Doppler Velocity Signatures Research Articles

Tropical cyclone signatures in SAR ocean radial Doppler Velocity

Ocean surface radial Doppler Velocity (DV) signatures of Tropical Cyclones (TC) at moderate incidence angles are analyzed using a semi-empirical DV model. This model, originally named KaDOP, is based on the physics of Ka-band Doppler radar backscattering from the sea surface and represents the DV as a sum of components due to surface currents, long surface waves, Bragg scattering, and wave breaking. The latter two components were modified in this study to fit the model to C-band observations at strong winds. This modified model, referred to as a TC-DOP, requires several environmental input parameters, including TC winds and translation velocity, waves, and currents. For known winds and TC translation velocity, the surface currents are simulated using a model of the upper ocean response to TC passage. Waves are modeled using a self-similar description for the energy-containing TC-generated local wind waves and emanating swell. Given known winds, waves, and currents, the DV is calculated by the TC-DOP independently at each grid point. Calculations are performed for scanner-like observations that detect only the radial (cross-track) DV component. It is shown that at storm-strength winds and radar incidence angle, θ=45°, the main contribution to the total DV is provided by the surface current and wave breaking DV components (∼1 m s−1). The latter component has strong azimuth asymmetry and maximizes in the upwind sector. Next in magnitude is the contribution from wind waves (∼0.5 m s−1), followed by Bragg waves (∼0.2 m s−1), while the contribution from swell is less important. Comparisons of the TC-DOP calculations with the C-band Sentinel-1A SAR radial DV data show qualitatively good agreement. All observed radial velocity images in TC storm areas have a dipole-like feature similar to that predicted by the simulations, with a zero DV area roughly aligned with the cross-wind direction. The TC-DOP model prediction is found generally consistent with calculations utilizing an empirical geophysical model function (known as the CDOP). The residual differences are attributed to specific features of radar scattering mechanisms in different radar wavelength bands (Ka- vs C-band), as well as possible shortcomings of the Ka-band Modulation Transfer Function (MTF) originally derived from platform-based measurements.

Forward modelling of MHD waves in braided magnetic fields

Aims. We investigate synthetic observational signatures generated from numerical models of transverse waves propagating in complex (braided) magnetic fields. Methods. We consider two simulations with different levels of magnetic field braiding and impose periodic, transverse velocity perturbations at the lower boundary. As the waves reflect off the top boundary, a complex pattern of wave interference occurs. We applied the forward modelling code FoMo and analysed the synthetic emission data. We examined the line intensity, Doppler shifts, and kinetic energy along several line-of-sight (LOS) angles. Results. The Doppler shift perturbations clearly show the presence of the transverse (Alfvénic) waves. However, in the total intensity, and running difference, the waves are less easily observed for more complex magnetic fields and may be indistinguishable from background noise. Depending on the LOS angle, the observable signatures of the waves reflect some of the magnetic field braiding, particularly when multiple emission lines are available, although it is not possible to deduce the actual level of complexity. In the more braided simulation, signatures of phase mixing can be identified. We highlight possible ambiguities in the interpretation of the wave modes based on the synthetic emission signatures. Conclusions. Most of the observables discussed in this article behave in the manner expected, given knowledge of the evolution of the parameters in the 3D simulations. Nevertheless, some intriguing observational signatures are present. Identifying regions of magnetic field complexity is somewhat possible when waves are present; although, even then, simultaneous spectroscopic imaging from different lines is important in order to identify these locations. Care needs to be taken when interpreting intensity and Doppler velocity signatures as torsional motions, as is done in our setup. These types of signatures are a consequence of the complex nature of the magnetic field, rather than real torsional waves. Finally, we investigate the kinetic energy, which was estimated from the Doppler velocities and is highly dependent on the polarisation of the wave, the complexity of the background field, and the LOS angles.

