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Daniel R. Chavas and Daniel T. Dawson II

Abstract

This work develops a theoretical model for steady thermodynamic and kinematic profiles for severe convective storm environments, building off the two-layer static energy framework developed in work by Agard and Emanuel. The model is phrased in terms of static energy, and it allows for independent variation of the boundary layer and free troposphere separated by a capping inversion. An algorithm is presented to apply the model to generate a sounding for numerical simulations of severe convective storms, and the model is compared and contrasted with that of Weisman and Klemp. The model is then fit to a case-study sounding associated with the 3 May 1999 tornado outbreak, and its potential utility is demonstrated via idealized numerical simulation experiments. A long-lived supercell is successfully simulated with the historical sounding but not the analogous theoretical sounding. Two types of example experiments are then performed that do simulate a long-lived supercell: 1) a semitheoretical experiment in which a portion of the theoretical sounding is modified to match the real sounding (low-level moisture); 2) a fully theoretical experiment in which a model physical parameter is modified (free-tropospheric relative humidity). Overall, the construction of this minimal model is flexible and amenable to additional modifications as needed. The model offers a novel framework that may be useful for testing how severe convective storms depend on the vertical structure of the hydrostatic environment, as well as for linking variability in these environments to the physical processes that produce them within the climate system.

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Daniel T. Dawson II and Ming Xue

Abstract

High-resolution explicit forecasts using the Advanced Regional Prediction System (ARPS) of the 15–16 June 2002 mesoscale convective system (MCS) that occurred over the U.S. central and southern plains during the International H2O Project (IHOP_2002) field experiment period are performed. The forecasts are designed to investigate the impact of mesoscale and convective-scale data on the initialization and prediction of an organized convective system. Specifically, the forecasts test the impact of special mesoscale surface and upper-air data collected by, but not necessarily specific to, IHOP_2002 and of level-II data from multiple Weather Surveillance Radar-1988 Doppler radars. The effectiveness of using 30-min assimilation cycles with the use of a complex cloud-analysis procedure and high-temporal-resolution surface data is also examined. The analyses and forecasts employ doubly nested grids, with resolutions of 9 and 3 km. Emphasis is placed on the solutions of the 3-km grid. In all forecasts, a strong, well-defined bow-shaped MCS is produced with structure and behavior similar to those of the observed system. Verification of these forecasts through both regular and phase-shifted equitable threat scores of the instantaneous composite reflectivity fields indicate that the use of the complex cloud analysis has the greatest positive impact on the prediction of the MCS, primarily by removing the otherwise needed “spinup” time of convection in the model. The impact of additional data networks is smaller and is reflected mainly in reducing the spinup time of the MCS too. The use of intermittent assimilation cycles appears to be quite beneficial when the assimilation window covers a time period when the MCS is present. Difficulties with verifying weather systems with high spatial and temporal intermittency are also discussed, and the use of both regular and spatially shifted equitable threat scores is found to be very beneficial in assessing the quality of the forecasts.

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Heather Dawn Reeves and Daniel T. Dawson II

Abstract

Several lake-effect-snow forecasts are compared to assess how the choice of microphysical parameterization affects quantitative precipitation forecasting (QPF). Eight different schemes, with different numbers of moments and categories of hydrometeors, are considered. Half of the schemes are in the steady regime (so named because the precipitation rates are nearly constant with time), and the remaining experiments are in the unsteady regime, which has a high temporal variation in precipitation. The steady-regime members have broader precipitation shields and 24-h accumulations that range from 43 to 50 mm. In the unsteady regime, the precipitation shields are narrower, leading to higher accumulations (ranging from 55 to 94 mm). These differences are the result of lower terminal velocities υt in the steady regime, which allows for relofting or suspension of hydrometeors (assuming the vertical velocity is sufficiently large) and, hence, a longer in-cloud residence time and stronger downstream transport. In the six-category experiments, low υt values in the steady regime occur in conjunction with a lower production of graupel, which is primarily due to less accretion of rain by snow. In the five-category experiments, differences are due to the way υt is functionally dependent on environmental temperature and the degree of riming, with the steady regime having a more conservative relation. The steady regime compares better to available observations, although both have notable forecast errors.

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Daniel T. Dawson II, Brett Roberts, and Ming Xue

Abstract

In idealized, horizontally homogeneous, cloud model simulations of convective storms, the action of surface friction can substantially modify the near-ground environmental wind profile over time owing to the lack of a large-scale pressure gradient force to balance the frictional force together with the Coriolis force. This situation is undesirable for many applications where the impact of an unchanging environmental low-level wind shear on the simulated storm behavior is the focus of investigation, as it introduces additional variability in the experiment and accordingly complicates interpretation of the results. Partly for this reason, many researchers have opted to perform simulations with free-slip lower boundary conditions, which with appropriate boundary conditions allows for more precise control of the large-scale environmental wind profile. Yet, some recent studies have advocated important roles of surface friction in storm dynamics. Here, a simple method is introduced to effectively maintain any chosen environmental wind profile in idealized storm simulations in the presence of surface friction and both resolved and subgrid-scale turbulent mixing. The method is demonstrated through comparisons of simulations of a tornadic supercell with and without surface friction and with or without invoking the new method. The method is compared with similar techniques in the literature and potential extensions and other applications are discussed.

