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
- 1 May 2012
- journal article
- Published by American Meteorological Society in Monthly Weather Review
- Vol. 140 (5), 1457-1475
- https://doi.org/10.1175/mwr-d-11-00032.1
Abstract
The 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 SM scheme.These results demonstrate for the first time for a real supercell storm that EnKF data assimilation using a numerical model with an adequate microphysics scheme (i.e., a scheme that predicts at least two moments of the hydrometeor size distributions) is capable of producing polarimetric radar signatures similar to those seen in observations without directly assimilating polarimetric data. In such cases, the polarimetric data also serve as completely independent observations for the verification purposes.Keywords
This publication has 55 references indexed in Scilit:
- The Impact of Evaporation on Polarimetric Characteristics of Rain: Theoretical Model and Practical ImplicationsJournal of Applied Meteorology and Climatology, 2010
- Additive Noise for Storm-Scale Ensemble Data AssimilationJournal of Atmospheric and Oceanic Technology, 2009
- Effects of microphysical drop size distribution on tornadogenesis in supercell thunderstormsGeophysical Research Letters, 2008
- Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part II: Impact of Polarimetric Data on Storm AnalysisMonthly Weather Review, 2008
- Simultaneous Estimation of Microphysical Parameters and Atmospheric State with Simulated Radar Data and Ensemble Square Root Kalman Filter. Part II: Parameter Estimation ExperimentsMonthly Weather Review, 2008
- Multiresolution Ensemble Forecasts of an Observed Tornadic Thunderstorm System. Part I: Comparsion of Coarse- and Fine-Grid ExperimentsMonthly Weather Review, 2006
- The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilationArchiv für Meteorologie, Geophysik und Bioklimatologie Serie A, 2003
- The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applicationsArchiv für Meteorologie, Geophysik und Bioklimatologie Serie A, 2001
- The Advanced Regional Prediction System (ARPS) - A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verificationArchiv für Meteorologie, Geophysik und Bioklimatologie Serie A, 2000
- Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statisticsJournal of Geophysical Research: Oceans, 1994