Impacts of NOAA GSL research - Camp Fire of 2018

With the onset of climate change and global warming, extreme weather events are becoming increasingly common. The Camp Fire of 2018 is a devastating example.

The Camp Fire is the deadliest and most destructive in California's history. It claimed 88 lives and wiped out the town of Paradise, CA.

The fire created a dense blanket of smoke in Northern California, trapping it across the Central Valley and San Francisco Bay for an extended period of time. Smoke from the fire even spread to the east coast and could be seen in New York City.

With extreme events becoming increasingly common, forecasting systems are crucial in protecting citizens and stopping fires. A  new study   in the Bulletin of the American Meteorological Society, found that NOAA’s  HRRR-Smoke model , developed by the  Global Systems Laboratory  (GSL), accurately predicted the general movement and concentration of the Camp Fire’s smoke during the initial phase of the fire, and the increasing particulate pollution as weather conditions trapped smoke close to the surface.

 GSL's model  predicts concentrations of smoke aloft and at surface level. It depicts the smoke column from 8 meters to nearly 2 kilometers.  This is done  by calculating biomass burning emissions, fire size, and heat production using a combination of weather data and inputs from four  NOAA-NASA polar orbiting satellites .

At the time of the Camp Fire, NOAA's HRRR-Smoke model was  operating experimentally (HRRRX-Smoke),  which allowed for verification of the model's success. Not only did the model accurately produce a 3D depiction of the smoke plume from the fire, but it predicted the intensification of 2.5M particulate matter. This is a major marker of success for the program - the model was only in its experimental phase, but still had significant impacts for the public.

Data on both smoke and air pollution is crucial in protecting human health. The ability to predict smoke concentrations has significant impacts for citizens, the media, and forecast developers alike.

HRRR-Smoke identifies areas that could experience suffocating wildfire smoke, and can predict if will intensify--even over complex terrain. It operates at 3-km resolution, which means it can model smoke concentrations at the magnitude of a neighborhood. In the Camp Fire, this high-resolution data added to the base of information used to guide fire chiefs and other officials in deciding where to send  aid and firefighters .

During the fire, HRRRX-Smoke was also able to pick up important data on air movement. In the Bay Area, it could predict movement of clean air coming down the west side of the Sacramento Valley as well as into Monterey Bay, Hollister, and Gilroy due to maritime air. HRRRX-Smoke also identified “dirty air” coming into the area via the Carquinez Strait and the Altamont Pass. These predictions also contributed to the process of outlining evacuation plans.

 HRRRX-Smoke was used to guide tanker aircraft that help put out the fires.  Additionally, the model was used for monitoring and communicating air quality changes for local residents. T he LA-Times used HRRRX-Smoke  to provide live updates regarding both smoke and air pollution.

HRRRX-Smoke provided important warnings regarding visibility and weather. The model produced accurate and fast predictions, used for weeks after the fire began. Government agencies, journalists, and meteorologists relied on the technology to communicate the severity and spread of smoke.

HRRRX-Smoke also accurately predicted the onset of smoke across the country, in New York City:

HRRRX-Smoke's success in forecasting the significant event of the Camp Fire has major implications for further development of new smoke models.

HRRR-Smoke uses the innovative technique of stereoscopic modeling, which compares smoke and cloud images from two satellites. This technique's success in depicting the Camp Fire will be extremely helpful in evaluating and improving other stereoscopic models.

HRRR-Smoke also laid the groundwork for future technological developments using NOAA's new GOES-18 satellite, which takes much more frequent observations of fire radiative power, yielding great benefits for not only NOAA's smoke forecasts, but for models internationally.

HRRRX-Smoke is based on the NOAA GSL-developed Rapid Refresh modeling system. RAP provides forecast information for North America on a 13km grid and is used for aviation, severe storm forecasting, energy, hydrology, air quality, and coupling. HRRRX-Smoke's success in the Camp Fire emphasizes the importance of rapid-refreshing forecast technologies, and contributes to the further development of RAP. As HRRRX-Smoke continues to be verified, it will soon complete its experimental phase and become fully operational.

In the 2018 Camp Fire, the technology protected citizens, bolstered reporting systems, and contributed to the growing field of rapid-refresh extreme weather event forecasts.