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.

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.

Tornadogenesis in a Simulated Mesovortex within a Mesoscale Convective System

2012 ◽  
Vol 69 (11) ◽  
pp. 3372-3390 ◽  
Author(s):  
Alexander D. Schenkman ◽  
Ming Xue ◽  
Alan Shapiro
Keyword(s):  
Three Dimensional ◽  
Mesoscale Convective System ◽  
Surface Friction ◽  
Convective System ◽  
Grid Spacing ◽  
Near Surface ◽  
Advanced Regional Prediction System ◽  
Low Level ◽  
Regional Prediction ◽  
Mesoscale Convective

Abstract The Advanced Regional Prediction System (ARPS) is used to simulate a tornadic mesovortex with the aim of understanding the associated tornadogenesis processes. The mesovortex was one of two tornadic mesovortices spawned by a mesoscale convective system (MCS) that traversed southwestern and central Oklahoma on 8–9 May 2007. The simulation used 100-m horizontal grid spacing, and is nested within two outer grids with 400-m and 2-km grid spacing, respectively. Both outer grids assimilate radar, upper-air, and surface observations via 5-min three-dimensional variational data assimilation (3DVAR) cycles. The 100-m grid is initialized from a 40-min forecast on the 400-m grid. Results from the 100-m simulation provide a detailed picture of the development of a mesovortex that produces a submesovortex-scale tornado-like vortex (TLV). Closer examination of the genesis of the TLV suggests that a strong low-level updraft is critical in converging and amplifying vertical vorticity associated with the mesovortex. Vertical cross sections and backward trajectory analyses from this low-level updraft reveal that the updraft is the upward branch of a strong rotor that forms just northwest of the simulated TLV. The horizontal vorticity in this rotor originates in the near-surface inflow and is caused by surface friction. An additional simulation with surface friction turned off does not produce a rotor, strong low-level updraft, or TLV. Comparison with previous two-dimensional numerical studies of rotors in the lee of mountains shows striking similarities to the rotor formation presented herein. The findings of this study are summarized in a four-stage conceptual model for tornadogenesis in this case that describes the evolution of the event from mesovortexgenesis through rotor development and finally TLV genesis and intensification.

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.

Prediction of Tornado-Like Vortex (TLV) Embedded in the 8 May 2003 Oklahoma City Tornadic Supercell Initialized from the Subkilometer Grid Spacing Analysis Produced by the Dual-Resolution GSI-Based EnVar Data Assimilation System

2020 ◽  
Vol 148 (7) ◽  
pp. 2909-2934
Author(s):  
Yongming Wang ◽  
Xuguang Wang
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Potential Temperature ◽  
Intensity Variation ◽  
Oklahoma City ◽  
Grid Spacing ◽  
Near Surface ◽  
Low Level ◽  
Cold Pools ◽  
The Impact

Abstract Explicit forecasts of a tornado-like vortex (TLV) require subkilometer grid spacing because of their small size. Most previous TLV prediction studies started from interpolated kilometer grid spacing initial conditions (ICs) rather than subkilometer grid spacing ICs. The tornadoes embedded in the 8 May 2003 Oklahoma City tornadic supercell are used to understand the impact of IC resolution on TLV predictions. Two ICs at 500-m and 2-km grid spacings are, respectively, produced through an efficient dual-resolution (DR) and a single-coarse-resolution (SCR) EnVar ingesting a 2-km ensemble. Both experiments launch 1-h forecasts at 500-m grid spacing. Diagnostics of data assimilation (DA) cycling reveal DR produces stronger and broader rear-flank cold pools, more intense downdrafts and updrafts with finer scales, and more hydrometeors at high altitudes through accumulated differences between two DA algorithms. Relative differences in DR, compared to SCR, include the integration from higher-resolution analyses, the update for higher-resolution backgrounds, and the propagation of ensemble perturbations along higher-resolution model trajectory. Predictions for storm morphology and cold pools are more realistic in DR than in SCR. The DR-TLV tracks match better with the observed tornado tracks than SCR-TLV in timing of intensity variation, and in duration. Additional experiments suggest 1) the analyzed kinematic variables strongly influence timing of intensity variation through affecting both low-level rear-flank outflow and midlevel updraft; 2) potential temperature analysis by DR extends the second track’s duration consistent with enhanced low-level stretching, delayed broadening large-scale downdraft, and (or) increased near-surface baroclinic vorticity supply; and 3) hydrometeor analyses have little impact on TLV predictions.

