Kelvin K. Droegemeier

Some Practical Considerations Regarding Horizontal Resolution in the First Generation of Operational Convection-Allowing NWP

Abstract During the 2005 NOAA Hazardous Weather Testbed Spring Experiment two different high-resolution configurations of the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model were used to produce 30-h forecasts 5 days a week for a total of 7 weeks. These configurations used the same physical parameterizations and the same input dataset for the initial and boundary conditions, differing primarily in their spatial resolution. The first set of runs used 4-km horizontal grid spacing with 35 vertical levels while the second used 2-km grid spacing and 51 vertical levels. Output from these daily forecasts is analyzed to assess the numerical forecast sensitivity to spatial resolution in the upper end of the convection-allowing range of grid spacing. The focus is on the central United States and the time period 18–30 h after model initialization. The analysis is based on a combination of visual comparison, systematic subjective verification conducted during the Spring Experiment, and objectiv...

Numerical Simulation of Thunderstorm Outflow Dynamics. Part I: Outflow Sensitivity Experiments and Turbulence Dynamics

Abstract In this first paper of a two-part series, a two-dimensional numerical model is developed and used to investigate the dynamics of thunderstorm outflows. By focusing only on the outflow and using essentially inviscid equations and high spatial resolution, we are able to explicitly represent important physical processes such as turbulent mixing. To simplify interpretation of the results, the model atmosphere used in all experiments is calm and dry adiabatic. This approach allows us to establish basic characteristics of modeled outflows in simple physical settings, and provides a foundation for future studies using more realistic environments. All simulated outflows are initialized by prescribing a (controlled) horizontal flux of cold air into the model domain through a lateral boundary. In a series of sensitivity tests, we examine three parameters of the cold air source region: 1) the vertical temperature deficit profile, 2) the magnitude of the temperature deficit, and 3) the cold-air depth. By hol...

A Three-Dimensional Variational Data Analysis Method with Recursive Filter for Doppler Radars

Abstract In this paper, a new method of dual-Doppler radar wind analysis based on a three-dimensional variational data assimilation (3DVAR) approach is proposed. In it, a cost function, including background term and radial observation term, is minimized through a limited memory, quasi-Newton conjugate-gradient algorithm with the mass continuity equation imposed as a weak constraint. In the method, the background error covariance matrix, though simple in this case, is modeled by a recursive filter. Furthermore, the square root of this matrix is used to precondition the minimization problem. The current method is applied to Doppler radar observation of a supercell storm, and the analysis results are compared to a conceptual model and previous research. It is shown that the horizontal circulations, both within and around the storms, as well as the strong updraft and the associated downdraft, are well analyzed. Because no explicit integration of the anelastic mass continuity equation is involved, error accumu...

A Variational Method for the Analysis of Three-Dimensional Wind Fields from Two Doppler Radars

This paper proposes a new method of dual-Doppler radar analysis based on a variational approach. In it, a cost function, defined as the distance between the analysis and the observations at the data points, is minimized through a limited memory, quasi-Newton conjugate gradient algorithm with the mass continuity equation imposed as a weak constraint. The analysis is performed in Cartesian space. Compared with traditional methods, the variational method offers much more flexibility in its use of observational data and various constraints. Using the radar data directly at observation locations avoids an interpolation step, which is often a source of error, especially in the presence of data voids. In addition, using the mass continuity equation as a weak instead of strong constraint avoids the error accumulation and the subsequent somewhat arbitrary adjustment associated with the explicit vertical integration of the continuity equation. The current method is tested on both model-simulated and observed datasets of supercell storms. It is shown that the circulation inside and around the storms, including the strong updraft and associated downdraft, is well analyzed in both cases. Furthermore, the authors found that the analysis is not very sensitive to the specification of boundary conditions and to data contamination. The method also has the potential for retrieving, with reasonable accuracy, the wind in regions of single-Doppler radar coverage.

Objective verification of the SAMEX '98 Ensemble Forecasts

During May 1998, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma coordinated a multi-institution numerical forecast project known as the Storm and Mesoscale Ensemble Experiment (SAMEX). SAMEX involved, for the first time, the real-time operation of four different ensembles of mesoscale models over the same region of the United States. The main purpose of this paper is the evaluation of the ensemble forecasts, performed at a relatively coarse resolution of 30 km. An additional SAMEX goal not discussed here is to compare the value of the ensemble forecasts against single forecasts made over smaller subregions of the Great Plains at both intermediate (10 km) and high (3 km) resolution. The SAMEX ’98 ensembles consisted of a single 36-h control forecast from the ARPS (at CAPS), the Penn State‐NCAR fifth-generation Mesoscale Model (at NSSL), and the Eta Model and Regional Spectral Model (at NCEP), all with horizontal resolutions of approximately 30 km, and perturbed runs, resulting in a grand ensemble of 25 members. The forecasts of geopotential heights, temperatures, and moisture were verified against the Eta operational analyses, rather than observations. Unlike global ensembles, which tend to be useful in the medium range, the mesoscale SAMEX ensembles provided useful information in the short range. A major result is that the performance of the ensemble of multiple forecast systems is much better than that of each individual ensemble system, probably because it represents more realistically the current uncertainties in both models and initial conditions. A similar advantage from the use of multimodel, multianalysis systems has been observed with global ensembles. The SAMEX results also show that perturbations to model physics parameterizations, as well as the use of consistent perturbations in the boundary conditions, are important for regional ensemble forecasting. Efforts are now under way to compare the ensemble forecasts against those made using higher spatial resolution, and follow-on SAMEX experiments are anticipated in other geographical areas and weather regimes. Although the main results of this paper appear to be very robust, they were based on a small number of cases, and similar experiments carried out during other periods will help to test their significance.

