Abstract

The scientific community has long acknowledged the importance of high-temporal-resolution radar observations to advance science research and improve high-impact weather prediction. Development of innovative rapid-scan radar technologies over the past two decades has enabled radar volume scans of 10–60 s compared to 3–5 min with traditional parabolic dish research radars and the WSR-88D radar network. This review examines the impact of rapid-scan radar technology, defined as radars collecting volume scans in 1 min or less, on atmospheric science research spanning different subdisciplines and evaluates the strengths and weaknesses of the use of rapid-scan radars. In particular, a significant body of literature has accumulated for tornado and severe thunderstorm research and forecasting applications, in addition to a growing number of studies of convection. Convection research has benefited substantially from more synchronous vertical views, but could benefit more substantially by leveraging multi-Doppler wind retrievals and complementary in situ and remote sensors. In addition, several years of forecast evaluation studies are synthesized from radar testbed experiments, and the benefits of assimilating rapid-scan radar observations are analyzed. Although the current body of literature reflects the considerable utility of rapid-scan radars to science research, a weakness is that limited advancements in understanding of the physical mechanisms behind observed features have been enabled. There is considerable opportunity to bridge the gap in physical understanding with the current technology using coordinated efforts to include rapid-scan radars in field campaigns and expanding the breadth of meteorological phenomena studied.

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.

Abstract

Temperature and wind data from a rural micronet and nearby site of the Oklahoma Mesonet are analyzed to study the frequency, strength, and formation processes of cold-pool events in a region with gentle terrain. Spatial analyses were performed for a 2-yr-long temperature record from 26 temperature/humidity surface stations, deployed across a 120 m × 320 m micronet located in a region of gently sloped terrain with maximum elevation changes of ∼25 m. Cold pools frequently formed at the base of a gentle slope in a small depression of only ∼6-m depth that is also sheltered by trees. The strength of each cold-pool event was classified according to a cold-pool index based on average nocturnal temperature perturbations within the cold-pool region. Wind data collected with sonic anemometers on a 15-m-tall tower at the micronet for a period of three months (spring 2005) suggest that flow sheltering by vegetation plays an important role in the cold-pool formation. The wind data also show signatures of katabatic flow for about 50% of the strong cold-pool events. However, a heat budget analysis for these nights suggested that the katabatic flows were associated with warm-air advection along the slope and that if katabatic jets had penetrated the cold pool, they would have produced substantial warming in the region of the cold pool. Since such warming was not observed, it is concluded that the katabatic jets did not actually penetrate the cold pool but likely flowed over it. An analysis of Richardson numbers demonstrates that cold-pool formation frequently occurs under strongly stable conditions that tend to suppress vertical turbulent mixing in the surface layer. Observations that significant temperature changes can occur even with elevation changes on the order of 6 m have important implications in agriculture as well as in data assimilation.

Abstract

Downbursts are rapidly evolving meteorological phenomena with numerous vertically oriented precursor signatures, and the temporal resolution and vertical sampling of the current NEXRAD system are too coarse to observe their evolution and precursor signatures properly. A future all-digital polarimetric phased-array weather radar (PAR) should be able to improve both temporal resolution and spatial sampling of the atmosphere to provide better observations of rapidly evolving hazards such as downbursts. Previous work has been focused on understanding the trade-offs associated with using various scanning techniques on stationary PARs; however, a rotating, polarimetric PAR (RPAR) is a more feasible and cost-effective candidate. Thus, understanding the trade-offs associated with using various scanning techniques on an RPAR is vital in learning how to best observe downbursts with such a system. This work develops a framework for analyzing the trade-offs associated with different scanning strategies in the observation of downbursts and their precursor signatures. A proof-of-concept analysis—which uses a Cloud Model 1 (CM1)-simulated downburst-producing thunderstorm—is also performed with both conventional and imaging scanning strategies in an adaptive scanning framework to show the potential value and feasibility of the framework. Preliminary results from the proof-of-concept analysis indicate that there is indeed a limit to the benefits of imaging as an update time speedup method. As imaging is used to achieve larger speedup factors, corresponding data degradation begins to hinder the observations of various precursor signatures.

Abstract

Polarimetric weather radars are capable of detecting tornadic debris signatures (TDSs), which result from debris being lofted to the level of the radar beam and can be modulated by centrifuging and debris fallout. TDSs have been used in promising applications, such as enhanced tornado detection, improved warning and assessment of a potential tornado threat, and estimating tornado damage potential and intensity. Regions with negative differential reflectivity have been found in TDS observations but a physical explanation is yet to be determined. Some hypotheses suggest a common alignment of debris or non-Rayleigh scattering to be the cause. However, because it is inherently difficult and extremely dangerous to verify this, a simulated environment can aid in this context to reveal information that would otherwise be impossible to retrieve in practice. Under the simulation environment, the true construct of the debris is known, wherefrom the bulk distributions of position and orientation data can be extracted for statistical analysis. The primary focus of this work is to investigate the cause of nonzero mean values of in TDSs with simulated data from SimRadar, which is a polarimetric radar time series simulator developed for tornadic debris studies. The 6-degrees-of-freedom (DOF) model shows that for both small and large platelike debris, the debris face tends to have some common degree of alignment normal to the wind direction, which may be a plausible cause for the occurrence of negative in real polarimetric radar observations. Potential explanations for other hypotheses regarding tornado and debris dynamics are also briefly discussed.

Abstract

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.

Abstract

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 (Φ_DP) 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.

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.

Abstract

Phased-array radar (PAR) technology can potentially provide high-quality clear-air radial velocity observations at a high spatiotemporal resolution, usually ∼1 min or less. These observations are hypothesized to partially fill the gaps in current operational observing systems with relatively coarse-resolution surface mesonet observations and the lack of high-resolution upper-air observations especially in planetary boundary layer. In this study, observing system simulation experiments are conducted to investigate the potential value of assimilating PAR observations of clear-air radial velocity to improve the forecast of convection initiation (CI) along small-scale boundary layer convergence zones. Both surface-based and elevated CIs driven by meso-γ-scale boundary layer convergence are tested. An ensemble Kalman filter method is used to assimilate synthetic surface mesonet observations and PAR clear-air radial velocity observations. Results show that assimilating only surface mesonet observations fails to predict either surface-based or elevated CI processes. Assimilating clear-air radial velocity observations in addition to surface mesonet observations can capture both surface-based and elevated CI processes successfully. Such an improvement benefits from the better analyses of boundary layer convergence, resulting from the assimilation of clear-air radial velocity observations. Additional improvement is observed with more frequent assimilation. Assimilating clear-air radial velocity observations only from the one radar results in analysis biases of cross-beam winds and CI location biases, and assimilating additional radial velocity observations from the second radar at an appropriate position can reduce these biases while sacrificing the CI timing. These results suggest the potential of assimilating clear-air radial velocity observations from PAR to improve the forecast of CI processes along boundary layer convergence zones.

Abstract

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.