Smoke from fire is a local, regional and often international issue that is growing in complexity as competition for airshed resources increases. BlueSky is a smoke modeling framework designed to help address this problem by enabling simulations of the cumulative smoke impacts from fires (prescribed, wildland, and agricultural) across a region. Versions of BlueSky have been implemented in prediction systems across the contiguous US, and land managers, air-quality regulators, incident command teams, and the general public can currently obtain BlueSky-based predictions of smoke impacts for their region. A highly modular framework, BlueSky links together a variety of state-of-the-art models of meteorology, fuels, consumption, emissions, and air quality, and offers multiple model choices at each modeling step. This modularity also allows direct comparison between similar component models. This paper presents the overall model framework Version 2.5 – the component models, how they are linked together, and the results from case studies of two wildfires. Predicted results are affected by the specific choice of modeling pathway. With the pathway chosen, the modeled output generally compares well with plume shape and extent as observed by satellites, but underpredicts surface concentrations as observed by ground monitors. Sensitivity studies show that knowledge of fire behavior can greatly improve the accuracy of these smoke impact calculations.

We evaluate two candidate mechanisms for the onset of lightning in the relatively low electric fields measured inside thunderstorms. The first is conventional dielectric breakdown due to local enhancement of the electric field in the vicinity of hydrometeors. The second is runaway breakdown, due to extended acceleration of highenergy electrons (from cosmic rays or terrestrial sources of ionizing radiation) by the incloud electric field.We compare the electric fields required for lightning onset by each mechanism with those observed inside lightning-producing clouds, and we examine the sensitivity of the computed results to input parameters and assumptions. The conclusion of our analysis is that the conventional breakdown mechanism alone cannot trigger lightning while the runaway breakdown mechanism appears a more likely candidate. We identify the parameters on which each mechanism depends and emphasize the impact of observational uncertainties on our conclusions.

Plume injection height influences plume transport characteristics, such as range and potential for dilution. We evaluated plume injection height from a predictive wildland fire smoke transport model over the contiguous United States (U.S.) from 2006 to 2008 using satellite-derived information, including plume top heights from the Multi-angle Imaging SpectroRadiometer (MISR) Plume Height Climatology Project and aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). While significant geographic variability was found in the comparison between modeled plumes and satellite-detected plumes, modeled plume heights were lower overall. In the eastern U.S., satellite-detected and modeled plume heights were similar (median height 671 and 660 m respectively). Both satellite-derived and modeled plume injection heights were higher in the western U.S. (2345 and 1172 m, respectively). Comparisons of modeled plume injection height to satellite-derived plume height at the fire location (R2 = 0.1) were generally worse than comparisons done downwind of the fire (R2 = 0.22). This suggests that the exact injection height is not as important as placement of the plume in the correct transport layer for transport modeling

[1] We evaluated predictions of hourly PM 2.5 surface concentrations produced by the experimental BlueSky Gateway air quality modeling system during two wildfire episodes in southern California (Case 1) and northern California (Case 2). In southern California, the prediction performance was dominated by the prevailing synoptic weather patterns, which differentiated the smoke plumes into two types: narrow and highly concentrated during an offshore flow, and diluted and well-mixed during a light onshore flow. For the northern California fires, the prediction performance was dominated by terrain and the limitations of predicting concentrations in a narrow valley, rather than by the synoptic pattern, which did not differ much throughout the wildfire episode. There was an over-prediction bias for the maximum values during this episode. When the predicted values were compared to observed values, the best performance results were for the onshore flow during the southern California fires, indicating that the coarse grid used by BlueSky Gateway appropriately represented these well-mixed conditions. Overall, the southern California fire predictions were biased low and the model did not reproduce the high hourly concentrations (>240 mg/m 3 ) observed by the monitors. The predicted results performed well against the observations for the northern California fires, with a large number of predicted values within acceptable range of the observed values.Citation: Strand, T.