SuomiNet: A Real–Time National GPS Network for Atmospheric Research and Education

“SuomiNet,” a university-based, real-time, national Global Positioning System (GPS) network, is being developed for atmospheric research and education with funding from the National Science Foundation and with cost share from collaborating universities. The network, named to honor meteorological satellite pioneer Verner Suomi, will exploit the recently shown ability of ground-based GPS receivers to make thousands of accurate upper- and lower-atmospheric measurements per day. Phase delays induced in GPS signals by the ionosphere and neutral atmosphere can be measured with high precision simultaneously along a dozen or so GPS ray paths in the field of view. These delays can be converted into integrated water vapor (if surface pressure data or estimates are available) and total electron content (TEC), along each GPS ray path. The resulting continuous, accurate, all-weather, real-time GPS moisture data will help advance university research in mesoscale modeling and data assimilation, severe weather, precipita...

Application of the Piecewise Parabolic Method (PPM) to Meteorological Modeling

Abstract The Piecewise Parabolic Method (PPM), a numerical technique developed in astrophysics for modeling fluid flows with strong shocks and discontinuities is adapted for treating sharp gradients in small-scale meteorological flows. PPM differs substantially from conventional gridpoint techniques in three ways. First, PPM is a finite volume scheme, and thus represents physical variables as averages over a grid zone rather than single values at discrete points. Second, a unique, monotonic parabola is fit to the zone average of each dependent variable using information from neighboring zone averages. As shown in a series of one- and two-dimensional linear advection experiments, the use of parabolas provides for extremely accurate advection, particularly of sharp gradients. Furthermore, the monotonicity constraint renders PPMs solutions free from Gibbs oscillations. PPMs third attribute is that each zone boundary is treated as a discontinuity. Using the method of characteristic the nonlinear flux of qua...

An OSSE Framework Based on the Ensemble Square Root Kalman Filter for Evaluating the Impact of Data from Radar Networks on Thunderstorm Analysis and Forecasting

Abstract A framework for Observing System Simulation Experiments (OSSEs) based on the ensemble square root Kalman filter (EnSRF) technique for assimilating data from more than one radar network is described. The system is tested by assimilating simulated radial velocity and reflectivity data from a Weather Surveillance Radar-1988 Doppler (WSR-88D) radar and a network of four low-cost radars planned for the Oklahoma test bed by the new National Science Foundation (NSF) Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). Such networks are meant to adaptively probe the lower atmosphere that is often missed by the existing WSR-88D radar network, so as to improve the detection of low-level hazardous weather events and to provide more complete data for the initialization of numerical weather prediction models. Different from earlier OSSE work with ensemble Kalman filters, the radar data are sampled on the radar elevation levels and a more realistic forward operator based on ...

A Numerical Simulation of Cyclic Mesocyclogenesis

Abstract A three-dimensional nonhydrostatic numerical model, the Advanced Regional Prediction System, is used to study the process of cyclic mesocyclogenesis in a classic supercell thunderstorm. During the 4-h simulation, the storm’s mesocyclone undergoes two distinct occlusions, with the beginning of a third indicated at the end of the simulation. The occlusion process exhibits a period of approximately 60 min and is qualitatively similar in each case. Initial midlevel (3–7 km) mesocyclogenesis proceeds according to the “classic” picture, that is, via tilting of streamwise environmental vorticity. The development of an evaporatively driven rear-flank downdraft (RFD) signals the beginning of the occlusion process. The developing RFD wraps cyclonically around the mesocyclone, causing the gust front to surge outward. Simultaneously, the occluding mesocyclone rapidly intensifies near the surface. Trajectory analyses demonstrate that this intensification follows from the tilting and stretching of near-ground ...

The Influence of Helicity on Numerically Simulated Convective Storms

Abstract A three-dimensional numerical cloud model is used to investigate the influence of storm-relative environmental helicity (SREH) on convective storm structure and evolution, with a particular emphasis on the identification of ambient shear profiles that are conducive to the development of long-lived, strongly rotating storms. Eleven numerical simulations are made in which the depth and turning angle of the ambient vertical shear vector are varied systematically while maintaining a constant magnitude of the shear in the shear layer. In this manner, an attempt is made to isolate the effects of different environmental Felicities on storm morphology and show that the SREH and bulk Richardson number, rather than the mean shear in the low levels, determine the rotational characteristics and morphology of deep convection. The results demonstrate that storms forming in environments characterized by large SREH are longer-lived than those in less helical surroundings. Further, it appears that the storm-relat...