Forecasting smoke and dust in NOAA’s next-generation high-resolution coupled numerical weather prediction model

NOAA’s Global Systems Laboratory (GSL), in collaboration with other laboratories, is developing and testing a new high-resolution weather model known as the Rapid-Refresh Forecasting System (RRFS). This model, which uses the Finite Volume Cubed-Sphere Dynamical Core, features a grid covering all of North and Central America at 3 km horizontal resolution, with 65 vertical layers. 

The RRFS is initialized every hour through assimilation of the latest weather observations. It incorporates primary aerosol emissions from wildland fires and dust sources. The coupled RRFS-Smoke-Dust (RRFS-SD) model simulates 3D concentrations of smoke, fine and coarse dust aerosol species concurrently with the meteorology, and includes the aerosol radiative feedback. Hourly fire radiative power data from the Regional ABI and VIIRS fire Emissions (RAVE) product is ingested into RRFS to estimate biomass burning emissions and fire heat fluxes. Windblown dust emissions are parameterized by using the FENGSHA scheme. An experimental version of the RRFS-SD model is being tested by NOAA Environmental Modeling Center (EMC) in real time:  https://rapidrefresh.noaa.gov/RRFS-SD/

We will present an evaluation of the RRFS-SD model  for several fire and dust case studies. Ground and aircraft-based in-situ and remote sensing data are extensively utilized to evaluate the model simulations of meteorology, smoke and dust fields. Additionally, we will present the radiative feedback of smoke and dust on the meteorological simulations in RRFS. The challenges and uncertainties affecting the smoke and dust forecasting will be discussed as well.