Influence of Wind Direction on Thermodynamic Properties and Arctic Mixed‐Phase Clouds in Autumn at Utqiaġvik, Alaska

Seven years of autumnal ground‐based observations (September–November 2002–2008) at the U.S. Department of Energy Atmospheric Radiation Measurement North Slope of Alaska site have been analyzed for addressing the occurrence frequency and macrophysical and microphysical properties of Arctic mixed‐phase clouds (AMC), as well as the relationship between environmental parameters and AMC properties. In September and October, AMC occurrence frequency is 20–30% lower during a southerly wind when compared to the other wind directions; in November, the variation of AMC occurrence frequency with wind direction is small. The mean liquid water path in November is about half of that in October and September. When the surface is snow free, temperature (T) and specific humidity (q) profiles during a northerly wind are warmer and moister than those for the southerly wind. Northerly wind profiles have a higher relative humidity to ice (RHi) and lower atmosphere stability. Furthermore, the AMC occurrence frequency has a positive relationship with RHi and a negative relationship with stability. These two points may explain the lower AMC occurrence frequency during a southerly wind. During a northerly wind, AMCs have larger radar reflectivity, wider spectrum width, and larger Doppler velocity signatures. The stronger precipitation for AMC during a northerly wind is possibly due to the cleaner air masses from the ocean (north). With the same amount of q, the radar spectrum width has a higher frequency in the larger bins during a northerly wind. Both T, q, and radar reflectivity, radar spectrum width profiles show evidence of deposition in the sub‐cloud layer in September and October.

Suppressing Wind Turbine Signatures in Weather Radar Observations

Unwanted radar echoes, colloquially referred to as “clutter,” impede the mission effectiveness of radar systems. Depending on radar’s application, clutter examples can include weather, buildings, vegetation, and more. Techniques to mitigate clutter and improve the performance of radar systems are continuously being developed and refined. In this paper, wind turbines used for commercial power generation, which present a Doppler velocity signature that is time-varying, are considered a source of radar clutter. A wind turbine clutter mitigation technique is developed for fixed-pointing weather radar applications, approximating the turbine’s radar signature as a cyclostationary process. The cyclostationary model for the wind turbine and the suppression technique is then validated using observations of wind turbines and precipitation.

Survey of ULF wave signatures seen in the Tasman International Geospace Environment Radars data

AbstractUltralow frequency (ULF) plasma waves propagate through the magnetosphere and ionosphere where they can alter the Doppler velocity of HF radar echoes. Data from the two Tasman International Geospace Environment Radars and the fluxgate and induction coil magnetometers located on Macquarie Island (54.5°S, 158.95°E geographic) over 2006–2009 show that ULF wave signatures are common. Using coincident radar and magnetometer data selection criteria, 194 events representing a total of 233.4 h were identified. The majority of ULF signatures seen in the radar data were detected between 06 and 12 UT (15 and 21 LT). Using the Maximum Entropy Method, the spectral content showed favored frequencies of 1.6, 2.1, 2.9, and 3.3 mHz but no obvious variation of frequency with latitude. Most of the observed frequencies were in the range 1–4 mHz. A class of Doppler velocity signatures that appeared as a zigzag shape in the radar range:time plots were identified and may be related to the expected plasmapause latitudes. Regularly spaced, favored frequencies appeared in the ground magnetometer data during the afternoon, night, and morning sectors for those days where ULF wave events were observed in the radar data.

The Tornadic Vortex Signature: An Update

Abstract A tornadic vortex signature (TVS) is a degraded Doppler velocity signature of a tornado that occurs when the core region of a tornado is smaller than the half-power beamwidth of the sampling Doppler radar. Soon after the TVS was discovered in the mid-1970s, simulations were conducted to verify that the signature did indeed represent a tornado. The simulations, which used a uniform reflectivity distribution across a Rankine vortex model, indicated that the extreme positive and negative Doppler velocity values of the signature should be separated by about one half-power beamwidth regardless of tornado size or strength. For a Weather Surveillance Radar-1988 Doppler (WSR-88D) with an effective half-power beamwidth of approximately 1.4° and data collected at 1.0° azimuthal intervals, the two extreme Doppler velocity values should be separated by 1.0°. However, with the recent advent of 0.5° azimuthal sampling (“superresolution”) by WSR-88Ds at lower elevation angles, some of the extreme Doppler velocity values unexpectedly were found to be separated by 0.5° instead of 1.0° azimuthal intervals. To understand this dilemma, the choice of vortex model and reflectivity profile is investigated. It is found that the choice of vortex model does not have a significant effect on the simulation results. However, using a reflectivity profile with a minimum at the vortex center does make a difference. The revised simulations indicate that it is possible for the distance between the peak Doppler velocity values of a TVS to be separated by 0.5° with superresolution data collection.

