dual-Doppler Analysis Research Articles

Machine Learning Estimation of Maximum Vertical Velocity from Radar

Abstract The quantification of storm updrafts remains unavailable for operational forecasting despite their inherent importance to convection and its associated severe weather hazards. Updraft proxies, like overshooting top area from satellite images, have been linked to severe weather hazards but only relate to a limited portion of the total storm updraft. This study investigates if a machine learning model, namely, U-Nets, can skillfully retrieve maximum vertical velocity and its areal extent from three-dimensional gridded radar reflectivity alone. The machine learning model is trained using simulated radar reflectivity and vertical velocity from the National Severe Storm Laboratory’s convection permitting Warn-on-Forecast System (WoFS). A parametric regression technique using the sinh–arcsinh–normal distribution is adapted to run with U-Nets, allowing for both deterministic and probabilistic predictions of maximum vertical velocity. The best models after hyperparameter search provided less than 50% root mean squared error, a coefficient of determination greater than 0.65, and an intersection over union (IoU) of more than 0.45 on the independent test set composed of WoFS data. Beyond the WoFS analysis, a case study was conducted using real radar data and corresponding dual-Doppler analyses of vertical velocity within a supercell. The U-Net consistently underestimates the dual-Doppler updraft speed estimates by 50%. Meanwhile, the area of the 5 and 10 m s−1 updraft cores shows an IoU of 0.25. While the above statistics are not exceptional, the machine learning model enables quick distillation of 3D radar data that is related to the maximum vertical velocity, which could be useful in assessing a storm’s severe potential. Significance Statement All convective storm hazards (tornadoes, hail, heavy rain, straight line winds) can be related to a storm’s updraft. Yet, there is no direct measurement of updraft speed or area available for forecasters to make their warning decisions from. This paper addresses the lack of observational data by providing a machine learning solution that skillfully estimates the maximum updraft speed within storms from only the radar reflectivity 3D structure. After further vetting the machine learning solutions on additional real-world examples, the estimated storm updrafts will hopefully provide forecasters with an added tool to help diagnose a storm’s hazard potential more accurately.

Airborne Radar Quality Control with Machine Learning

Abstract Airborne Doppler radar provides detailed and targeted observations of winds and precipitation in weather systems over remote or difficult-to-access regions that can help to improve scientific understanding and weather forecasts. Quality control (QC) is necessary to remove nonweather echoes from raw radar data for subsequent analysis. The complex decision-making ability of the machine learning random-forest technique is employed to create a generalized QC method for airborne radar data in convective weather systems. A manually QCed dataset was used to train the model containing data from the Electra Doppler Radar (ELDORA) in mature and developing tropical cyclones, a tornadic supercell, and a bow echo. Successful classification of ∼96% and ∼93% of weather and nonweather radar gates, respectively, in withheld testing data indicate the generalizability of the method. Dual-Doppler analysis from the genesis phase of Hurricane Ophelia (2005) using data not previously seen by the model produced a comparable wind field to that from manual QC. The framework demonstrates a proof of concept that can be applied to newer airborne Doppler radars. Significance Statement Airborne Doppler radar is an invaluable tool for making detailed measurements of wind and precipitation in weather systems over remote or difficult to access regions, such as hurricanes over the ocean. Using the collected radar data depends strongly on quality control (QC) procedures to classify weather and nonweather radar echoes and to then remove the latter before subsequent analysis or assimilation into numerical weather prediction models. Prior QC techniques require interactive editing and subjective classification by trained researchers and can demand considerable time for even small amounts of data. We present a new machine learning algorithm that is trained on past QC efforts from radar experts, resulting in an accurate, fast technique with far less user input required that can greatly reduce the time required for QC. The new technique is based on the random forest, which is a machine learning model composed of decision trees, to classify weather and nonweather radar echoes. Continued efforts to build on this technique could benefit future weather forecasts by quickly and accurately quality-controlling data from other airborne radars for research or operational meteorology.

The Potential Roles of Preexisting Airmass Boundaries on a Tornadic Supercell Observed by TORUS on 28 May 2019

Abstract On 28 May 2019, a tornadic supercell, observed as part of Targeted Observation by UAS and Radars of Supercells (TORUS) produced an EF-2 tornado near Tipton, Kansas. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool-side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm-side air mass; features associated with mesoscale air masses with high theta-e (MAHTEs). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell.

