Storm-Scale Data Assimilation and Ensemble Forecasts for the 22nd May 2011 Joplin Tornadic Supercell

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Wednesday, 7 January 2015: 4:15 PM
131AB (Phoenix Convention Center - West and North Buildings)
Spencer Ross Rhodes, North Carolina State University, Raleigh, NC; and N. Yussouf

One of the goals of NOAA's Warn-on-Forecast (WoF) initiative is a 1-h probabilistic storm-scale forecast of severe thunderstorm events. As part of this initiative, a multiscale ensemble data assimilation and forecast system is developed at NSSL using the WRF-ARW model and the ensemble Kalman filter technique from the Data Assimilation Research Testbed (DART) software. In this study, the system's effectiveness is tested using the 22nd May 2011 Joplin, Missouri (MO) tornadic supercell event. The 36-member multiphysics mesoscale and storm-scale ensembles are initialized from the Global Ensemble Forecast System (GEFS) at 0000 UTC 22 May 2011 at 15-km and 3-km horizontal grid spacing, respectively. Routinely available observations are assimilated on both grids every hour for more than a day. Prior to the initiation of the supercell that eventually produced the Joplin EF5 tornado, reflectivity and radial velocity observations from five operational WSR-88D radars are assimilated every 5 minutes into storm-scale ensemble for a 5-hour period. 1-h ensemble forecasts are launched from the storm-scale analyses every 10 minutes starting from 2200 UTC, which is 30 minutes before the Joplin tornado touched ground. Results indicate that the storm-scale ensembles are able to analyze the observed storms with reasonable accuracy even though the Joplin tornadic supercell is not in close proximity to the operational radars. In addition, the 1-h probabilistic forecasts of low-level vorticity corresponds reasonably well with the observed Joplin tornado damage path up to 24 minutes in advance, offering 7 minutes extra lead time than that provided by the WFO in Springfield, MO on that day. The results obtained from this study show the potential for a numerical weather prediction model based short-range probabilistic storm-scale forecast of tornadic supercell thunderstorms that can help extend severe weather warning lead times.