HRRR-Smoke: A high-resolution rapidly updating coupled modeling system to forecast smoke, visibility and smoke-weather interactions over the US

DSRC entrance

Ravan Ahmadov, NOAA ESRL Global Systems Division

Wednesday, April 17, 2019, 1:30 pm Mountain Time
DSRC 2A305


In recent years the western US has been experiencing many devastating wildfires. These wildfires have caused large amount of human and property losses. The increasing intensity of the deadly wildfires were associated with degraded air quality and visibility affecting millions of people across the country. Smoke from wildfires can have profound impact on outdoor events and economic activity (e.g. tourism). Moreover, smoke particles affect radiation, thus modulating weather.

Global Systems Division (GSD) has been running the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model, which is based on WRF. The HRRR domain covers the contiguous US on 3km resolution. Every hour a new HRRR forecast starts by assimilating the latest meteorological observations from multiple platforms. We implemented a smoke tracer (primary PM2.5) from biomass burning (BB) sources in HRRR by leveraging on the WRF-Chem model’s coupled modeling framework. In HRRR-Smoke the BB emissions are estimated by ingesting the satellite (Suomi-NPP, NOAA-20 and MODIS Aqua/Terra) fire radiative power (FRP) data. HRRR-Smoke also simulates smoke feedback on radiation. Since 2016 HRRR-Smoke has been running at GSD in real-time. The rapidly updated forecast products of smoke (near surface and aloft) concentrations, visibility and other related variables are provided to a wide range of operational users and researchers across the US.

Here, I present our FRP based BB emission parameterization and HRRR-Smoke forecasting system, its products, and their use in various applications. I present HRRR-Smoke simulations for August, 2018, when the western US and Canada experienced one of the worst fire seasons. The simulated smoke and visibility fields are evaluated using the ground and satellite based measurements. Additionally, detailed verification of the meteorological forecasts, and their sensitivity to the radiative impact of smoke is presented.

Ravan Ahmadov received his PhD in Atmospheric Physics from Lomonosov Moscow State University, and completed a post-doctoral fellowship at the Max-Planck Institute for Biogeochemistry in Germany. He spent 7 years as a Research Scientist in NOAA ESRL CSD, where he worked in the Regional Climate Modeling group. In 2016, he began working in the Model Development Branch of GSD, where he is developing new methods of smoke forecasting.

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