Insights in Hailstorm Dynamics through Polarimetric High-Resolution X-Band and Operational C-Band Radar: A Case Study for Vienna, Austria

Abstract Data from a dual-polarized, solid-state X-band radar and an operational C-band weather radar are used for high-resolution analyses of two hailstorms in the Vienna, Austria, region. The combination of both radars provides rapid-update (1 min) polarimetric data paired with wind field data of a dual-Doppler analysis. This is the first time that such an advanced setup is used to examine severe storm dynamics at the eastern Alpine fringe, where the influence of local topography is particularly challenging for thunderstorm prediction. We investigate two storms transitioning from the pre-Alps into the Vienna basin with different characteristics: 1) A rapidly evolving multicell storm producing large hail (5 cm), with observations of an intense ZDR column preceding hail formation and the rapid development of multiple pulses of hail; and 2) a cold pool–driven squall line with small hail, for which we find that the updraft location inhibited the formation of larger hailstones. For both cases, we analyzed the evolution of different ZDR column metrics as well as updraft speed and size and found that (i) the 90th percentile of ZDR within the ZDR column was highest for the cell later producing large hail, (ii) the peak 90th percentile of ZDR preceded large hailfall by 20 min and highest updraft size and speed by 10 min, and (iii) sudden drops of the 90th percentile of ZH within the ZDR column indicated imminent hailfall. Significance Statement Thunderstorm evolution on the transition from complex terrain into the Vienna basin in northeastern Austria varies strongly. In some instances, thunderstorm cells intensify once they reach flat terrain, while in most cases there is a weakening tendency. To improve our process understanding and short-term forecasting methods, we analyze two representative cases of hail-bearing storms transitioning into the Vienna basin. We mainly build our study on data from a new, cost-efficient weather radar, complemented by an operational radar, lightning observations, and ground reports. Our results show which radar variables could be well suited for early detection of intensification, and how they relate to thunderstorm updraft speeds and lightning activity.

Dynamic Field Retrieval and Analysis of Structural Evolution in Offshore Core Area of Typhoon Higos Based on Ground-Based Radar Observation

Three ground-based radars in the Pearl River Delta successfully observed Typhoon Higos (2020), which traveled over the offshore area in the South China Sea. During the observation period, the stratiform region of the outer rainband of HIGOS became active while swirling inward, merging into an unclosed eyewall and spreading outward, but its structure was asymmetric between upwind and downwind. To understand the dynamic mechanism of the asymmetry of the stratiform region in detail, the refined wind speed distributions in the inner core of Higos was retrieved by using the radar observation data and a three-dimensional, variational, direct, data assimilation, Dual-Doppler analysis (DDA). In addition, an Observing System Simulation Experiment (OSSE) was conducted with the numerical simulations by the Weather Research and Forecasting (WRF) model and numerical emulations by Cloud Resolving Model Radar SIMulator (CR-SIM) software to validate the retrieved data. From the OSSE, the emulated retrieved data were comparable with the WRF-out data. The analysis shows that the dynamic mechanisms are different between upwind and downwind in the stratiform rainband. In the former, the inflow sinks in the middle troposphere. In addition, there is an inflow in the lower troposphere, with an outflow aloft the inflow. In the latter, however, the stratiform rainband is primarily influenced by outflow from inside the rainband and inflow from outside the monsoon-related southwesterly winds. The vertical velocity characteristics in the stratiform rainband downwind also differ from those upwind. The upwind updraft was distinct in the middle troposphere, whereas the downwind updraft was caused by the convergence of the outflow from inside the stratiform rainband and the monsoon-related southwesterly inflow in the lower troposphere.