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Robin L. Tanamachi, Daniel T. Dawson II, and Loran Carleton Parker

Abstract

A summer course has been developed at Purdue University that leverages students’ intrinsic desire to observe tornadoes as a motivator for learning severe storms forecasting. Relative to previous “storm chasing” courses described in the literature, the Students of Purdue Observing Tornadic Thunderstorms for Research (SPOTTR) course is enhanced by active learning exercises, career exploration activities, and the inclusion of research-grade meteorological instrumentation in order to provide an authentic in-field experiential learning scenario. After teaching severe weather forecasting skills and deployment techniques for several meteorological instruments (such as a mobile radar, radiosondes, and disdrometers), the instructors then guide the students on a 1-week field trip to the Great Plains, where the group executes a miniature field campaign to collect high-quality meteorological observations in and near severe storms. On days with no targetable severe weather, the participants visit sites deemed beneficial to the students’ professional development. The final week of the course is spent performing retrospective case studies based on the observations collected, and distilling lessons learned. Surveys given to SPOTTR students show that students’ understanding of severe storms forecasting, technical skills, and career aspirations all improved as a result of having participated in the SPOTTR course, affirming the efficacy of the course design.

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Alexander D. Schenkman, Ming Xue, and Daniel T. Dawson II

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.

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Marcus Johnson, Youngsun Jung, Daniel T. Dawson II, and Ming Xue

Abstract

Microphysics parameterization becomes increasingly important as the model grid spacing increases toward convection-resolving scales. The performance of several partially or fully two-moment (2M) schemes within the Weather Research and Forecasting (WRF) Model, version 3.5.1, chosen because of their well-documented advantages over one-moment (1M) schemes, is evaluated with respect to their ability in producing the well-known polarimetric radar signatures found within supercell storms. Such signatures include the Z DR and K DP columns, the Z DR arc, the midlevel Z DR and ρ HV rings, the hail signature in the forward-flank downdraft, and the K DP foot. Polarimetric variables are computed from WRF Model output using a polarimetric radar simulator. It is found that microphysics schemes with a 1M rimed-ice category are unable to simulate the Z DR arc, despite containing a 2M rain category. It is also found that a hail-like rimed-ice category (in addition to graupel) may be necessary to reproduce the observed hail signature. For the microphysics schemes that only contain a graupel-like rimed-ice category, only very wet graupel particles are able to reach the lowest model level, which did not adequately reduce Z DR in this signature. The most realistic signatures overall are found with microphysics schemes that are fully 2M with a separate hail category.

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Daniel T. Dawson II, Edward R. Mansell, and Matthew R. Kumjian

Abstract

Several recent studies have implicated vertical wind shear in producing steady-state size sorting of a distribution of hydrometeors falling at their terminal velocity, which varies as a function of hydrometeor diameter. In particular, this mechanism has been invoked to explain both the strength and storm-relative orientation of the commonly observed differential reflectivity (Z DR) arc in supercell thunderstorms. However, the actual role of the shear has not been fully clarified. In this study, a simple analytical model is used to show that the fundamental source of size sorting is the storm-relative wind field itself and, in particular, its mean taken over the depth of the sorting layer. Wind shear is only strictly required for producing sustained size sorting in the special but common case of a precipitation source having a motion that lies on the hodograph (such as with the environmental winds at the source level). In supercells, the precipitation source (the rotating updraft) does not necessarily move with the winds at any level. It is shown that this off-hodograph propagation and the associated storm-relative mean wind is responsible for the positive correlation of size-sorting observables (such as Z DR) and storm-relative helicity that has been noted in previous work.

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Brett Roberts, Ming Xue, and Daniel T. Dawson II

Abstract

A suite of six idealized supercell simulations is performed in which the surface drag coefficient C d is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with C d ≥ 0.002, with the intensification occurring earlier for larger C d. In the experiment with C d = 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller C d, as well as stronger corner flow in experiments with larger C d. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with C d. However, the circulation generation is similar in magnitude for the experiments with C d = 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of C d values for promoting intense tornadoes within our experimental configuration.

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Edward R. Mansell, Daniel T. Dawson II, and Jerry M. Straka

Abstract

A three-moment bulk microphysics scheme is modified to treat melting in a size-dependent manner that emulates results from a spectral bin scheme. The three-moment bulk framework allows the distribution shape to change and accommodate some direct effects of melting on both the hail and raindrop size distributions. Reflectivity changes and shed raindrop sizes are calculated over discrete size ranges of the hail particle spectrum. Smaller ice particles are treated as melting into drops of the same mass, whereas large particles shed drops as they melt. As small ice particles are lost, the size spectrum naturally becomes narrower and the mean size of small hail can increase. Large hail with a narrow spectrum, however, can decrease in size from melting. A substantial effect is seen on the rain median volume diameter when small drops are shed from large melting hail. The NSSL bulk scheme is compared with bin microphysics in steady-state hail shafts and in a supercell storm case. It is also shown that melting (or any substantial removal of mass) induces gravitational size sorting in bulk microphysics to increase hail size despite the design of the process rates to maintain the mean size of the melting ice. This unintended side effect can be a correct behavior for small hail, but not for large hail with a narrow distribution, when mean hail size should decrease by melting.

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