scholarly journals Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model

2013 ◽  
Vol 2013 ◽  
pp. 1-18
Author(s):  
Edward Natenberg ◽  
Jidong Gao ◽  
Ming Xue ◽  
Frederick H. Carr
Keyword(s):  
Doppler Radar ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Radar Data ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Upper Level ◽  
Using Data ◽  
Nwp Model ◽  
The Impact

A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

Impact of Configurations of Rapid Intermittent Assimilation of WSR-88D Radar Data for the 8 May 2003 Oklahoma City Tornadic Thunderstorm Case

2007 ◽  
Vol 135 (2) ◽  
pp. 507-525 ◽  
Author(s):  
Ming Hu ◽  
Ming Xue
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Initial Conditions ◽  
Radar Data ◽  
Oklahoma City ◽  
Advanced Regional Prediction System ◽  
Initial Stage ◽  
Regional Prediction ◽  
Cloud Temperature ◽  
Adjustment Scheme

Abstract Various configurations of the intermittent data assimilation procedure for Level-II Weather Surveillance Radar-1988 Doppler radar data are examined for the analysis and prediction of a tornadic thunderstorm that occurred on 8 May 2003 near Oklahoma City, Oklahoma. Several tornadoes were produced by this thunderstorm, causing extensive damages in the south Oklahoma City area. Within the rapidly cycled assimilation system, the Advanced Regional Prediction System three-dimensional variational data assimilation (ARPS 3DVAR) is employed to analyze conventional and radar radial velocity data, while the ARPS complex cloud analysis procedure is used to analyze cloud and hydrometeor fields and adjust in-cloud temperature and moisture fields based on reflectivity observations and the preliminary analysis of the atmosphere. Forecasts for up to 2.5 h are made from the assimilated initial conditions. Two one-way nested grids at 9- and 3-km grid spacings are employed although the assimilation configuration experiments are conducted for the 3-km grid only while keeping the 9-km grid configuration the same. Data from the Oklahoma City radar are used. Different combinations of the assimilation frequency, in-cloud temperature adjustment schemes, and the length and coverage of the assimilation window are tested, and the results are discussed with respect to the length and evolution stage of the thunderstorm life cycle. It is found that even though the general assimilation method remains the same, the assimilation settings can significantly impact the results of assimilation and the subsequent forecast. For this case, a 1-h-long assimilation window covering the entire initial stage of the storm together with a 10-min spinup period before storm initiation works best. Assimilation frequency and in-cloud temperature adjustment scheme should be set carefully to add suitable amounts of potential energy during assimilation. High assimilation frequency does not necessarily lead to a better result because of the significant adjustment during the initial forecast period. When a short assimilation window is used, covering the later part of the initial stage of storm and using a high assimilation frequency and a temperature adjustment scheme based on latent heat release can quickly build up the storm and produce a reasonable analysis and forecast. The results also show that when the data from a single Doppler radar are assimilated with properly chosen assimilation configurations, the model is able to predict the evolution of the 8 May 2003 Oklahoma City tornadic thunderstorm well for up to 2.5 h. The implications of the choices of assimilation settings for real-time applications are discussed.

scholarly journals Impact of the Dual-Polarization Doppler Radar Data on Two Convective Storms with a Warm-Rain Radar Forward Operator

2012 ◽  
Vol 140 (7) ◽  
pp. 2147-2167 ◽  
Author(s):  
Xuanli Li ◽  
John R. Mecikalski
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Radar Data ◽  
Dual Polarization ◽  
Convective Storms ◽  
Warm Rain ◽  
Mesoscale Convective ◽  
Differential Reflectivity ◽  
The Impact