Evaluating Vertical Velocity Retrievals from Vertical Vorticity Equation Constrained Dual-Doppler Analysis of Real, Rapid-Scan Radar Data

Abstract Accurate vertical velocity retrieval from dual-Doppler analysis (DDA) is a long-standing problem of radar meteorology. Typical radar scanning strategies poorly observe the vertical component of motion, leading to large uncertainty in vertical velocity estimates. Using a vertical vorticity equation constraint in addition to a mass conservation constraint in DDA has shown promise in improving vertical velocity retrievals. However, observation system simulation experiments (OSSEs) suggest this technique requires rapid radar volume scans to realize the improvements due to the vorticity tendency term in the vertical vorticity constraint. Here, the vertical vorticity constraint DDA is tested with real, rapid-scan radar data to validate prior OSSEs results. Generally, the vertical vorticity constraint DDA produced more accurate vertical velocities from DDAs than those that did not use the constraint. When the time between volume scans was greater than 30 s, the vertical velocity accuracy was significantly affected by the vorticity tendency estimation method. A technique that uses advection correction on provisional DDA wind fields to shorten the discretization interval for the vorticity tendency calculation improved the vertical velocity retrievals for longer times between volume scans. The skill of these DDAs was similar to those using a shorter time between volume scans. These improvements were due to increased accuracy of the vertical vorticity tendency using the advection correction technique. The real radar data tests also revealed that the vertical vorticity constraint DDAs are more forgiving to radar data errors. These results suggest that vertical vorticity constraint DDA with rapid-scan radars should be prioritized for kinematic analyses.

A Variational Method for Analyzing Vortex Flows in Radar-Scanned Tornadic Mesocyclones. Part IV: Applications to the 20 May 2013 Oklahoma Tornadic Mesocyclone

Abstract The variational method for vortex flow (VF) analyses, called VF-Var (formulated in Part I), is applied to the 20 May 2013 Newcastle–Moore tornadic mesocyclone observed from the operational KTLX radar and an experimental phased-array radar. The dual-Doppler-analyzed VF field reveals the following features: The axisymmetric part of the VF is a well-defined slantwise two-cell vortex in which the maximum tangential velocity is nearly 40 m s−1 at the edge of the vortex core (0.6 km from the vortex center), the central downdraft velocity reaches −35 m s−1 at 3-km height, and the surrounding-updraft velocity reaches 26 m s−1 at 5-km height. The total VF field is a loosely defined slantwise two-cell vortex consisting of a nearly axisymmetric vortex core (in which the ground-relative surface wind speed reaches 50 m s−1 on the southeast edge), a strong nonaxisymmetric slantwise downdraft in the vortex core, and a main updraft in a banana-shaped area southeast of the vortex core, which extends slantwise upward and spirals cyclonically around the vortex core. The single-Doppler analysis with observations from the KTLX radar only exhibits roughly the same features as the dual-Doppler analysis but contains spurious vertical-motion structures in and around the vortex core. Analysis errors are assessed by leveraging the findings from Parts II and III, which indicate that the dual-Doppler-analyzed VF is accurate enough to represent the true VF but the single-Doppler-analyzed VF is not (especially for nonaxisymmetric vertical motions in and around the vortex core), so the dual-Doppler-analyzed VF should be useful for initializing/verifying high-resolution tornado simulations. Significance Statement After the variational method for vortex flow (VF) analyses, called VF-Var (formulated in Part I of this paper series), was tested successfully with simulated radar observations in Part II and its sensitivity to vortex center location error was examined in Part III, the method is now applied to the 20 May 2013 Newcastle–Moore tornadic mesocyclone observed from the operational KTLX radar and an experimental phased-array radar. Analysis errors are assessed by leveraging the findings from Parts II and III. The results indicate that the dual-Doppler-analyzed VF is accurate enough to represent the true VF (although the single-Doppler-analyzed VF is not especially for nonaxisymmetric vertical motions in and around the vortex core) and thus should be useful for initializing/verifying high-resolution tornado simulations.

A Variational Method for Analyzing Vortex Flows in Radar-Scanned Tornadic Mesocyclones. Part III: Sensitivities to Vortex Center Location Errors