Simulated Tornadic Vortex Signatures of Tornado-Like Vortices Having One- and Two-Celled Structures

AbstractA tornadic vortex signature (TVS) is a degraded Doppler velocity signature that occurs when the tangential velocity core region of a tornado is smaller than the effective beamwidth of a sampling Doppler radar. Early Doppler radar simulations, which used a uniform reflectivity distribution across an idealized Rankine vortex, showed that the extreme Doppler velocity peaks of a TVS profile are separated by approximately one beamwidth. The simulations also indicated that neither the size nor the strength of the tornado is recoverable from a TVS. The current study was undertaken to investigate how the TVS might change if vortices having more realistic tangential velocity profiles were considered. The one-celled (axial updraft only) Burgers–Rott vortex model and the two-celled (annular updraft with axial downdraft) Sullivan vortex model were selected. Results of the simulations show that the TVS peaks still are separated by approximately one beamwidth—signifying that the TVS not only is unaffected by the size or strength of a tornado but also is unaffected by whether the tornado structure consists of one or two cells.

Vertical Structure of Convective Systems during NAME 2004

Abstract This study describes the vertical structure of mesoscale convective systems (MCSs) that characterized the 2004 North American monsoon utilizing observations from a 2875-MHz (S band) profiler and a dual-polarimetric scanning Doppler radar. Both instrument platforms operated nearly continuously during the North American Monsoon Experiment (NAME). A technique was developed to identify dominant hydrometeor type using S-band (profiler) reflectivity along with temperature. The simplified hydrometeor identification (HID) algorithm matched polarimetric scanning radar fuzzy logic–based HID results quite well. However, the simplified algorithm lacked the ability to identify ice hydrometeors below the melting layer and on occasion, underestimated the vertical extent of graupel because of a profiler reflectivity bias. Three of the strongest NAME convective rainfall events recorded by the profiler are assessed in this study. Stratiform rain exhibited a reflectivity bright band and strong Doppler velocity gradient within the melting layer. Convective rainfall exhibited high reflectivity and Doppler velocities exceeding 3 (−10) m s−1 in updrafts (downdrafts). Low-density graupel persisted above the melting layer, often extending to 10 km, with high-density graupel observed near 0°C. Doppler velocity signatures suggested that updrafts and downdrafts were often tilted, though estimating the degree of tilt would have required a more three-dimensional view of the passing storms. Cumulative frequency distributions (CFDs) of reflectivity were created for stratiform and convective rainfall and were found to be similar to results from other tropical locations.

Simulated WSR-88D Velocity and Reflectivity Signatures of Numerically Modeled Tornadoes

Abstract Low-altitude radar reflectivity measurements of tornadoes sometimes reveal a donut-shaped signature (low-reflectivity eye surrounded by a high-reflectivity annulus) and at other times reveal a high-reflectivity knob associated with the tornado. The differences appear to be due to such factors as (i) the radar’s sampling resolution, (ii) the presence or absence of lofted debris and a low-reflectivity eye, (iii) whether measurements were made within the lowest few hundred meters where centrifuged hydrometeors and smaller debris particles were recycled back into the tornadic circulation, and (iv) the presence or absence of multiple vortices in the parent tornado. To explore the influences of some of these various factors on radar reflectivity and Doppler velocity signatures, a high-resolution tornado numerical model was used that incorporated the centrifuging of hydrometeors. A model reflectivity field was computed from the resulting concentration of hydrometeors. Then, the model reflectivity and velocity fields were scanned by a simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) using both the legacy resolution and the new super-resolution sampling. Super-resolution reflectivity and Doppler velocity data are displayed at 0.5° instead of 1.0° azimuthal sampling intervals and reflectivity data are displayed at 0.25-km instead of 1.0-km range intervals. Since a mean Doppler velocity value is the reflectivity-weighted mean of the radial motion of all the radar scatterers within a radar beam, a nonuniform distribution of scatterers produces a different mean Doppler velocity value than does a uniform distribution of scatterers. Nonuniform reflectivities within the effective resolution volume of the radar beam can bias the indicated size and strength of the tornado’s core region within the radius of the peak tangential velocities. As shown in the simulation results, the Doppler-indicated radius of the peak wind underestimates the true radius and true peak tangential velocity when the effective beamwidth is less than the tornado’s core diameter and there is a weak-reflectivity eye at the center of the tornado. As the beam becomes significantly wider than the tornado’s core diameter with increasing range, the peaks of the Doppler velocity profiles continue to decrease in magnitude but overestimate the tornado’s true radius. With increasing range from the radar, the prominence of the weak-reflectivity eye at the center of the tornado is progressively lessened until it finally disappears. As to be expected, the Doppler velocity signatures and reflectivity eye signatures were more prominent and stronger with super-resolution sampling than those with legacy-resolution sampling.

