The October 2017 fires near Santa Rosa in northern California (N. CA) were the second most destructive fires to date in California 12 , killing 44 people 13 , destroying nearly 9,000 structures 13,14 , with reported losses of over $10 billion 14 , and resulting in the highest particulate matter (PM2.5) levels recorded in the Bay Area since 1999 15 . The Tubbs fire, the largest of the Oct. 2017 N. CA fires, which devastated the city of Santa Rosa, was started by a private electrical system 16 , and was associated with an intense terrain-induced downslope windstorm 17 . Such windstorms, commonly known as "Santa Ana" or "Diablo" winds, can be very destructive when driving fires and are projected with climate change to extend the fire season later into the fall and winter 17 .The Oct. 2017 N. CA fires are an example of fires with anthropogenic ignition sources and their subsequent air quality impacts that are likely to increase due to a warmer and drier climate in the Western U.S. during the 21 st century 18,19,20,21 . These trends combined with rising numbers of humans living in the urban-wildland interface are likely to result in increases in population exposure to fire activity 22 and poor air quality episodes 23 . Long-term exposure to elevated PM2.5 may increase human susceptibility to respiratory diseases such as coronavirus (COVID-19) 24,25 .The University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument was deployed to quantify the emission fluxes of the N. CA wildfires on Oct. 10, 2017. CU AirSOF consists of a Fourier Transform Spectrometer installed on a research aircraft, and uses a digital fast solar tracker to point directly at the sun to measure the total CO column above the aircraft at mid-infrared wavelengths 26,27 . The SOF method has been used to quantify emissions from area sources by mass balance 28,29,30 , but its potential to study wildfires remains largely unexplored. The CU AirSOF instrument is a unique prototype, and optimized to quantify wildfire emissions due to

TROPOspheric Monitoring Instrument (TROPOMI) measurements of carbon monoxide (CO) vertical column enhancements in optically thick biomass burning plumes were evaluated using measurements from the University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument during the 2018 Biomass Burning Fluxes of Trace Gases and Aerosols (BB-FLUX) field campaign in the northwestern United States. The different temporal and spatial scales and measurement geometries sampled from the aircraft and satellite are actively accounted for by (1) focusing on coincident measurements, (2) comparing spatial integrals of CO enhancements across plume transects, (3) using the FLEXible PARTicle (FLEXPART) dispersion model to correct for atmospheric transport, and (4) accounting for Averaging Kernels (AVK). TROPOMI is found to be systematically higher relative to the aircraft by +36% for the operational product (+27% preoperational product) without geospatial and temporal corrections. Consecutive transects by CU AirSOF revealed significant variations between integrated CO enhancements (on average 28% over 30 min) on the satellite sub-pixel scale. When the additional corrections are applied (FLEXPART, and to a lesser degree also AVK), the average bias is reduced to +10% for the operational product (+7.2% preoperational), which is insignificant within 15% uncertainty (variability among case studies, 95% confidence level). Radiative transfer simulations in synthetic plumes indicate that multiple scattering can enhance satellite CO signals by 5−10% at high aerosol loads, which warrants further attention. Smoke strongly reduces trace gas measurements at ultraviolet and visible wavelengths (by up to a factor of 6), highlighting the importance of multispectral aerosol properties in thick smoke.

Abstract. Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

<p>NOAA has been transitioning its numerical weather predictions (NWP) models to the new models, which are based on Unified Forecasting System [https://ufscommunity.org/]. NOAA Global Systems Laboratory (GSL) in collaboration with other teams has been developing a new storm-scale NWP model – Rapid Refresh Forecasting System (RRFS) based on UFS. Currently the RRFS model is running in real time to provide experimental weather forecasting products [https://rapidrefresh.noaa.gov/RRFS/]. In the future the RRFS model will replace NOAA’s current operational High-Resolution Rapid Refresh (HRRR) NWP system.</p><p>Following on the successful HRRR-Smoke implementation in 2020, we started transitioning the smoke emission, plume rise, dry and wet removal simulation capabilities into the RRFS based using the Common Community Physics Package (CCPP) framework. The CCPP framework also ensures consistency between the physics and smoke/aerosol parameterizations. There are a number of new capabilities implemented in RRFS-Smoke. The high spatial resolution VIIRS I-band and high-frequency GOES-16/17 fire radiative power (FRP) data are ingested into the model to estimate both biomass burning (BB) emissions and fire heat fluxes every hour. Inline turbulent mixing of smoke within the boundary layer scheme, hourly wildfire potential to predict the evolution of the BB emissions, smoke interactions with the double-moment microphysics scheme and other new capabilities are implemented into the new RRFS-Smoke model.</p><p>The RRFS-Smoke model is simulated for August 2019 over the US by focusing on the FIREX-AQ field campaign [https://csl.noaa.gov/projects/firex-aq/]. The wide range of in-situ and remote sensing observations obtained onboard the DC-8 aircraft during FIREX-AQ provide valuable datasets to evaluate and improve the capabilities of the RRFS-Smoke model to accurately simulate BB emissions, smoke transport and mixing, and fire plume rise. Here, we present the simulations and evaluations of the RRFS-Smoke model for fire weather and smoke for some of the FIREX-AQ cases.</p>