Abstract When the vortex center location is estimated from a radar-scanned tornadic mesocyclone, the estimated location is not error-free. This raises an important issue concerning the sensitivities of analyzed vortex flow (VF) fields by the VF-Var (formulated in Part I of this paper series and tested in Part II) to vortex center location errors, denoted by Δxc. Numerical experiments are performed to address this issue with the following findings: The increase of |Δxc| from zero to a half of vortex core radius causes large analysis error increases in the vortex core but the increased analysis errors decrease rapidly away from the vortex core especially for dual-Doppler analyses. The increased horizontal-velocity errors in the vortex core are mainly in the Δxc-normal component, because this component varies much more rapidly than the other component along the Δxc direction in the vortex core. The vertical variations of Δxc distort the vertical correlation structure of Δxc-dislocated VF-dependent background error covariance, which can increase the analysis errors in the vortex core. The dual-Doppler analyses have adequate accuracies outside the vortex core even when |Δxc| increases to a half of vortex core radius, while single-Doppler analyses can also have adequate accuracies outside the vortex core mainly for the single-Doppler-observed velocity component. The sensitivities to Δxc are largely unaffected by the vortex slanting. The above findings are important and useful for assessing the accuracies of analyzed VFs for real radar-observed tornadic mesocyclones. Significance Statement When the vortex center location is estimated from a radar-scanned tornadic mesocyclone, the estimated location is not error-free. This raises an issue concerning the sensitivity of analyzed vortex flow (VF) by the VF-Var (formulated in Part I of this paper series and tested with simulated radar observations in Part II) to vortex center location error. This issue and its required investigations are very important for the VF-Var to be applied to real radar-observed tornadic mesocyclones, especially in an operational setting with the WSR-88Ds. Numerical experiments are performed to address this issue. The findings from these experiments are important and useful for assessing the accuracies of VF-Var analyzed VF fields for real radar-observed tornadic mesocyclones.

Transition of the Hurricane Boundary Layer during the Landfall of Hurricane Irene (2011)

AbstractThe hurricane boundary layer (HBL) has been observed in great detail through aircraft investigations of tropical cyclones over the open ocean, but the coastal transition of the HBL has been less frequently observed. During the landfall of Hurricane Irene (2011), research and operational aircraft over water sampled the open-ocean HBL simultaneously with ground-based research and operational Doppler radars onshore. The location of the radars afforded 13 h of dual-Doppler analysis over the coastal region. Thus, the HBL from the coastal waterways, through the coastal transition, and onshore was observed in great detail for the first time. Three regimes of HBL structure were found. The outer bands were characterized by temporal perturbations of the HBL structure with attendant low-level wind maxima in the vicinity of rainbands. The inner core, in contrast, did not produce such perturbations, but did see a reduction of the height of the maximum wind and a more jet-like HBL wind profile. In the eyewall, a tangential wind maximum was observed within the HBL over water as in past studies and above the HBL onshore. However, the transition of the tangential wind maximum through the coastal transition showed that the maximum continued to reside in the HBL through 5 km inland, which has not been observed previously. It is shown that the adjustment of the HBL to the coastal surface roughness discontinuity does not immediately mix out the residual high-momentum jet aloft. Thus, communities closest to the coast are likely to experience the strongest winds onshore prior to the complete adjustment of the HBL.

Mesoscale Analysis on the Asymmetric Rainband of Typhoon Matmo (2014) and the Related Weather Situations for the GE222 Aircraft Crash Case

Typhoon Matmo (2014) was formed over the Central Pacific Ocean on 18 July 2014, and later, it became moderate in intensity (32.7~50.9 m/s) with maximum wind speed of 38 m/s. After it landed the southeast coast of China, the typhoon circulation showed an asymmetric pattern in dipole wind field based upon the composite mean winds at 925 hPa in use of NCEP/NCAR reanalysis data and NOAA/ESRL atmospheric variables plotting approach. The wind dipole feature was due to the steep gradient of the geopotential height anomaly at the east flank of the typhoon circulation and the friction effect at its lowest levels over land from the synoptic scale point of view. The study focuses on investigating the characteristics of the line echo wave pattern (LEWP) embedded within the typhoon rainband through the multi-scale processes, and try to realize the possible causes of crash event from the meteorological point of view for TransAsia Airways GE222 occurrence at Makung Airport influenced by the LEWPs in use of mesonet surface analysis based on 1-minute interval data measured by Makung Airport weather station and dual-Doppler radar analysis composited from Makung and Chiku weather radar data. The preliminary results delineated that the wave-like echoes organized by deep convections featured a key factor on the development of short duration heavy rainfall, low visibility and significant turbulence from the mesoscale point of view. Conclusively speaking, the aircraft faced multiple and severe weather situations, including the intense crosswind, obvious downdraft and extremely low visibility. Therefore, the impact of deep convections inside LEWPs embedded within the typhoon rainband on aviation safety was remarkable, and this case is a good lesson for flight safety.