Simulated Doppler Velocity Signatures of Evolving Tornado-Like Vortices

Abstract Exact solutions of the Navier–Stokes or Euler equations of motion and the continuity equation in cylindrical coordinates for 3D, axisymmetric, inviscid, or laminar flows are utilized to represent evolving vortices that roughly model tornado cyclones or misocyclones contracting to tornadoes. These solutions are unsteady versions of the diffusive Burgers–Rott vortex and the inviscid Rankine-combined vortex. They satisfy the free-slip condition at the ground. Different vortices are obtained by choosing different values of the constant eddy viscosity and uniform horizontal convergence while holding the circulation at infinity constant. A simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) is employed to generate time-varying Doppler velocity signatures in uniform reflectivity of these analytical vortices at ranges of 25 and 50 km from the radar. Mean Doppler velocities are determined by computing 3D integrals over effective resolution volumes. Magnitudes of Doppler vortex signatures at different times in the evolution of the stationary vortices are computed for effective beamwidths of 1.02° and 1.39°, which correspond to azimuthal sampling intervals of 0.5° and 1.0°, respectively. Four tornado predictors—rotational velocity, shear, excess rotational kinetic energy, and circulation—are examined. Results of the simulations show that for smaller effective beamwidths, Doppler vortex signatures are stronger and exceed fixed threshold values of rotational velocity and shear earlier. With finer azimuthal resolution, tornado cyclone, misocyclone, or tornado signatures switch to tornadic vortex signatures later. Circulations of the vortex signatures give good estimates of the circulations of the simulated tornadoes and tornado cyclones with relative insensitivity to range, effective beamwidth, and stage of evolution. High circulation and convergence values of a rotation signature reveal the potential for a tornado earlier than all the other predictors, which increase significantly during tornadogenesis.

Doppler Velocity Signatures of Idealized Elliptical Vortices

Doppler Velocity Signatures of Idealized Elliptical Vortices

PATH TO NEXRAD: Doppler Radar Development at the National Severe Storms Laboratory

In this historical paper, we trace the scientific-and engineering-based steps at the National Severe Storms Laboratory (NSSL) and in the larger weather radar community that led to the development of NSSL's first 10-cm-wavelength pulsed Doppler radar. This radar was the prototype for the current Next Generation Weather Radar (NEXRAD), or Weather Surveillance Radar-1998 Doppler (WSR-88D) network. We track events, both political and scientific, that led to the establishment of NSSL in 1964. The vision of NSSL's first director, Edwin Kessler, is reconstructed through access to historical documents and oral histories. This vision included the development of Doppler radar, where research was to be meshed with the operational needs of the U.S. Weather Bureau and its successor—the National Weather Service. Realization of the vision came through steps that were often fitful, where complications arose due to personnel concerns, and where there were always financial concerns. The historical research indicates that 1) the engineering prowess and mentorship of Roger Lhermitte was at the heart of Doppler radar development at NSSL; 2) key decisions by Kessler in the wake of Lhermitte's sudden departure in 1967 proved crucial to the ultimate success of the project; 3) research results indicated that Doppler velocity signatures of mesocyclones are a precursor of damaging thunderstorms and tornadoes; and 4) results from field testing of the Doppler-derived products during the 1977-79 Joint Doppler Operational Project—especially the noticeable increase in the verification of tornado warnings and an associated marked decrease in false alarms—led to the government decision to establish the NEXRAD network.

Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements

Abstract Doppler velocity and reflectivity measurements from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0° and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory’s test bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5°-azimuthal spacing and 0.25-km-range spacing, resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fine-resolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements

Doppler velocity and reflectivity measurements from Weather Surveillance Radar-1988 Doppler (WSR88D) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0° and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory’s test bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5°-azimuthal spacing and 0.25-km-range spacing, resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fineresolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

Improved Tornado Detection Using Simulated and Actual WSR-88D Data with Enhanced Resolution

Abstract The magnitude of the Doppler velocity signature of a tornado depends on the effective width of the radar beam relative to the size of the tornado. The effective beamwidth is controlled by the antenna pattern beamwidth and the azimuthal sampling interval. Simulations of Weather Surveillance Radar-1988 Doppler (WSR-88D) velocity signatures of tornadoes, presented in this paper, show that signature resolution is greatly improved when the effective beamwidth of the radar is reduced. Improved signature resolution means that stronger signatures can be resolved at greater ranges from the radar. Using a special recording device on the National Weather Service's Radar Operations Center's KCRI test bed radar, Archive Level I time series data were collected during the Oklahoma–Kansas tornado outbreak of 3 May 1999. Two Archive Level II meteorological datasets, each having a different effective beamwidth, were created from the Archive Level I dataset. Since the rotation rate and time interval between pulses ...

