Evaluating aerosol emissions from wildfires in the UK Earth System Model: What we have learnt from modelling the extreme wildfires in California during September 2020

An accurate representation of biomass burning aerosol emissions is essential in climate and Earth System Models to capture aerosol properties and their interactions. The sources of regional smoke plumes include the widespread prevalence of numerous small fires, which are  common across Savanahs, and larger more episodic wildfires, such as the extreme Californian wildfire event of September 2020. Capturing emissions from such a diverse range of fire activity is a major challenge and some atmospheric models, including the UK Earth System Model (UKESM) have scaled up aerosol emissions to ensure modelled AOD match observations. Past evaluations have struggled to provide a clear answer as to how to reconcile emissions and modelled aerosols, with contrasting outcomes for different regions and/or assessments of seasonal means versus individual smoke plumes. Our modelling study leverages observational data from the unprecedented wildfires in September 2020 to identify potential issues in capturing the aerosol from large / extreme wildfires in the global modelling system of UKESM. Running in nudged mode and with daily emissions from GFED4.1s emissions enables a realistic simulation of the thick smoke plumes that ensued across the continent and out into the Pacific, with little overall bias in AODs between UKESM and co-located observations (AERONET, VIRS, MAIAC). However, scaling emissions by a factor of 2 provides better agreement globally and across regions dominated by smaller fires. We therefore develop a means of differentiating between small and large fires based on the daily dry matter (fuel) consumption and apply this to enable scaling of emissions from small fires that seem to otherwise be underestimated in the model, whilst avoiding scaling those from large fires. Our results indicate a way forward to ensure a global simulation of biomass burning aerosol and fidelity in modelling extreme events.