scholarly journals Impact of radar data assimilation using WRF three-dimensional variational system, for the simulation of a heavy rainfall case in Central Italy

2013 ◽  
Vol 6 (4) ◽  
pp. 7315-7353
Author(s):  
I. Maiello ◽  
R. Ferretti ◽  
S. Gentile ◽  
M. Montopoli ◽  
E. Picciotti ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Central Italy ◽  
Three Dimensional ◽  
Warm Start ◽  
The Impact ◽  
Dwr Data

Abstract. This work is a first assessment of the role of Doppler Weather radar (DWR) data in a mesoscale model for the prediction of a heavy rainfall. The study analyzes the event occurred during 19–22 May 2008 in the urban area of Rome. The impact of the radar reflectivity and radial velocity acquired from Monte Midia Doppler radar, on the assimilation into the Weather Research Forecasting (WRF) model version 3.2, is discussed. The goal is to improve the WRF high resolution initial condition by assimilating DWR data and using ECMWF analyses as First Guess thus improving the forecast of surface rainfall. Several experiments are performed using different set of Initial Conditions (ECMWF analyses and warm start or cycling) and a different assimilation strategy (3 h-data assimilation cycle). In addition, 3DVAR (three-dimensional variational) sensitivity tests to outer loops are performed for each of the previous experiment to include the non-linearity in the observation operators. In order to identify the best ICs, statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a positive impact on the prediction of the heavy rainfall of this event, both assimilating reflectivity and radial velocity, together with conventional observations. Finally, warm start results in more accurate experiments as well as the outer loops strategy.

External Influences on Nocturnal Thermally Driven Flows in a Deep Valley

2009 ◽  
Vol 48 (1) ◽  
pp. 3-23 ◽  
Author(s):  
Juerg Schmidli ◽  
Gregory S. Poulos ◽  
Megan H. Daniels ◽  
Fotini K. Chow
Keyword(s):  
Measurement Data ◽  
Owens Valley ◽  
Valley Wind ◽  
Advanced Regional Prediction System ◽  
Low Level ◽  
External Influences ◽  
Regional Prediction ◽  
Thermally Driven ◽  
Flow Features ◽  
Flow Evolution

Abstract The dynamics that govern the evolution of nighttime flows in a deep valley, California’s Owens Valley, are analyzed. Measurements from the Terrain-Induced Rotor Experiment (T-REX) reveal a pronounced valley-wind system with often nonclassical flow evolution. Two cases with a weak high pressure ridge over the study area but very different valley flow evolution are presented. The first event is characterized by the appearance of a layer of southerly flow after midnight local time, sandwiched between a thermally driven low-level downvalley (northerly) flow and a synoptic northwesterly flow aloft. The second event is characterized by an unusually strong and deep downvalley jet, exceeding 15 m s−1. The analysis is based on the T-REX measurement data and the output of high-resolution large-eddy simulations using the Advanced Regional Prediction System (ARPS). Using horizontal grid spacings of 1 km and 350 m, ARPS reproduces the observed flow features for these two cases very well. It is found that the low-level along-valley forcing of the valley wind is the result of a superposition of the local thermal forcing and a midlevel (2–2.5 km MSL) along-valley pressure forcing. The analysis shows that the large difference in valley flow evolution derives primarily from differences in the midlevel pressure forcing, and that the Owens Valley is particularly susceptible to these midlevel external influences because of its specific geometry. The results demonstrate the delicate interplay of forces that can combine to determine the valley flow structure on any given night.

