Improved Convective Scale Prediction from the Assimilation of Rapid-Scan Phased Array Radar Data

The past decade has seen the development of two major technologies that will help develop the capability for real-time prediction of severe convective storms. Since 2003, NSSL has been actively developing the Multifunction Phased Array Radar (MPAR), a potential next-generation operational weather radar system using phased array radar panels to enable complete radar volumes to be collected every 30-60 seconds (Heinselman and Torres, 2012). During the same period, data assimilation techniques have been extended from the synoptic and mesoscale to encompass nonhydrostatic scales, enabling a more complete assimilation of radar observations.

An observing system simulation experiment by Yussouf and Stensrud (2011) demonstrated that the assimilation of synthetic rapid-scan radar data from a splitting supercell storm using an Ensemble Kalman Filter (EnKF) improved both analyses and ensemble forecasts relative to radar data collected using a typical WSR-88D scan strategy. Demonstrating a similar impact using real phased-array radar data has proven more challenging. Determining the impact from rapid-scan radar data requires the mesoscale background environment to be accurately estimated and having the forecast model's convective-scale error-growth rates to be small. If these requirements are not met, our experience has shown that these errors rapidly increase and contaminate the storm-scale forecasts. When compared to convective-scale forecasts using WSR-88D scanning rates, these errors obscure impacts arising from the inclusion of rapid-scan radar data.

This presentation will focus on results from the 24 May 2011 El Reno tornadic storm, where a long time-series (> 3 hours) of ~1 minute volume scans was collected when the storm was within 100 km of a phased array radar (the National Weather Radar Testbed in Norman, OK). A large number of storm-scale assimilation experiments have been conducted using EnKF and demonstrate the added benefit from rapid-scan data during a series of 40-minute forecast periods. A number of techniques were applied to ensure the results are robust and indicate that the results are insensitive to small changes to the ensemble configuration and initial conditions. This is the first real-data demonstration of the potential impact from an MPAR observing capability for storm-scale numerical weather prediction.

References

Elliott, M. S., D. R. MacGorman, T. J. Schuur, P. L. Heinselman, 2012: An analysis of overshooting top lightning mapping array signatures in supercell thunderstorms. Extended Abstracts, 4th International Lightning Meteorology Conference, Broomfield, CO, USA, Vaisala, 1–12.

Heinselman, P. L., and S. M. Torres, 2011: Hightemporal resolution capabilities of the National Weather Radar Testbed Phasedarray Radar. J. Appl. Meteor. Climatol., 50, 579–593.

Yussouf, N., D. J. Stensrud, 2010: Impact of Phased-Array Radar Observations over a Short Assimilation Period: Observing System Simulation Experiments Using an Ensemble Kalman Filter. Monthly Weather Review, 138, 517–538, doi:10.1175/2009MWR2925.1