Smoke from the 2018 Camp Fire in Northern California blanketed a large part of the region for two weeks, creating poor air quality in the “unhealthy” range for millions of people. The NOAA Global System Laboratory’s HRRR-Smoke model was operating experimentally in real time during the Camp Fire. Here, output from the HRRR-Smoke model is compared to surface observations of PM2.5 from AQS and PurpleAir sensors as well as satellite observation data. The HRRR-Smoke model grid at 3-km resolution successfully simulated the evolution of the plume during the initial phase of the fire (8-10 November 2018). Stereoscopic satellite plume height retrievals were used to compare with model output (for the first time, to the authors’ knowledge), showing that HRRR-Smoke is able to represent the complex 3D distribution of the smoke plume over complex terrain. On 15-16 November, HRRR-Smoke was able to capture the intensification of PM2.5 pollution due to a high pressure system and subsidence that trapped smoke close to the surface; however, HRRR-Smoke later underpredicted PM2.5 levels due to likely underestimates of the fire radiative power (FRP) derived from satellite observations. The intensity of the Camp Fire smoke event and the resulting pollution during the stagnation episodes make it an excellent test case for HRRR-Smoke in predicting PM2.5 levels, which were so high from this single fire event that the usual anthropogenic pollution sources became insignificant. The HRRR-Smoke model was implemented operationally at NOAA/NCEP in December 2020, now providing essential support for smoke forecasting as the impact of US wildfires continues to increase in scope and magnitude.
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