Abstract The dual-polarization (dual pol) Doppler radar can transmit/receive both horizontally and vertically polarized power returns. The dual-pol radar measurements have been shown to provide a more accurate precipitation estimate compared to traditional radars. In this study, the horizontal reflectivity ZH, differential reflectivity ZDR, specific differential phase KDP, and radial velocity VR collected by the C-band Advanced Radar for Meteorological and Operational Research (ARMOR) are assimilated for two convective storms. A warm-rain scheme is constructed to assimilate ZH, ZDR, and KDP data using the three-dimensional variational data assimilation (3DVAR) system with the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The main goals of this study are first to demonstrate and compare the impact of various dual-pol variables in initialization of real case convective storms and second to test how the dual-pol fields may be better used with a 3DVAR system. The results show that the ZH, ZDR, KDP, and VR data substantially improve the initial condition for two mesoscale convective storms. Significant positive impacts on short-term forecast are obtained for both storms. Additionally, KDP and ZDR data assimilation is shown to be superior to ZH and ZDR and ZH-only data assimilation when the warm-rain microphysics is adopted. With the ongoing upgrade of the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network to include dual-pol capabilities (started in early 2011), the findings from this study can be a helpful reference for utilizing the dual-pol radar data in numerical simulations of severe weather and related quantitative precipitation forecasts.

scholarly journals A Doppler Radar Emulator with an Application to the Detectability of Tornadic Signatures

2007 ◽  
Vol 24 (12) ◽  
pp. 1973-1996 ◽  
Author(s):  
Ryan M. May ◽  
Michael I. Biggerstaff ◽  
Ming Xue
Keyword(s):  
Pulse Propagation ◽  
Doppler Radar ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Advanced Regional Prediction System ◽  
Adaptive Sensing ◽  
Regional Prediction ◽  
Sampling Intervals ◽  
Half Power ◽  
The Impact

Abstract A Doppler radar emulator was developed to simulate the expected mean returns from scanning radar, including pulse-to-pulse variability associated with changes in viewing angle and atmospheric structure. Based on the user’s configuration, the emulator samples the numerical simulation output to produce simulated returned power, equivalent radar reflectivity, Doppler velocity, and Doppler spectrum width. The emulator is used to evaluate the impact of azimuthal over- and undersampling, gate spacing, velocity and range aliasing, antenna beamwidth and sidelobes, nonstandard (anomalous) pulse propagation, and wavelength-dependent Rayleigh attenuation on features of interest. As an example, the emulator is used to evaluate the detection of the circulation associated with a tornado simulated within a supercell thunderstorm by the Advanced Regional Prediction System (ARPS). Several metrics for tornado intensity are examined, including peak Doppler velocity and axisymmetric vorticity, to determine the degradation of the tornadic signature as a function of range and azimuthal sampling intervals. For the case of a 2° half-power beamwidth radar, like those deployed in the first integrated project of the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), the detection of the cyclonic shear associated with this simulated tornado will be difficult beyond the 10-km range, if standard metrics such as azimuthal gate-to-gate shear from a single radar are used for detection.

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

2009 ◽  
Vol 137 (4) ◽  
pp. 1230-1249 ◽  
Author(s):  
Corey K. Potvin ◽  
Alan Shapiro ◽  
Tian-You Yu ◽  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
Cost Function ◽  
Wind Field ◽  
Doppler Radar ◽  
Radar Data ◽  
Horizontal Wind ◽  
Order Model ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Objective Detection ◽  
Low Order

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

The Effect of Topographic Variability on Initial Condition Sensitivity of Low-Level Wind Forecasts. Part II: Experiments Using Real Terrain and Observations

2013 ◽  
Vol 141 (7) ◽  
pp. 2156-2172 ◽  
Author(s):  
Paul E. Bieringer ◽  
Peter S. Ray ◽  
Andrew J. Annunzio
Keyword(s):  
Doppler Radar ◽  
Initial Conditions ◽  
Surface Wind ◽  
Forecast Accuracy ◽  
Radar Data ◽  
Model Verification ◽  
Initial Condition ◽  
Terrain Elevation ◽  
The Impact ◽  
Topographic Variability

Abstract A study by Bieringer et al., which is Part I of this two-part study, demonstrated analytically using the shallow-water equations and numerically in controlled experiments that the presence of terrain can result in an enhancement of sensitivities to initial condition adjustments. The increased impact of adjustments to initial conditions corresponds with gradients in the flow field induced by the presence of the terrain obstacle. In cross-barrier flow situations the impact of the initial condition adjustments on the final forecast increases linearly as the height of the terrain obstacle increases. While this property associated with initial condition perturbations may be present in an analytic and controlled numerical environment, it is often difficult to realize these benefits in a more operationally realistic setting. This study extends the prior work to a situation with actual terrain, Doppler radar wind observations over the terrain, and observations from a surface mesonet for model verification. The results indicate that the downstream surface wind forecast was improved more when the initial conditions adjusted through the assimilation of Doppler radar data originated from areas with terrain gradients than from regions where the terrain was relatively flat. This result is consistent with the findings presented in Part I and suggests that when varying terrain elevation is present upstream of a target forecast area, a greater benefit (in terms of forecast accuracy) can be made by targeting additional observations in the regions containing variable terrain than regions where the terrain is relatively flat.

