the vector velocity field satisfies this hypothesis, its radial component does not—but that component does satisfy a second-derivative condition. We treat the advection correction of the radial velocity (υ r) as a variational problem in which errors in that second-derivative condition are minimized subject to smoothness constraints on spatially variable pattern-translation components (U, V). The Euler–Lagrange equations are derived, and an iterative trajectory-based solution is developed in which U, V, and υ r are analyzed together. The analysis code is first verified using analytical data, and then tested using Atmospheric Imaging Radar (AIR) data from a band of heavy rainfall on 4 September 2018 near El Reno, Oklahoma, and a decaying tornado on 27 May 2015 near Canadian, Texas. In both cases, the analyzed υ r field has smaller root-mean-square errors and larger correlation coefficients than in analyses based on persistence, linear time interpolation, or advection correction using constant U and V. As some experimentation is needed to obtain appropriate parameter values, the procedure is more suitable for non-real-time applications than use in an operational setting. In particular, the degree of spatial variability in U and V, and the associated errors in the analyzed υ r field are strongly dependent on a smoothness parameter.

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Martin A. Satrio, David J. Bodine, Anthony E. Reinhart, Takashi Maruyama, and Franklin T. Lombardo

Abstract

A simulated vortex within a large-eddy simulation is subjected to various surface terrain, implemented through the immersed boundary method, to analyze the effects of complex topography on vortex behavior. Thirty simulations, including a control with zero-height terrain, are grouped into four categories—2D sinusoidal hills, 3D hills, valleys, and ridges—with slight modifications within each category. A medium-swirl-ratio vortex is translated over shallow terrain, which is modest in size relative to the vortex core diameter and with no explicitly defined surface roughness. While domain size restricts results to the very near-field effects of terrain, vortex–terrain interaction yields notable results. Terrain influences act to increase the variability of the near-surface vortex, including a notable leftward (rightward) deflection, acceleration (deceleration), and an expansion (a contraction) of the vortex as it ascends (descends) the terrain owing to changes in the corner flow swirl ratio. Additionally, 10-m track analyses show stronger horizontal wind speeds are found 1) on upslope terrain, resulting from transient subvortices that are more intense compared to the control simulation, and 2) in between adjacent hills simultaneous with strong pressure perturbations that descend from aloft. Composite statistics confirm that the region in between adjacent hills has the strongest horizontal wind speeds, while upward motions are more intense during ascent. Overall, valley (ridge) simulations have the largest horizontal (vertically upward) wind speeds. Last, horizontal and vertical wind speeds are shown to be affected by other terrain properties such as slope steepness and two-dimensionality of the terrain.

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David J. Bodine, Matthew R. Kumjian, Robert D. Palmer, Pamela L. Heinselman, and Alexander V. Ryzhkov

Abstract

This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile Z HH, TDS height, and volume, as well as lower minimum values of 10th percentile ρ HV and Z DR, are observed. Maxima in spatial TDS parameters are observed after periods of severe, widespread tornado damage for violent tornadoes. This paper discusses how forecasters could use TDS parameters to obtain near-real-time information about tornado damage severity and spatial extent.

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