On June 2, 2025, thick wildfire smoke swirled over the eastern United States, a scene captured and explained in a NOAA NESDIS case study showing how far and fast the plumes traveled.
That same week, an experimental forecast quietly gave meteorologists a heads up that the haze would spread and linger.
NOAA’s experimental RRFS-Smoke model does more than draw a plume, it resolves where smoke will sit near the ground and how the whole column of smoke will shift aloft across North America at roughly 1.9 miles of detail.
Ravan Ahmadov of NOAA’s Global Systems Laboratory (GSL) has been a key contributor to NOAA’s smoke modeling advances.
The danger from smoke is driven by fine particles known as PM2.5 that can reach deep into the lungs and the bloodstream, raising risks for asthma attacks, heart problems, and early deaths during heavy episodes.
Short bursts can still be harmful, especially for older adults, children, and people with lung or heart disease.
Near-surface smoke is the layer we breathe. It affects school schedules, outdoor work plans, and whether a city issues a health alert on a summer afternoon.
Smoke higher in the atmosphere still matters. It dims sunlight, cools the surface, and can alter temperature and wind patterns that are part of routine weather forecasts.
The RRFS is NOAA’s next flagship, hourly updating system that covers a large North American domain at storm scale resolution.
It builds on the nation’s operational HRRR-Smoke guidance that has been used by forecasters since 2020. That continuity means forecasters can compare what they know with what is coming next as RRFS matures.
RRFS-Smoke provides both near-surface and vertically integrated smoke fields, so forecasters can see where people will breathe the worst air and where plumes-aloft might later mix down.
That two-layer view is practical for airports, school districts, and public health departments that need targeted actions.
Resolution matters in wildfire season. At about 1.9 miles, the model can resolve sharp smoke gradients across towns and valleys, which helps local officials decide where to cancel games, shift outdoor work, or open clean air spaces.
Hourly updates matter too. When a wind shift behind a cold front flips the smoke path, fresh guidance helps officials change course before conditions deteriorate.
RRFS-Smoke leans on satellite detections of active fires to estimate emissions and to place those emissions in the right spot at the right time.
Those detections come from polar orbiters and geostationary platforms that see heat signatures and the extent of smoke in near real time.
That satellite intelligence helps the model catch sudden flare ups and steady burns that last through the night.
It also helps forecasters judge if smoke is trapped near the surface or riding above the boundary layer where it is less directly harmful.
When model output points to a surge in PM2.5 levels, local officials often issue air quality alerts that can change daily routines.
These warnings may trigger school closures, cancel outdoor sports, or encourage vulnerable people to stay indoors until conditions improve.
Businesses also rely on accurate smoke forecasts. Construction crews, farm workers, and delivery services can adjust shifts or provide protective gear when the forecast shows unhealthy air, limiting exposure during peak smoke hours.
Forecasters do not use these maps in isolation. They combine them with air quality sensors and local weather knowledge to tailor messages for sensitive groups, commuters, and emergency managers.
NOAA’s ensemble analysis workspace, DESI, lets forecasters explore many model scenarios, compare paths, and share graphics that explain uncertainty and timing.
This is useful when the forecast hinges on a subtle wind shift or an overnight inversion that could lock smoke in place.
Independent validation builds confidence in decisions. A peer reviewed study of NOAA’s HRRR-Smoke during the 2018 Camp Fire found that the model captured the spread of dense smoke and the pattern of surface pollution during the worst days.
“HRRR-Smoke is a powerful tool for forecasting such extreme smoke pollution events,” said Ravan Ahmadov, a CIRES scientist in NOAA’s Global Systems Laboratory who helped lead the development of HRRR-Smoke.
Real events show why lead time matters. When the Canadian fires pushed haze into the Upper Midwest and then the East in early June 2025, satellite analysts flagged the plume and warned that air quality could drop as winds shifted.
Forecasters then used model output from this data to brief agencies before the thickest air arrived.
The operational backbone that forecasters use today will not disappear. HRRR-Smoke has been in National Weather Service operations since 2020, and its guidance remains central while RRFS-Smoke is tested and refined.
The goal is straightforward. Give forecasters a fast, trustworthy smoke picture that updates hourly, resolves local details, and ties directly to the choices communities must make about health, mobility, and safety.
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