Detailed Dual-Doppler Structure of Kelvin–Helmholtz Waves from an Airborne Profiling Radar over Complex Terrain. Part I: Dynamic Structure

AbstractKelvin–Helmholtz (KH) waves are remarkably common in deep stratiform precipitation systems associated with frontal disturbances, at least in the vicinity of complex terrain, as is evident from transects of vertical velocity and 2D circulation, obtained from a 3-mm airborne Doppler radar, the Wyoming Cloud Radar. The high range resolution of this radar (~40 m) allows detection and depiction of KH waves in fine detail. These waves are observed in a variety of wavelengths, depths, amplitudes, and turbulence intensities. Proximity rawinsonde data confirm that they are triggered in layers where the Richardson number is very small. Complex terrain may locally enhance wind shear, leading to KH instability. In some KH waves, the flow remains mostly laminar, while in other cases it breaks down into turbulence. KH waves are frequently locked to the terrain, and occur at various heights, including within the free troposphere, at the boundary layer top, and close to the surface. They are observed not only upwind of terrain barriers, as has been documented before, but also in the wake of steep terrain, where the waves can be highly turbulent. Vertical-plane dual-Doppler analyses of KH waves reveal the mixing of layers of differential momentum across the high-shear zone. Doppler radar data are used to explore the dynamics of KH waves, including the response of thermodynamic and kinematic variables above, below, and within the instability layer.

Mobile Radar Observations of the Evolving Debris Field Compared with a Damage Survey of the Shawnee, Oklahoma, Tornado of 19 May 2013

AbstractA detailed damage survey is combined with high-resolution mobile, rapid-scanning X-band polarimetric radar data collected on the Shawnee, Oklahoma, tornado of 19 May 2013. The focus of this study is the radar data collected during a period when the tornado was producing damage rated EF3. Vertical profiles of mobile radar data, centered on the tornado, revealed that the radar reflectivity was approximately uniform with height and increased in magnitude as more debris was lofted. There was a large decrease in both the cross-correlation coefficient (ρhv) and differential radar reflectivity (ZDR) immediately after the tornado exited the damaged area rated EF3. Low ρhv and ZDR occurred near the surface where debris loading was the greatest. The 10th percentile of ρhv decreased markedly after large amounts of debris were lofted after the tornado leveled a number of structures. Subsequently, ρhv quickly recovered to higher values. This recovery suggests that the largest debris had been centrifuged or fallen out whereas light debris remained or continued to be lofted. Range–height profiles of the dual-Doppler analyses that were azimuthally averaged around the tornado revealed a zone of maximum radial convergence at a smaller radius relative to the leading edge of lofted debris. Low-level inflow into the tornado encountering a positive bias in the tornado-relative radial velocities could explain the existence of the zone. The vertical structure of the convergence zone was shown for the first time.

High-Resolution, Rapid-Scan Dual-Doppler Retrievals of Vertical Velocity in a Simulated Supercell

AbstractObservation system simulation experiments are used to evaluate different dual-Doppler analysis (DDA) methods for retrieving vertical velocity w at grid spacings on the order of 100 m within a simulated tornadic supercell. Variational approaches with and without a vertical vorticity equation constraint are tested, along with a typical (traditional) method involving vertical integration of the mass conservation equation. The analyses employ emulated radar data from dual-Doppler placements 15, 30, and 45 km east of the mesocyclone, with volume scan intervals ranging from 10 to 150 s. The effect of near-surface data loss is examined by denying observations below 1 km in some of the analyses. At the longer radar ranges and when no data denial is imposed, the “traditional” method produces results similar to those of the variational method and is much less expensive to implement. However, at close range and/or with data denial, the variational method is much more accurate, confirming results from previous studies. The vorticity constraint shows the potential to improve the variational analysis substantially, reducing errors in the w retrieval by up to 30% for rapid-scan observations (≤30 s) at close range when the local vorticity tendency is estimated using spatially variable advection correction. However, the vorticity constraint also degrades the analysis for longer scan intervals, and the impact diminishes with increased range. Furthermore, analyses using 30-s data also frequently outperform analyses using 10-s data, suggesting a limit to the benefit of increasing the radar scan rate for variational DDA employing the vorticity constraint.