Technique for Improving Detection of WSR-88D Mesocyclone Signatures by Increasing Angular Sampling

Abstract The Doppler velocity signature of a thunderstorm mesocyclone becomes increasingly degraded as distance from the radar increases. Degradation is due to the broadening of the radar beam with range relative to the size of the mesocyclone. Using a model mesocyclone and a simulated WSR-88D Doppler radar, a potential approach for improving the detection of mesocyclones is investigated. The approach involves decreasing the azimuthal sampling interval from the conventional 1.0° to 0.5°. Using model mesocyclones that cover the spread of expected mesocyclone sizes and strengths, simulations show that stronger mesocyclone signatures consistently are produced when radar data are collected at 0.5° azimuthal increments. Consequently, the distance from the radar at which a mesocyclone of a given strength and size can be detected increases by an average of at least 50% when data are collected using 0.5° azimuthal increments. The simulated findings are tested using Archive Level I (time series) data collected by ...

Effects of Radar Sampling on Single-Doppler Velocity Signatures of Mesocyclones and Tornadoes

Abstract Simulated WSR-88D (Weather Surveillance Radar-1988 Doppler) radar data were used to investigate the effects of discrete azimuthal sampling on Doppler velocity signatures of modeled mesocyclones and tornadoes at various ranges from the radar and for various random positions of the radar beam with respect to the vortices. Results show that the random position of the beam can change the magnitudes and locations of peak Doppler velocity values. The important implication presented in this study is that short-term variations in tornado and far-range mesocyclone intensity observed by a WSR-88D radar may be due to evolution or due to the chance positions of the radar beam relative to the vortex’s maximum rotational velocities or due to some combination of both.

Evolution and Morphology of Two Splitting Thunderstorms with Dominant Left-Moving Members

During the late afternoon and early evening of 27 June 1989. Three splitting thunderstorms formed over Standing Rock Indian Reservation in the southern portion of the North Dakota Thunderstorm Project area. The first two storms are the subject of this study. The entire life cycles of both storms were documented using a single ground-based Doppler radar. Radar reflectivity signatures of updraft summits and Doppler velocity signatures of divergence near storm top were used to deduce updraft evolution within the storms. Dual-Doppler radar observations from a ground-based radar and an airborne Doppler radar provided fragmentary documentation of the storms’ life cycles. The splitting storms on that day were unusual in two distinct ways: (a) the left members of the splitting storms were the dominant and longer-lasting ones, and (b) none of the deduced updrafts were collocated with centers of vorticity signatures that would have indicated updraft rotation. Both of the left-moving storms had 10 sequential primary updrafts, whereas their right-hand counterparts had 3 or 4 primary updrafts. Initial formation of the right-flank updrafts lagged behind the initial formation of the left-flank updrafts by 40–70 min. All the individual updraft summits moved in the general direction of the mean wind. Sequential updraft development on the left and right flanks of the storms suggested that expanding gust fronts provided the propagational component of storm motion.

Observations of global-scale photospheric Fraunhofer line shifts

Transform techniques have been applied to a 1 yr sequence of solar photospheric Fraunhofer line shift data. In agreement with earlier studies, we find no evidence of large-scale structure in mean spatial power spectra near the level of 12 m s/sup -1/. It is argued that such spectra are easily dominated by random supergranule noise, and that these data may even be used to estimate supergranule characteristics. By considering a rotation signal in the temporal transformed data, we find statistical evidence (at the 3 sigma level) of a large-scale, long-lived, photospheric line shift field. A simple model suggests spatial scales of 10/sup 5/--10/sup 6/ km, with lifetimes of at least 3 days and line shifts corresponding to velocity amplitudes near 2 m s/sup -1/. While the interpretation of the residual line shift is not unambiguous, we suggest that this is the Doppler velocity signature of large-scale convective cells.

Tornado characteristics revealed by Doppler radar

A Doppler velocity signature of large shear coincident with tornado location has been discovered in an Oklahoma thunderstorm. The gate‐to‐gate tangential shear (GGS) signature is used to draw conclusions concerning vertical depth of the tornado vortex and its apparent descent from storm mid‐levels to the surface.