scholarly journals Dynamical Influences of Anvil Shading on Simulated Supercell Thunderstorms

2013 ◽  
Vol 141 (8) ◽  
pp. 2802-2820 ◽  
Author(s):  
Jeffrey Frame ◽  
Paul Markowski
Keyword(s):  
Vertical Wind Shear ◽  
Time Of Day ◽  
Surface Fluxes ◽  
Maximum Temperature ◽  
Near Surface ◽  
Advanced Regional Prediction System ◽  
Low Level ◽  
Regional Prediction ◽  
Supercell Thunderstorms ◽  
Gust Front

Abstract Numerical simulations of supercell thunderstorms including parameterized radiative transfer and surface fluxes are performed using the Advanced Regional Prediction System (ARPS) model to investigate how low-level air temperature deficits within anvil shadows affect the simulated storms. The maximum temperature deficits within the modeled cloud shadows are 1.5–2.0 K, which is only about half that previously observed. Within the shadows, the loss of strong solar heating cools and stabilizes the near-surface layer, which suppresses vertical mixing and modifies the near-surface vertical wind shear. In a case of a stationary storm, the enhanced easterly shear present beneath the anvil leads to a thinning of the outflow layer and corresponding acceleration of the rear-flank gust front far ahead of the overlying updraft, weakening the low-level mesocyclone. It is further shown that the direct absorption and emission of radiation by clouds does not significantly affect the simulated supercells. Varying the time of day of model initialization does not prevent the simulated storms from weakening. This behavior is mirrored for storms that slowly move along the major axis of the anvil shadow. If the rear-flank gust front moves into the anvil shadow and the updraft moves normal to the shadow (i.e., northward movement of the updraft), cyclic periods of intensification and decay can result, although this result is likely highly dependent on the storm-relative wind profile. If the gust front does not advance into the shaded region (i.e., southward movement), or if the storm moves rapidly, the storm is relatively unaffected by anvil shading because the rear-flank gust front speed and outflow depth remain relatively unchanged.

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.

scholarly journals OSSEs for an Ensemble 3DVAR Data Assimilation System with Radar Observations of Convective Storms

2016 ◽  
Vol 73 (6) ◽  
pp. 2403-2426 ◽  
Author(s):  
Jidong Gao ◽  
Chenghao Fu ◽  
David J. Stensrud ◽  
John S. Kain
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Initial Conditions ◽  
Positive Impact ◽  
Three Dimensional ◽  
Field Analysis ◽  
Cold Pool ◽  
Ensemble Forecasts ◽  
Convective Scale

Abstract An ensemble of the three-dimensional variational data assimilation (En3DA) method for convective-scale weather has been developed. It consists of an ensemble of three-dimensional variational data assimilations and forecasts in which member differences are introduced by perturbing initial conditions and/or observations, and it uses flow-dependent error covariances generated by the ensemble forecasts. The method is applied to the assimilation of simulated radar data for a supercell storm. Results indicate that the flow-dependent ensemble covariances are effective in enabling convective-scale analyses, as the most important features of the simulated storm, including the low-level cold pool and midlevel mesocyclone, are well analyzed. Several groups of sensitivity experiments are conducted to test the robustness of the method. The first group demonstrates that incorporating a mass continuity equation as a weak constraint into the En3DA algorithm can improve the quality of the analyses when radial velocity observations contain large errors. In the second group of experiments, the sensitivity of analyses to the microphysical parameterization scheme is explored. Results indicate that the En3DA analyses are quite sensitive to differences in the microphysics scheme, suggesting that ensemble forecasts with multiple microphysics schemes could reduce uncertainty related to model physics errors. Experiments also show that assimilating reflectivity observations can reduce spinup time and that it has a small positive impact on the quality of the wind field analysis. Of the threshold values tested for assimilating reflectivity observations, 15 dBZ provides the best analysis. The final group of experiments demonstrates that it is not necessary to perturb radial velocity observations for every ensemble number in order to improve the quality of the analysis.

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.

Sign in / Sign up

Export Citation Format

Share Document