A Generalized Navigation Correction Method for Airborne Doppler Radar Data

AbstractUncertainties in aircraft inertial navigation system and radar-pointing angles can have a large impact on the accuracy of airborne dual-Doppler analyses. The Testud et al. (THL) method has been routinely applied to data collected by airborne tail Doppler radars over flat and nonmoving terrain. The navigation correction method proposed in Georgis et al. (GRH) extended the THL method over complex terrain and moving ocean surfaces by using a variational formulation but its capability over ocean has yet to be tested. Recognizing the limitations of the THL method, Bosart et al. (BLW) proposed to derive ground speed, tilt, and drift errors by statistically comparing aircraft in situ wind with dual-Doppler wind at the flight level. When combined with the THL method, the BLW method can retrieve all navigation errors accurately; however, it can be applied only to flat surfaces, and it is rather difficult to automate. This paper presents a generalized navigation correction method (GNCM) based on the GRH method that will serve as a single algorithm for airborne tail Doppler radar navigation correction for all possible surface conditions. The GNCM includes all possible corrections in the cost function and implements a new closure assumption by taking advantage of an accurate aircraft ground speed derived from GPS technology. The GNCM is tested extensively using synthetic airborne Doppler radar data with known navigation errors and published datasets from previous field campaigns. Both tests show the GNCM is able to correct the navigation errors associated with airborne tail Doppler radar data with adequate accuracy.

Applications of a Spatially Variable Advection Correction Technique for Temporal Correction of Dual-Doppler Analyses of Tornadic Supercells

Abstract In many instances, synchronization of Doppler radar data among multiple platforms for multiple-Doppler analysis is challenging. This study describes the production of dual-Doppler wind analyses from several case studies using data from a rapid-scanning, X-band, polarimetric, Doppler radar—the RaXPol radar—and data from nearby WSR-88Ds. Of particular interest is mitigating difficulties related to the drastic differences in scanning rates of the two radars. To account for differences in temporal resolution, a variational reflectivity tracking scheme [a spatially variable advection correction technique (SVAC)] has been employed to interpolate (in a Lagrangian sense) the coarser temporal resolution data (WSR-88D) to the times of the RaXPol volume scans. The RaXPol data and temporally interpolated WSR-88D data are then used to create quasi–rapid scan dual-Doppler analyses. This study focuses on the application of the SVAC technique to WSR-88D data to create dual-Doppler analyses of three tornadic supercells: the 19 May 2013 Edmond–Carney and Norman–Shawnee, Oklahoma, storms and the 24 May 2016 Dodge City, Kansas, storm. Results of the dual-Doppler analyses are briefly examined, including observations of the ZDR columns as a proxy for updrafts. Potential improvements to this technique are also discussed.

In Situ and Radar Observations of the Low Reflectivity Ribbon in Supercells during VORTEX2

Abstract During the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) field campaign, mobile radars observed a previously undocumented feature: the low-reflectivity ribbon (LRR). The LRR was characterized by reduced reflectivity ZH and differential reflectivity ZDR through a narrow region extending from the intersection of the hook and forward-flank regions of supercells. This study synthesizes kinematic and polarimetric radar observations with in situ measurements taken by the “StickNet” observing network. StickNet data have been used to establish that the LRR is associated with a localized minimum in pseudoequivalent potential temperature Pronounced drops in are observed by nine separate probes in three different supercell thunderstorms. Both single- and dual-Doppler analyses are used to examine the two- and three-dimensional structures of the winds within the LRR, revealing that the LRR is associated with cyclonic vertical vorticity aloft. Polarimetric radar observations are used to study the hydrometeor characteristics and the processes that cause those hydrometers to be present. Special consideration is given to the analysis of the vertical distribution of traditional and polarimetric variables, as well as the evolution of the kinematic fields retrieved by dual-Doppler analysis. The combination of thermodynamic, kinematic, and inferred microphysical observations supports a hypothesis that the LRR comprises sparse, large hail.

Kinematic and Polarimetric Radar Observations of the 10 May 2010, Moore–Choctaw, Oklahoma, Tornadic Debris Signature

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 ([Formula: see text]) 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.

