CAREER: Advancing Modeling of Wildfire Smoke

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This project seeks to reduce uncertainties in wildfire smoke modeling in order to enhance our ability to make forecasts of smoke events and improve smoke advisories to the general population. This would not only enhance our understanding of wildfire smoke events, but also reduce harmful pollutant exposures for communities affected by wildfire events and provide new tools for decision makers and the public. Existing observations will be used to update wildfire smoke models, and wildfire smoke forecasters will receive training and share knowledge via regular workshops. Feedback from these end user wildfire smoke forecasters will be incorporated into the research plan to ensure that new knowledge gained during the course of this work will not only advance the field but also reach communities affected by wildfire smoke events. There are three primary tasks included in this proposal. First, satellite and ground-based observations of smoke and smoke-relevant variables will be collected and assessed for their viability of usage within wildfire smoke models. Second, these observations will be used to evaluate and improve smoke simulations via improvements to model parameterizations such as smoke emissions, injection heights, chemical evolution, and optical properties. Finally, training will be conducted to potential end users of the updated wildfire smoke forecasting system with the goal of developing a framework for evaluating and establishing routine or operational smoke forecasting systems. Additionally, this work will provide potential end users with a platform for developing and sharing methods for routine or operational wildfire smoke forecasting systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.