7B.4 Wildfires and Anthropogenic Emissions in the HRRR: Forecasting Dispersion of Smoke (HRRR-Smoke) and its Impact on Numerical Weather Prediction

Thursday, 26 January 2017: 11:15 AM
611 (Washington State Convention Center )
Georg A. Grell, NOAA, Boulder, CO; and R. Ahmadov, E. P. James, S. R. Freitas, G. Pereira, I. A. Csiszar, M. Tsidulko, R. B. Pierce, S. A. McKeen, C. Alexander, S. E. Peckham, P. E. Saide, and S. Benjamin

The High Resolution Rapid Refresh (HRRR) is an operational modeling system currently running at the National Centers for Environmental Prediction (NCEP). The HRRR model runs on a 3km horizontal grid over the CONUS domain and is cycled on an hourly basis. Because of this high temporal and spatial resolution used in the forecast model, the HRRR is credited with providing detailed information to key decision makers. The HRRR is based on the Weather Research and Forecasting numerical model (WRF), with many modifications for operational applications developed at ESRL (http://rapidrefresh.noaa.gov/HRRR).  The HRRR has recently been upgraded to use the improved Thompson aerosol-aware microphysics parameterization, which uses monthly aerosol concentration climatology as the initial state and lateral boundary conditions.

Over the last two years a HRRR developmental version was tested and evaluated at ESRL that ingests Fire Radiative Power (FRP) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor to determine wildfire locations and calculate aerosol and smoke emissions. This information is then used to forecast dispersion of smoke (HRRR-Smoke) as well as to allow the emitted aerosols (emissions from anthropogenic emissions have also been included) to support the climatological information and  impact radiation and microphysics through the Thompson aerosol aware microphysics scheme.

In this talk, we discuss the configuration of the HRRR-Smoke modeling system. We present examples of modeled smoke fields for some major wildfire cases over the western US and discuss the model performance.

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