Youngsun Jung

Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part I: Observation Operators for Reflectivity and Polarimetric Variables

Abstract A radar simulator for polarimetric radar variables, including reflectivities at horizontal and vertical polarizations, the differential reflectivity, and the specific differential phase, has been developed. This simulator serves as a test bed for developing and testing forward observation operators of polarimetric radar variables that are needed when directly assimilating these variables into storm-scale numerical weather prediction (NWP) models, using either variational or ensemble-based assimilation methods. The simulator takes as input the results of high-resolution NWP model simulations with ice microphysics and produces simulated polarimetric radar data that may also contain simulated errors. It is developed based on calculations of electromagnetic wave propagation and scattering at the S band of wavelength 10.7 cm in a hydrometeor-containing atmosphere. The T-matrix method is used for the scattering calculation of raindrops and the Rayleigh scattering approximation is applied to snow and ha...

Simulations of Polarimetric Radar Signatures of a Supercell Storm Using a Two-Moment Bulk Microphysics Scheme

A new general polarimetric radar simulator for nonhydrostatic numerical weather prediction (NWP) models has been developed based on rigorous scattering calculations using the T-matrix method for reflectivity, differential reflectivity, specific differential phase, and copolar cross-correlation coefficient. A continuous melting process accounts for the entire spectrum of varying density and dielectric constants. This simulator is able to simulate polarimetric radar measurements at weather radar frequency bands and can take as input the prognostic variables of high-resolution NWP model simulations using one-, two-, and threemoment microphysics schemes. The simulator was applied at 10.7-cm wavelength to a model-simulated supercell storm using a double-moment (two moment) bulk microphysics scheme to examine its ability to simulate polarimetric signatures reported in observational studies. The simulated fields exhibited realistic polarimetric signatures that include ZDR and KDP columns, ZDR arc, midlevel ZDR and rhy rings, hail signature, and KDP foot in terms of their general location, shape, and strength. The authors compared the simulation with one employing a single-moment (SM) microphysics scheme and found that certain signatures, such as ZDR arc, midlevel ZDR, and rhy rings, cannot be reproduced with the latter. It is believed to be primarily caused by the limitation of the SM scheme in simulating the shift of the particle size distribution toward larger/smaller diameters, independent of mixing ratio. These results suggest that two- or higher-moment microphysics schemes should be used to adequately describe certain important microphysical processes. They also demonstrate the utility of a well-designed radar simulator for validating numerical models. In addition, the simulator can also serve as a training tool for forecasters to recognize polarimetric signatures that can be reproduced by advanced NWP models.

Analysis of a Tornadic Mesoscale Convective Vortex Based on Ensemble Kalman Filter Assimilation of CASA X-Band and WSR-88D Radar Data

AbstractOne of the goals of the National Science Foundation Engineering Research Center (ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) is to improve storm-scale numerical weather prediction (NWP) by collecting data with a dense X-band radar network that provides high-resolution low-level coverage, and by assimilating such data into NWP models. During the first spring storm season after the deployment of four radars in the CASA Integrated Project-1 (IP-1) network in southwest Oklahoma, a tornadic mesoscale convective system (MCS) was captured by CASA and surrounding Weather Surveillance Radars-1988 Doppler (WSR-88Ds) on 8–9 May 2007. The MCS moved across northwest Texas and western and central Oklahoma; two tornadoes rated as category 1 on the enhanced Fujita scale (EF-1) and one tornado of EF-0 intensity were reported during the event, just to the north of the IP-1 network. This was the first tornadic convective system observed by CASA.To quantify the impacts of CASA radar data in storm...

Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part II: Impact of Polarimetric Data on Storm Analysis

Abstract A data assimilation system based on the ensemble square-root Kalman filter (EnSRF) is extended to include the additional capability of assimilating polarimetric radar variables. It is used to assess the impact of assimilating additional polarimetric observations on convective storm analysis in the Observing System Simulation Experiment (OSSE) framework. The polarimetric variables considered include differential reflectivity ZDR, reflectivity difference Zdp, and specific differential phase KDP. To simulate the observational data more realistically, a new error model is introduced for characterizing the errors of the nonpolarimetric and polarimetric radar variables. The error model includes both correlated and uncorrelated error components for reflectivities at horizontal and vertical polarizations (ZH and ZV, respectively). It is shown that the storm analysis is improved when polarimetric variables are assimilated in addition to ZH or in addition to both ZH and radial velocity Vr. Positive impact ...

Ensemble Kalman Filter Analyses of the 29-30 May 2004 Oklahoma Tornadic Thunderstorm using One-and Two-Moment Bulk Microphysics Schemes , with Verification against Polarimetric Radar Data

AbstractThe performance of ensemble Kalman filter (EnKF) analysis is investigated for the tornadic supercell on 29–30 May 2004 in Oklahoma using a dual-moment (DM) bulk microphysics scheme in the Advanced Regional Prediction System (ARPS) model. The comparison of results using single-moment (SM) and DM microphysics schemes evaluates the benefits of using one over the other during storm analysis. Observations from a single operational Weather Surveillance Radar-1988 Doppler (WSR-88D) are assimilated and a polarimetric WSR-88D in Norman, Oklahoma (KOUN), is used to assess the quality of the analysis.Analyzed reflectivity and radial velocity in the SM and DM experiments compare favorably with independent radar observations in general. However, simulated polarimetric signatures obtained from analyses using a DM scheme agree significantly better with polarimetric signatures observed by KOUN in terms of the general structure, location, and intensity of the signatures than those generated from analyses using an ...

