Statistical and case study assessment of RAP and HRRR convective forecast skill for 2013
For the HRRR, the enhancements include the same WRF-ARW model changes as well as a new storm-scale data assimilation procedure designed to significantly improve short lead-time predictions of convection and other weather phenomena. This procedure features a one-hour 3-km HRRR pre-forecast period, in which 4 15-min. cycles of radar reflectivity assimilation are completed, followed by application of the Global Statistical Interpolation (GSI) variational analysis package at 3-km to ensure close fit to the latest conventional observations. The radar reflectivity assimilation method is similar to that used in the RAP (specification of latent heating-based temperature tendencies derived from the radar observed reflectivity during a forward integration), but omits the digital filtering aspect of the RAP initialization. This procedure has greatly reduced the model spin-up time for initializing ongoing precipitation systems, leading to much improved short term forecast performance.
The presentation will include a detailed statistical assessment of RAP and HRRR forecasts from the 2013 warm season, with an emphasis on the prediction of convective phenomena. This statistical analysis will be complemented by specific case-study analyses to illustrate details of how the assimilation and model upgrades lead to forecast improvement.