Time-Lagged 3-km Ensemble High-Resolution Rapid Refresh (HRRR) Forecasts for Key Convective Storm, Fire Weather and Wind Energy Events in 2013

The 13-km Rapid Refresh (RAP) and 3-km convective-allowing High-Resolution Rapid Refresh (HRRR) are hourly updating weather forecast models that use a specially configured version of the Advanced Research WRF (ARW) model (including Thompson microphysics, MYNN PBL, and RUC LSM) and assimilate many novel and most conventional observation types on an hourly basis using Gridpoint Statistical Interpolation (GSI) and include a procedure for initializing ongoing precipitation systems from observed radar reflectivity data, a cloud analysis to initialize stable layer clouds from METAR and satellite observations, and special techniques to enhance retention of surface observation information. The HRRR is run hourly out to fifteen forecast hours over a domain covering the entire coterminous United States using initial and boundary conditions from the hourly-cycled RAP.

The HRRR is uniquely positioned as a situational awareness tool for short term high impact prediction of major weather events. The high resolution of the HRRR, including sub-hourly forecast output, permits an accurate deterministic depiction of the structure and evolution of deep moist convection and related hazards including tornadoes, hail, high winds, lightning and heavy rainfall. The hourly updating HRRR forecasts provide a measure of forecast likelihood in the form of run-to-run consistency that can be translated into probabilities of a particular weather hazard.

In this presentation we will focus on both the deterministic and probabilistic evaluation of HRRR forecasts for several high impact weather events from 2013 including the Yarnell, Arizona fire on 30 June and supercell tornadoes in central Oklahoma on 20 and 31 May. We will highlight model forecast diagnostics, available in real-time to operational forecasters in both the private and public sectors, that are related to particular hazards such as high 80-m winds from convective outflows in the vicinity of the Yarnell fire and the low-level rotation in supercell thunderstorms in Oklahoma. We will also present an evaluation of the continuity between model runs in the form of a time-lagged ensemble where forecast probabilities of these hazards are estimated from run-to-run consistency including neighborhood spatial and temporal filters of diagnostic fields. Finally, we will extend this time-lagged ensemble to other applications including forecasts of wind ramp events that impact renewable energy resources.