Low-Level ZDR Signatures in Supercell Forward Flanks: The Role of Size Sorting and Melting of Hail

AbstractThe low levels of supercell forward flanks commonly exhibit distinct differential reflectivity (ZDR) signatures, including the low-ZDR hail signature and the high-ZDR “arc.” The ZDR arc has been previously associated with size sorting of raindrops in the presence of vertical wind shear; here this model is extended to include size sorting of hail. Idealized simulations of a supercell storm observed by the Norman, Oklahoma (KOUN), polarimetric radar on 1 June 2008 are performed using a multimoment bulk microphysics scheme, in which size sorting is allowed or disallowed for hydrometeor species. Several velocity–diameter relationships for the hail fall speed are considered, as well as fixed or variable bulk densities that span the graupel-to-hail spectrum. A T-matrix-based emulator is used to derive polarimetric fields from the hydrometeor state variables.Size sorting of hail is found to have a dominant impact on ZDR and can result in a ZDR arc from melting hail even when size sorting is disallowed in...

Ensemble Probabilistic Forecasts of a Tornadic Mesoscale Convective System from Ensemble Kalman Filter Analyses Using WSR-88D and CASA Radar Data

AbstractThis study examines the ability of a storm-scale numerical weather prediction (NWP) model to predict precipitation and mesovortices within a tornadic mesoscale convective system that occurred over Oklahoma on 8–9 May 2007, when the model is initialized from ensemble Kalman filter (EnKF) analyses including data from four Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) X-band and five Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars. Ensemble forecasts are performed and probabilistic forecast products generated, focusing on prediction of radar reflectivity (a proxy of quantitative precipitation) and mesovortices (an indication of tornado potential).Assimilating data from both the CASA and WSR-88D radars for the ensemble and using a mixed-microphysics ensemble during data assimilation produces the best probabilistic mesovortex forecast. The use of multiple microphysics schemes within the ensemble aims to address at least partially the model physi...

The Analysis and Prediction of Microphysical States and Polarimetric Radar Variables in a Mesoscale Convective System Using Double-Moment Microphysics, Multinetwork Radar Data, and the Ensemble Kalman Filter

AbstractDoppler radar data are assimilated with an ensemble Kalman Filter (EnKF) in combination with a double-moment (DM) microphysics scheme in order to improve the analysis and forecast of microphysical states and precipitation structures within a mesoscale convective system (MCS) that passed over western Oklahoma on 8–9 May 2007. Reflectivity and radial velocity data from five operational Weather Surveillance Radar-1988 Doppler (WSR-88D) S-band radars as well as four experimental Collaborative and Adaptive Sensing of the Atmosphere (CASA) X-band radars are assimilated over a 1-h period using either single-moment (SM) or DM microphysics schemes within the forecast ensemble. Three-hour deterministic forecasts are initialized from the final ensemble mean analyses using a SM or DM scheme, respectively. Polarimetric radar variables are simulated from the analyses and compared with polarimetric WSR-88D observations for verification. EnKF assimilation of radar data using a multimoment microphysics scheme for ...

Multiscale EnKF Assimilation of Radar and Conventional Observations and Ensemble Forecasting for a Tornadic Mesoscale Convective System

AbstractIn recent studies, the authors have successfully demonstrated the ability of an ensemble Kalman filter (EnKF), assimilating real radar observations, to produce skillful analyses and subsequent ensemble-based probabilistic forecasts for a tornadic mesoscale convective system (MCS) that occurred over Oklahoma and Texas on 9 May 2007. The current study expands upon this prior work, performing experiments for this case on a larger domain using a nested-grid EnKF, which accounts for mesoscale uncertainties through the initial ensemble and lateral boundary condition perturbations. In these new experiments, conventional observations (including surface, wind profiler, and upper-air observations) are assimilated in addition to the WSR-88D and the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radar data used in the previous studies, better representing meso- and convective-scale features. The relative impacts of conventional and radar data on analyses and forecasts are examined, and bia...

Simultaneous Estimation of Microphysical Parameters and the Atmospheric State Using Simulated Polarimetric Radar Data and an Ensemble Kalman Filter in the Presence of an Observation Operator Error

Abstract The impacts of polarimetric radar data on the estimation of uncertain microphysical parameters are investigated through observing system simulation experiments when the effects of uncertain parameters on the observation operators are also considered. Five fundamental microphysical parameters (i.e., the intercept parameters of rain, snow, and hail and the bulk densities of snow and hail) are estimated individually or collectively using the ensemble square root Kalman filter. The differential reflectivity ZDR, specific differential phase KDP, and radar reflectivity at horizontal polarization ZH are used individually or in combinations for the parameter estimation while the radial velocity and ZH are used for the state estimation. In the process, the parameter values estimated in the previous analysis cycles are used in the forecast model and in observation operators in the ensuing assimilation cycle. Analyses are first performed that examine the sensitivity of various observations to the microphysi...