Tuesday, 8 January 2013: 2:30 PM
Room 11AB (Austin Convention Center)
, NOAA Earth System Research Laboratory, Boulder, CO; and S. S. Weygandt, S. Benjamin, D. C. Dowell
, T. G. Smirnova, E. P. James, P. Hofmann
, M. Hu, and J. Brown
The High-Resolution Rapid Refresh (HRRR) is a CONUS 3-km convection permitting atmospheric prediction system run hourly in real-time at the NOAA Earth System Research Laboratory. The HRRR uses a specially configured version of the Advanced Research WRF (ARW) model (including Thompson microphysics, MYJ PBL, and RUC LSM). The HRRR is run out to fifteen hours over a domain covering the entire coterminous United States using initial and boundary conditions from an hourly-cycled 13-km mesoscale model, the WRF-ARW-based Rapid Refresh (RAP). The RAP assimilates many novel and most conventional observation types including satellite observations on an hourly basis using Gridpoint Statistical Interpolation (GSI) and includes a procedure for initializing ongoing precipitation systems from observed radar reflectivity data using a digital filter, a cloud analysis system to initialize stable layer clouds, and special techniques to enhance retention of surface observation information.
The HRRR provides unique convective-scale forecast guidance with high spatial and temporal resolution leveraging both hourly updates and a sub-hourly output interval. In this presentation we will provide an overview of the HRRR forecast system including background on its inception, evolution to the current configuration with key milestones, and the path forward to operational implementation at the National Centers for Environmental Prediction (NCEP). We will provide examples of the diverse set of current HRRR forecast products, applications and users including the aviation, severe weather and renewable energy communities (both public and private) with use by the National Weather Service (NWS) including the Storm Prediction Center (SPC), and collaborative projects such as the Federal Aviation Administration-sponsored CoSPA and the Wind Forecast Improvement Project (WFIP). We will also describe challenges and infrastructure associated with maintaining a reliable, but non-operational, real-time system in terms of scalability and redundancy for user demands with data production on the order of one terabyte per day.
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