An Investigation of the Goshen County, Wyoming, Tornadic Supercell of 5 June 2009 Using EnKF Assimilation of Mobile Mesonet and Radar Observations Collected during VORTEX2. Part I: Experiment Design and Verification of the EnKF Analyses

Abstract

High-resolution Doppler radar velocities and in situ surface observations collected in a tornadic supercell on 5 June 2009 during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) are assimilated into a simulated convective storm using an ensemble Kalman filter (EnKF). A series of EnKF experiments using a 1-km horizontal model grid spacing demonstrates the sensitivity of the cold pool and kinematic structure of the storm to the assimilation of these observations and to different model microphysics parameterizations. An experiment is performed using a finer grid spacing (500 m) and the most optimal data assimilation and model configurations from the sensitivity tests to produce a realistically evolving storm. Analyses from this experiment are verified against dual-Doppler and in situ observations and are evaluated for their potential to confidently evaluate mesocyclone-scale processes in the storm using trajectory analysis and calculations of Lagrangian vorticity budgets. In Part II of this study, these analyses will be further evaluated to learn the roles that mesocyclone-scale processes play in tornado formation, maintenance, and decay. The coldness of the simulated low-level outflow is generally insensitive to the choice of certain microphysical parameterizations, likely owing to the vast quantity of kinematic and in situ thermodynamic observations assimilated. The three-dimensional EnKF wind fields and parcel trajectories resemble those retrieved from dual-Doppler observations within the storm, suggesting that realistic four-dimensional mesocyclone-scale processes are captured. However, potential errors are found in trajectories and Lagrangian three-dimensional vorticity budget calculations performed within the mesocyclone that may be due to the coarse (2 min) temporal resolution of the analyses. Therefore, caution must be exercised when interpreting trajectories in this area of the storm.

Sensitivity of Real-Data Simulations of the 3 May 1999 Oklahoma City Tornadic Supercell and Associated Tornadoes to Multimoment Microphysics. Part I: Storm- and Tornado-Scale Numerical Forecasts

“…However, the eastwarddirected difference in the track of the storm in 1kmMY1A relative to the other experiments is consistent with this mechanism of propagation. Similar structures have also been noted and described in several recent observational studies of supercells (Wurman et al 2007;Marquis et al 2008;Wurman et al 2010;Kosiba et al 2013;Lee et al 2012;Markowski et al 2012;Marquis et al 2014;Skinner et al 2014). This effect is in addition to the more dominant components of motion associated with advection by the mean wind and the dynamic interactions of the storm updraft and mesocyclone with the ambient shear (Zeitler and Bunkers 2005).…”

A Comparison of Ensemble Strategies for Flash Flood Forecasting: The 12 October 2007 Case Study in Valencia, Spain

“…DA algorithms aim to determine the atmospheric state and associated uncertainties by coupling model forecast information with multiple sources of observations and their respective errors. The ensemble Kalman filter (EnKF) is an ensemble DA approach to nonlinear Kalman filtering based on Monte Carlo techniques (Evensen 2003;Guillijns et al 2006), which has been shown to improve the sampling of the IC error space in both meso-and storm-scale ensemble data assimilation systems (Snyder and Zhang 2003;Zhang et al 2004;Dowell et al 2004;Tanamachi et al 2013;Marquis et al 2014;Sippel et al 2013). The EnKF has an unquestionable potential to produce valuable hydrometeorological predictions in Mediterranean Spain, as it combines the skill for an appropriate mesoscale ensemble generation strategy and the transference of information from land regions toward relatively sparsely observed maritime areas (Carrió and Homar 2016).…”

Assimilating surface observations in a four-dimensional variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case

“…Dong et al (2011) indicated that when a radar is far away from a convective system, a positive impact results from assimilating surface observations, as long as the network spacing is less than 20 km. Through assimilating high-resolution Doppler radar radial velocities and in situ surface observations into an EnKF system, Marquis et al (2014) successfully simulated mesocyclone-scale processes in the Goshen County, Wyoming, and the tornadic supercell of 5 June 2009. Yussouf et al (2015) developed a multiscale ensemble-based assimilation and prediction system that can assimilate the radar, surface, and other observations together.…”