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Abstract. Biomass burning emissions emit a significant amount of trace gases and aerosols and can affect atmospheric chemistry and radiative forcing for hundreds or thousands of kilometres downwind. They can also contribute to exceedances of air quality standards and have negative impacts on human health. We present a case study of an intense wildfire plume from Siberia that affected the air quality across the Pacific Northwest on 6–10 July 2012. Using satellite measurements (MODIS True Colour RGB imagery and MODIS AOD), we track the wildfire smoke plume from its origin in Siberia to the Pacific Northwest where subsidence ahead of a subtropical Pacific High made the plume settle over the region. The normalized enhancement ratios of O3 and PM1 relative to CO of 0.26 and 0.08 are consistent with a plume aged 6–10 days. The aerosol mass in the plume was mainly submicron in diameter (PM1 ∕ PM2.5 = 0.96) and the part of the plume sampled at the Whistler High Elevation Monitoring Site (2182 m a.s.l.) was 88 % organic material. Stable atmospheric conditions along the coast limited the initial entrainment of the plume and caused local anthropogenic emissions to build up. A synthesis of air quality from the regional surface monitoring networks describes changes in ambient O3 and PM2.5 during the event and contrasts them to baseline air quality estimates from the AURAMS chemical transport model without wildfire emissions. Overall, the smoke plume contributed significantly to the exceedances in O3 and PM2.5 air quality standards and objectives that occurred at several communities in the region during the event. Peak enhancements in 8 h O3 of 34–44 ppbv and 24 h PM2.5 of 10–32 µg m−3 were attributed to the effects of the smoke plume across the Interior of British Columbia and at the Whistler Peak High Elevation Site. Lesser enhancements of 10–12 ppbv for 8 h O3 and of 4–9 µg m−3 for 24 h PM2.5 occurred across coastal British Columbia and Washington State. The findings suggest that the large air quality impacts seen during this event were a combination of the efficient transport of the plume across the Pacific, favourable entrainment conditions across the BC interior, and the large scale of the Siberian wildfire emissions. A warming climate increases the risk of increased wildfire activity and events of this scale reoccurring under appropriate meteorological conditions.

Abstract. The balance between turbulent transport and emissions is a key issue in understanding the formation of O 3 and particulate matter with diameters less than 2.5 µm (PM 2.5 ). Discrepancies between observed and simulated concentrations for these species have, in the past, been ascribed to insufficient turbulent mixing, particularly for atmospherically stable environments. This assumption may be simplisticturbulent mixing deficiencies may explain only part of these discrepancies, and as turbulence parameterizations are improved, the timing of primary PM 2.5 emissions may play a much more significant role in the further reduction of model error. In a study of these issues, two regional air-quality models, the Community Multi-scale Air Quality model (CMAQ, version 4.6) and A Unified Regional Air-quality Modelling System (AURAMS, version 1.4.2), were compared to observations for a domain in north-western North America. The air-quality models made use of the same emissions inventory, emissions processing system, meteorological driving model, and model domain, map projection and horizontal grid, eliminating these factors as potential sources of discrepancies between model predictions. The initial statistical comparison between the models and monitoring network data showed that AURAMS' O 3 simulations outperformed those of this version of CMAQ4.6, while CMAQ4.6 outperformed AU-RAMS for most PM 2.5 statistical measures. A process analysis of the models revealed that many of the differences between the models' results could be attributed to the strength of turbulent diffusion, via the choice of an a priori lower limit in the magnitude of vertical diffusion coefficients, with AURAMS using 0.1 m 2 s −1 and CMAQ4.6 using 1.0 m 2 s −1 .The use of the larger CMAQ4.6 value for the lower limit of vertical diffusivity within AURAMS resulted in a similar performance for the two models (with AURAMS also showing improved PM 2.5 , yet degraded O 3 , and a similar time series as CMAQ4.6). The differences between model results were most noticeable at night, when the higher minimum turbulent diffusivity resulted in an erroneous secondary peak in predicted night-time O 3 . A spatially invariant and relatively high lower limit in diffusivity could not reduce errors in both O 3 and PM 2.5 fields, implying that other factors aside from the strength of turbulence might be responsible for the PM 2.5 over-predictions. Further investigation showed that the magnitude, timing and spatial allocation of area source emissions could result in improvements to PM 2.5 performance with minimal O 3 performance degradation. AURAMS was then used to investigate a land-use-dependant lower limit in diffusivity of 1.0 m 2 s −1 in urban regions, linearly scaling to 0.01 m 2 s −1 in rural areas, as employed in CMAQ5.0.1. This strategy was found to significantly improve mean statistics for PM 2.5 throughout the day and mean O 3 statistics at night, while significantly degrading (halving) midday PM 2.5 correlation coefficients and slope of observed to mode...

For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.