A major drawback of assimilating the radar data only within the RR model, which employs 13-km horizontal grid spacing, is the inability to continuously cycle explicit convection within the HRRR. Thus, work to improve the HRRR convective forecast skill is ongoing through experimentation with cycled 3-km radar-data assimilation techniques. We are evaluating a number of methods to apply the radar-DFI technique in a cycled way at 3-km (including a forward only 15-min update cycle). At the conference, we will present preliminary results, including an assessment of the 3-km forecast improvement from adding a cycled 3-km radar assimilation. Special attention will be given to storm-scale spin-up and balance (including an evaluation of the cold-pool evolution) along with continuity of convective-scale structures, originating from an accurate storm-scale analysis (initial condition), during much of the free forecast period (several hours).
A second focus of work to improve HRRR radar assimilation is on the use of radial velocity within the HRRR. Here, we will examine the forecast impact from assimilation of these data and evaluate sensitivity to variations in the assimilation configuration (assumed correlation length scale, data quality control, use of clear-air data, etc.). Finally, time permitting, we will describe some more experimental work, in which ensemble Kalman filter techniques have been applied to the storm-scale radar data assimilation problem.
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