Sensitivity of Storm-Scale Analyses and Forecasts to Radar-Observation and Model-Grid Resolution

NOAA's Warn-on-Forecast project is developing ensemble-based systems for numerical weather prediction of convective-storm hazards with lead times O(1 h). Assimilating Doppler velocity and reflectivity observations frequently (every 10 minutes or less) is essential for initializing convective scales in the ensembles, but tradeoffs must be considered in how the radar observations are assimilated. Assimilating radar observations at the same resolution as the model resolution could be necessary to initialize and predict important sub-storm scale details such as low-level mesocyclones. On the other hand, assimilating fine-scale radar observations is demanding computationally and could adversely affect ensemble spread. Assimilating radar observations instead at a coarser resolution than that of the model grid would reduce computational costs substantially, but it's unclear without experimentation how forecasts would be affected.

These issues will be investigated for retrospective analyses and forecasts of the 27 April 2011 supercell tornado outbreak in Alabama. The Data Assimilation Research Testbed (DART) system will be used to assimilate Doppler velocity and reflectivity observations into a 36-member WRF-ARW ensemble. The WRF-model horizontal grid spacing for the data assimilation will be 2 km, and the horizontal spacing of assimilated radar observations will be varied from 2 to 6 km in the experiments. From these analyses produced on the 2-km WRF grid, forecasts will be initialized with horizontal grid spacing ranging from 2 km to 250 m. For several of the many significant supercells in this case, we will discuss sensitivity of the ensemble forecasts of mesocyclone and updraft evolution to the radar-observation and model-grid resolution. We will also discuss these experiments in terms of computational cost.