Impacts of 4DVAR Assimilation of Airborne Doppler Radar Observations on Numerical Simulations of the Genesis of Typhoon Nuri (2008)

2014 ◽  
Vol 53 (10) ◽  
pp. 2325-2343 ◽  
Author(s):  
Zhan Li ◽  
Zhaoxia Pu ◽  
Juanzhen Sun ◽  
Wen-Chau Lee
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Numerical Simulations ◽  
Doppler Radar ◽  
Initial Conditions ◽  
Radar Data ◽  
Radar Observations ◽  
Wind Analysis ◽  
The Impact ◽  
Airborne Doppler Radar

AbstractThe Weather Research and Forecasting Model and its four-dimensional variational data assimilation (4DVAR) system are employed to examine the impact of airborne Doppler radar observations on predicting the genesis of Typhoon Nuri (2008). Electra Doppler Radar (ELDORA) airborne radar data, collected during the Office of Naval Research–sponsored Tropical Cyclone Structure 2008 field experiment, are used for data assimilation experiments. Two assimilation methods are evaluated and compared, namely, the direct assimilation of radar-measured radial velocity and the assimilation of three-dimensional wind analysis derived from the radar radial velocity. Results show that direct assimilation of radar radial velocity leads to better intensity forecasts, as this process enhances the development of convective systems and improves the inner-core structure of Nuri, whereas assimilation of the radar-retrieved wind analysis is more beneficial for tracking forecasts, as it results in improved environmental flows. The assimilation of both the radar-retrieved wind and the radial velocity can lead to better forecasts in both intensity and tracking, if the radial velocity observations are assimilated first and the retrieved winds are then assimilated in the same data assimilation window. In addition, experiments with and without radar data assimilation led to developing and nondeveloping disturbances in numerical simulations of Nuri’s genesis. The improved initial conditions and forecasts from the data assimilation imply that the enhanced midlevel vortex and moisture conditions are favorable for the development of deep convection in the center of the pouch and eventually contribute to Nuri’s genesis. The improved simulations of the convection and associated environmental conditions produce enhanced upper-level warming in the core region and lead to the drop in sea level pressure.

scholarly journals The Analysis and Prediction of the 8–9 May 2007 Oklahoma Tornadic Mesoscale Convective System by Assimilating WSR-88D and CASA Radar Data Using 3DVAR

2011 ◽  
Vol 139 (1) ◽  
pp. 224-246 ◽  
Author(s):  
Alexander D. Schenkman ◽  
Ming Xue ◽  
Alan Shapiro ◽  
Keith Brewster ◽  
Jidong Gao
Keyword(s):  
Three Dimensional ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Squall Line ◽  
Convective System ◽  
Data Types ◽  
Advanced Regional Prediction System ◽  
Engineering Research ◽  
Regional Prediction ◽  
Mesoscale Convective

Abstract The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution numerical simulations of a mesoscale convective system and associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8–9 May 2007. The simulation uses a 1000 km × 1000 km domain with 2-km horizontal grid spacing. The ARPS three-dimensional variational data assimilation (3DVAR) is used to assimilate a variety of data types. All experiments assimilate routine surface and upper-air observations as well as wind profiler and Oklahoma Mesonet data over a 1-h assimilation window. A subset of experiments assimilates radar data. Cloud and hydrometeor fields as well as in-cloud temperature are adjusted based on radar reflectivity data through the ARPS complex cloud analysis procedure. Radar data are assimilated from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network as well as from the Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA) network of four X-band Doppler radars. Three-hour forecasts are launched at the end of the assimilation window. The structure and evolution of the forecast MCS and LEV are markedly better throughout the forecast period in experiments in which radar data are assimilated. The assimilation of CASA radar data in addition to WSR-88D data increases the structural detail of the modeled squall line and MCS at the end of the assimilation window, which appears to yield a slightly better forecast track of the LEV.