Kinematic Structure of Mesovortices in the Eyewall of Hurricane Ike (2008) Derived from Ground-Based Dual-Doppler Analysis

AbstractPrevious work has shown that vorticity mixing in the tropical cyclone (TC) inner core can promote mesovortex (MV) formation and impact storm intensity. Observations of MVs have largely been serendipitous but are necessary to improve understanding of these features and their role in TC dynamics. This study presents nearly 10 h of ground-based dual-Doppler analysis of MVs in the eyewall of Hurricane Ike (2008) near and during landfall. Derived 3D winds, vertical vorticity, horizontal divergence, and perturbation pressures are analyzed. Results indicate persistent kinematic field arrangements and evolving vertical structures. Perturbation pressure retrievals suggest local pressure minima associated with the MVs. Preferential updraft locations appear to transition cyclonically about the local vorticity maximum as the MVs progress around the eye. Based on published observational datasets, the dual-Doppler updraft magnitudes in Ike’s MVs are within the top 5%–10% of TC vertical velocities. The MVs are marked by peak vorticity in the lowest 2 km and contain vertically coherent vorticity structures extending to 8 km AGL. After prolonged land interaction, the MV structures deteriorate. First, the vertical extent of localized vorticity diminishes, followed by a deterioration in the prelandfall characteristic kinematic arrangements. This supports the notion that the replenishment of a high vorticity annulus contributes to MV production and maintenance, and when the elevated vorticity aloft is not maintained, MV kinematic patterns become less consistent. It is unclear whether the decay of the vertically coherent vorticity structures occurs in response to land interaction, TC inner core processes, or some combination of both.

Velocity–Azimuth Display Analysis of Doppler Velocity for HIWRAP

AbstractThe velocity–azimuth display (VAD) analysis technique established for ground-based scanning radar is applied to the NASA High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP). The VAD technique provides a mean vertical profile of the horizontal winds for each complete conical scan of the HIWRAP radar. One advantage of this technique is that it has shown great value for data assimilation and for operational forecasts. Another advantage is that it is computationally inexpensive, which makes it suitable for real-time retrievals. The VAD analysis has been applied to the HIWRAP data collected during NASA’s Genesis and Rapid Intensification Processes (GRIP) mission. The traditional dual-Doppler analysis for deriving wind fields in the nadir plane is also presented and is compared with the VAD analysis. The results show that the along-track winds from the VAD technique and dual-Doppler analysis agree in general. The VAD horizontal winds capture the mean vortex structure of two tropical cyclones, and they are in general agreement with winds from nearby dropsondes. Several assumptions are made for the VAD technique. These assumptions include a stationary platform for each HIWRAP scan and constant vertical velocity of the hydrometeors along each complete scan. As a result, the VAD technique can produce appreciable errors in regions of deep convection such as the eyewall, whereas in stratiform regions the retrieval errors are minimal. Despite these errors, the VAD technique can still adequately capture the larger-scale structure of the hurricane vortex given a sufficient number of flight passes over the storm.

Instrument configuration for dual-Doppler lidar coplanar scans: METCRAX II

The second Meteor Crater Experiment (METCRAX II) was designed to study downslope-windstorm-type flows occurring at the Barringer Meteorite Crater in Arizona. Two Doppler wind lidars were deployed to perform a coplanar dual-Doppler lidar analysis to capture the two-dimensional (2-D) vertical structure of these flows in the crater basin. This type of analysis allows the flow to be resolved on a 2-D Cartesian grid constructed in the range height indicator scan overlap region. Previous studies have shown that the dominant error in the coplanar dual-Doppler analysis mentioned above is due to the under sampling of radial velocities. Hence, it is necessary to optimize the setup and choose a scan strategy that minimizes the under sampling of radial velocities and provides a good spatial as well as temporal coverage of these short-lived events. A lidar simulator was developed using a large Eddy simulation wind field to optimize the lidar parameters for METCRAX II field experiment. A retrieval technique based on the weighted least squares technique with weights calculated based on the relative location of the lidar range gate centers to the grid intersection point was developed. The instrument configuration was determined by comparing the simulator retrievals to the background wind field and taking into account the limitations of commercially available lidars.