Jerry M. Straka

Bio: Jerry M. Straka is an academic researcher from University of Oklahoma. The author has contributed to research in topics: Supercell & Tornado. The author has an hindex of 42, co-authored 82 publications receiving 6157 citations. Previous affiliations of Jerry M. Straka include Cooperative Institute for Mesoscale Meteorological Studies & University Corporation for Atmospheric Research.

Bulk Hydrometeor Classification and Quantification Using Polarimetric Radar Data: Synthesis of Relations

Abstract: A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper.

Cloud Microphysics Retrieval Using S-Band Dual-Polarization Radar Measurements

Abstract: Recent studies have shown the utility of polarimetric radar observables and derived fields for discrimination of hydrometeor particle types. Because the values of the radar observables that delineate different particle types overlap and are not sharply defined, the problem is well suited for a fuzzy logic approach. In this preliminary study the authors have developed and implemented a fuzzy logic algorithm for hydrometeor particle identification that is simple and efficient enough to run in real time for operational use. Although there are no in situ measurements available for this particle-type verification, the initial results are encouraging. Plans for further verification and optimization of the algorithm are described.

Direct surface thermodynamic observations within the rear-flank downdrafts of nontornadic and tornadic supercells

Abstract: Despite the long-surmised importance of the hook echo and rear-flank downdraft (RFD) in tornadogenesis, only a paucity of direct observations have been obtained at the surface within hook echoes and RFDs. In this paper, in situ surface observations within hook echoes and RFDs are analyzed. These “mobile mesonet” data have unprecedented horizontal spatial resolution and were obtained from the Verifications of the Origins of Rotation in Tornadoes Experiment (VORTEX) and additional field experiments conducted since the conclusion of VORTEX. The surface thermodynamic characteristics of hook echoes and RFDs associated with tornadic and nontornadic supercells are investigated to address whether certain types of hook echoes and RFDs are favorable (or unfavorable) for tornadogenesis. Tornadogenesis is more likely and tornado intensity and longevity increase as the surface buoyancy, potential buoyancy (as measured by the convective available potential energy), and equivalent potential temperature in the R...

Precipitation Uncertainty Due to Variations in Precipitation Particle Parameters within a Simple Microphysics Scheme

Abstract: This work reports on the sensitivity of accumulated precipitation to the microphysical parameterization in simulations of deep convective storms using a three-dimensional, nonhydrostatic cloud model with a simple liquid‐ice microphysics scheme. Various intercept parameters from an assumed Marshall‐Palmer exponential size distribution are tested along with two particle densities for the hail/graupel (qh) category. These variations allow testing of unique qh distributions that have been observed and documented in previous literature. Tests are conducted for a single thermodynamic profile and three idealized wind shear profiles. The amount of accumulated precipitation at the ground is very sensitive to the way the qh category is parameterized. Distributions characterized by larger intercepts and/or smaller particle density have a smaller mass-weighted mean terminal fall velocity and produce smaller qh mixing ratios spread over a larger area. For example, for a qh category weighted toward graupel, only a fourth as much precipitation accumulates on the ground over 2 h (and none is hail) compared to a qh category weighted toward large hail (with baseball-sized stones common). The inherent uncertainty within the qh distribution for this simple cloud-scale three-class ice microphysics scheme suggests limited usefulness in the forecasting of ground-accumulated precipitation and damaging hail.

Design and Deployment of a Portable, Pencil-Beam, Pulsed, 3-cm Doppler Radar

Abstract: A portable, pencil-beam, pulsed, Doppler, 3-cm wavelength radar has been constructed to study a wide variety of meteorological phenomena including tornadoes, severe storms, and boundary layer processes. The new radar, the Doppler on Wheels (DOW), has full scanning capability, a real-time display and archiving, and is mounted on a truck for easy portability and full mobility. This portability allows the radar to be brought to within a kilometer of rare meteorological phenomena. At this range, the pencil beam of the radar is very narrow, permitting significantly higher-resolution measurements (at 3-km range, 64 m × 64 m × 75 m) than are usually possible with stationary or airborne systems. The radar employs a new high-powered, PC-based, digital intermediate frequency (IF) data acquisition scheme called the PIRAQ. The radar has successfully collected data in several tornadoes and tornadic storms and has been used to detect dust devils and other boundary layer structures. The sensitivity and mobility...