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

2012 ◽  
Vol 29 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Corey K. Potvin ◽  
Alan Shapiro ◽  
Ming Xue
Keyword(s):  
Vertical Velocity ◽  
Three Dimensional ◽  
Mass Conservation ◽  
Vorticity Equation ◽  
Vertical Vorticity ◽  
Advanced Regional Prediction System ◽  
Supercell Storm ◽  
Radar Networks ◽  
Regional Prediction ◽  
The Impact

Abstract One of the greatest challenges to dual-Doppler retrieval of the vertical wind is the lack of low-level divergence information available to the mass conservation constraint. This study examines the impact of a vertical vorticity equation constraint on vertical velocity retrievals when radar observations are lacking near the ground. The analysis proceeds in a three-dimensional variational data assimilation (3DVAR) framework with the anelastic form of the vertical vorticity equation imposed along with traditional data, mass conservation, and smoothness constraints. The technique is tested using emulated radial wind observations of a supercell storm simulated by the Advanced Regional Prediction System (ARPS), as well as real dual-Doppler observations of a supercell storm that occurred in Oklahoma on 8 May 2003. Special attention is given to procedures to evaluate the vorticity tendency term, including spatially variable advection correction and estimation of the intrinsic evolution. Volume scan times ranging from 5 min, typical of operational radar networks, down to 30 s, achievable by rapid-scan mobile radars, are considered. The vorticity constraint substantially improves the vertical velocity retrievals in our experiments, particularly for volume scan times smaller than 2 min.

Numerical Prediction of the 8 May 2003 Oklahoma City Tornadic Supercell and Embedded Tornado Using ARPS with the Assimilation of WSR-88D Data

2014 ◽  
Vol 29 (1) ◽  
pp. 39-62 ◽  
Author(s):  
Ming Xue ◽  
Ming Hu ◽  
Alexander D. Schenkman
Keyword(s):  
Radial Velocity ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Oklahoma City ◽  
Similar Degree ◽  
Advanced Regional Prediction System ◽  
Low Level ◽  
Regional Prediction ◽  
Observed Damage ◽  
Reflectivity Data

Abstract The 8 May 2003 Oklahoma City, Oklahoma, tornadic supercell is predicted with the Advanced Regional Prediction System (ARPS) model using four nested grids with 9-km, 1-km, 100-m, and 50-m grid spacings. The Oklahoma City Weather Surveillance Radar-1988 Doppler (WSR-88D) radial velocity and reflectivity data are assimilated through the ARPS three-dimensional variational data assimilation (3DVAR) and cloud analysis on the 1-km grid to generate a set of initial conditions that includes a well-analyzed supercell and associated low-level mesocyclone. Additional 1-km experiments show that the use of radial velocity and the proper use of a divergence constraint in the 3DVAR play an important role in the establishment of the low-level mesocyclone during the assimilation and forecast. Assimilating reflectivity data alone failed to predict the mesocyclone intensification. The 100-m grid starts from the interpolated 1-km control initial conditions, while the further nested 50-m grid starts from the 20-min forecast on the 100-m grid. The forecasts on both grids cover the entire period of the observed tornado outbreak and successfully capture the development of tornadic vortices. The intensity of a tornado on the 50-m grid reaches the high end of category 3 on the Fujita scale (F3), while the corresponding simulated tornado on the 100-m grid reaches F2 intensity. The timing of the tornadogenesis on both grids agrees with the observations very well, although the predicted tornado was slightly weaker and somewhat shorter lived. The predicted tornado track parallels the observed damage track although it is displaced northward by about 8 km. The predicted tornado vortices have realistic structures similar to those documented in previous theoretical, idealized modeling and some observational studies. The prediction of an observed tornado in a supercell with a similar degree of realism has not been achieved before.

The Multiple-Vortex Structure of the El Reno, Oklahoma, Tornado on 31 May 2013

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Rapid Scan ◽  
X Band ◽  
Close Range ◽  
Formation And Evolution ◽  
Using Data ◽  
Secondary Vortices ◽  
The Right ◽  
Gust Front

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.

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