Abstract

A 50-m-grid-spacing Advanced Regional Prediction System (ARPS) simulation of the 8 May 2003 Oklahoma City tornadic supercell is examined. A 40-min forecast run on the 50-m grid produces two F3-intensity tornadoes that track within 10 km of the location of the observed long-track F4-intensity tornado.

The development of both simulated tornadoes is analyzed to determine the processes responsible for tornadogenesis. Trajectory-based analyses of vorticity components and their time evolution reveal that tilting of low-level frictionally generated horizontal vorticity plays a dominant role in the development of vertical vorticity near the ground. This result represents the first time that such a mechanism has been shown to be important for generating near-surface vertical vorticity leading to tornadogenesis.

A sensitivity simulation run with surface drag turned off was found to be considerably different from the simulation with drag included. A tornado still developed in the no-drag simulation, but it was much shorter lived and took a substantially different track than the observed tornadoes as well as the simulated tornadoes in the drag simulation. Tilting of baroclinic vorticity in an outflow surge may have played a role in tornadogenesis in the no-drag simulation.

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.

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.

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.

Abstract

To investigate the effect of surface drag on tornadogenesis, a pair of idealized simulations is conducted with 50-m horizontal grid spacing. In the first experiment (full-wind drag case), surface drag is applied to the full wind; in the second experiment (environmental drag case), drag is applied only to the background environmental wind, with storm-induced perturbations unaffected. The simulations are initialized using a thermal bubble within a horizontally homogeneous background environment that has reached a balance between the pressure gradient, Coriolis, and frictional forces. The environmental sounding is derived from a prior simulation of the 3 May 1999 Oklahoma tornado outbreak but modified to account for near-ground frictional effects. In the full-wind drag experiment, a tornado develops around 25 min into the simulation and persists for more than 10 min; in the environmental-only drag experiment, no tornado occurs. Three distinct mechanisms are identified by which surface drag influences tornadogenesis. The first mechanism is the creation by drag of near-ground vertical wind shear (and associated horizontal vorticity) in the background environment. The second mechanism is generation of near-ground crosswise horizontal vorticity by drag on the storm scale as air accelerates into the low-level mesocyclone; this vorticity is subsequently exchanged into the streamwise direction and eventually tilted into the vertical. The third mechanism is frictional enhancement of horizontal convergence, which strengthens the low-level updraft and stretching of vertical vorticity. The second and third mechanisms are found to work together to produce a tornado, while baroclinic vorticity plays a negligible role.

Abstract

A high-resolution simulation of the 8 May 2003 Oklahoma tornadic supercell is analyzed to determine the origin of internal outflow surges within the low-level cold pool. The analyzed simulation has 50-m horizontal grid spacing and is quadruply nested within larger, lower-resolution domains that were initialized via three-dimensional variational data assimilation (3DVAR) of radar and other observations. The high-resolution simulation produces two tornadoes that track in close proximity to the observed tornado on 8 May 2003. The authors’ previous study determined that an internal outflow surge instigated tornadogenesis for the first tornado in this simulation but the cause of this internal outflow surge was unclear.

In this study, the vertical momentum equation is analyzed along backward trajectories that are initialized within the tornado-triggering internal outflow surge. The analysis reveals that the internal outflow surge is forced by the dynamic part of the vertical pressure gradient. Further examination reveals that the dynamic forcing is the result of a high pressure perturbation in an area of stagnating flow on the west and northwest sides of the low-level (below ~3 km AGL) mesocyclone. This region of high perturbation pressure is unsteady and forces several other warm internal outflow surges on the west side of the tornado. Cold internal outflow surges also occur later in the simulation and are shown to be buoyantly forced by evaporation and water loading in heavy precipitation.

Abstract

The impact of radar and Oklahoma Mesonet data assimilation on the prediction of mesovortices in a tornadic mesoscale convective system (MCS) is examined. The radar data come from the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere’s (CASA) IP-1 radar network. The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution predictions of an MCS and the associated cyclonic line-end vortex that spawned several tornadoes in central Oklahoma on 8–9 May 2007, while the ARPS three-dimensional variational data assimilation (3DVAR) system in combination with a complex cloud analysis package is used for the data analysis. A set of data assimilation and prediction experiments are performed on a 400-m resolution grid nested inside a 2-km grid, to examine the impact of radar data on the prediction of meso-γ-scale vortices (mesovortices). An 80-min assimilation window is used in radar data assimilation experiments. An additional set of experiments examines the impact of assimilating 5-min data from the Oklahoma Mesonet in addition to the radar data.

Qualitative comparison with observations shows highly accurate forecasts of mesovortices up to 80 min in advance of their genesis are obtained when the low-level shear in advance of the gust front is effectively analyzed. Accurate analysis of the low-level shear profile relies on assimilating high-resolution low-level wind information. The most accurate analysis (and resulting prediction) is obtained in experiments that assimilate low-level radial velocity data from the CASA radars. Assimilation of 5-min observations from the Oklahoma Mesonet has a substantial positive impact on the analysis and forecast when high-resolution low-level wind observations from CASA are absent; when the low-level CASA wind data are assimilated, the impact of Mesonet data is smaller. Experiments that do not assimilate low-level wind data from CASA radars are unable to accurately resolve the low-level shear profile and gust front structure, precluding accurate prediction of mesovortex development.

Abstract

Vortex stretching by intense upward accelerations is a critical process for tornadogenesis and maintenance. Two high-resolution (250-m grid spacing) real-data simulations of the 3 May 1999 Oklahoma City, Oklahoma, supercell and associated tornadoes, using single- and triple-moment microphysics parameterization schemes, respectively, are examined. Microphysical, thermodynamic, and dynamic impacts on the vertical accelerations near and within simulated tornado-like vortices (TLVs) are analyzed. Systematic differences in behavior of the TLVS between the two experiments are found; the TLV in the triple-moment simulation is substantially more intense and longer lived than in the single-moment case. The triple-moment scheme in this case produces less rain and hail mass in the low levels and drop size distributions of rain shifted toward larger drops, relative to the single-moment scheme, leading to less latent cooling and warmer outflow. Trajectory analyses reveal that more parcels entering the TLV in the triple-moment simulation have a history of dynamically induced descent, whereas buoyantly driven descent is more prevalent in the single-moment experiment. It is found that the intensity and longevity of the TLV are tied to weaker negative or neutral thermal buoyancy in the air flowing into the TLV in the triple-moment case, consistent with previous observational and modeling studies. Finally, the contribution to buoyancy from pressure perturbations is found to be of prime importance within the TLV, where strong negative pressure perturbations lead to substantial positive buoyancy. This contribution compensates for the slight negative thermal buoyancy and negative dynamic pressure gradient acceleration in the triple-moment case.

Abstract

Observation 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.