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization

Abstract: A new bulk microphysical parameterization (BMP) has been developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models. As compared with earlier single-moment BMPs, the new scheme incorporates a large number of improvements to both physical processes and computer coding, and it employs many techniques found in far more sophisticated spectral/bin schemes using lookup tables. Unlike any other BMP, the assumed snow size distribution depends on both ice water content and temperature and is represented as a sum of exponential and gamma distributions. Furthermore, snow assumes a nonspherical shape with a bulk density that varies inversely with diameter as found in observations and in contrast to nearly all other BMPs that assume spherical snow with constant density. The new scheme’s snow category was readily modified to match previous research in sensitivity experiments designed to test the sphericity and distribution shape characteristics. From analysis of four idea...

The Advanced Regional Prediction System (ARPS) – A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification

Abstract: A completely new nonhydrostatic model system known as the Advanced Regional Prediction System (ARPS) has been developed in recent years at the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The ARPS is designed from the beginning to serve as an effective tool for basic and applied research and as a system suitable for explicit prediction of convective storms as well as weather systems at other scales. The ARPS includes its own data ingest, quality control and objective analysis packages, a data assimilation system which includes single-Doppler velocity and thermodynamic retrieval algorithms, the forward prediction component, and a self-contained post-processing, diagnostic and verification package. The forward prediction component of the ARPS is a three-dimensional, nonhydrostatic compressible model formulated in generalized terrain-following coordinates. Minimum approximations are made to the original governing equations. The split-explicit scheme is used to integrate the sound-wave containing equations, which allows the horizontal domain-decomposition strategy to be efficiently implemented for distributed-memory massively parallel computers. The model performs equally well on conventional shared-memory scalar and vector processors. The model employs advanced numerical techniques, including monotonic advection schemes for scalar transport and variance-conserving fourth-order advection for other variables. The model also includes state-of-the-art physics parameterization schemes that are important for explicit prediction of convective storms as well as the prediction of flows at larger scales. Unique to this system are the consistent code styling maintained for the entire model system and thorough internal documentation. Modern software engineering practices are employed to ensure that the system is modular, extensible and easy to use. The system has been undergoing real-time prediction tests at the synoptic through storm scales in the past several years over the continental United States as well as in part of Asia, some of which included retrieved Doppler radar data and hydrometeor types in the initial condition. As the first of a two-part paper series, we describe herein the dynamic and numerical framework of the model, together with the subgrid-scale turbulence and the PBL parameterization. The model dynamic and numerical framework is then verified using idealized and realistic mountain flow cases and an idealized density current. Other physics parameterization schemes will be described in Part II, which is followed by verification against observational data of the coupled soil-vegetation model, surface layer fluxes and the PBL parameterization. Applications of the model to the simulation of an observed supercell storm and to the prediction of a real case are also found in Part II. In the latter case, a long-lasting squall line developed and propagated across the eastern part of the United States following a historical number of tornado outbreak in the state of Arkansas.

Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities

Abstract: Since April 2007, the numerical weather prediction model, COSMO (Consortium for Small Scale Modelling), has been used operationally in a convection-permitting configuration, named COSMO-DE, at the Deutscher Wetterdienst (DWD; German weather service). Here the authors discuss the model changes that were necessary for the convective scale, and report on the experience from the first years of operational application of the model. For COSMO-DE the ability of the numerical solver to treat small-scale structures has been improved by using a Runge–Kutta method, which allows for the use of higher-order upwind advection schemes. The one-moment cloud microphysics parameterization has been extended by a graupel class, and adaptations for describing evaporation of rain and stratiform precipitation processes were made. Comparisons with a much more sophisticated two-moment scheme showed only minor differences in most cases with the exception of strong squall-line situations. Whereas the deep convection paramete...