Representing extreme fires and their radiative effects in a global climate model via variable scaling of emissions: Case study of the 2020 California wildfires

An accurate representation of biomass burning aerosol emissions is essential in Earth System Models to capture aerosol properties and reduce uncertainties in their interactions with radiation and climate. Sources of wildfire smoke include both widespread prevalence of numerous small fires and more extreme episodic events, such as the unprecedented Californian wildfires of September 2020. Our global modelling study leverages observational data to evaluate how well aerosol emissions from extreme wildfires are captured in the UK Earth System Model (UKESM), alongside those from other fires. Running with daily emissions from Global Fire Emission Database v.4.1s (GFED4.1s) enables a realistic simulation of the thick smoke plumes from the Californian fires and large boreal fires more generally, with little overall bias in aerosol optical depths (AODs) between UKESM and co-located observations (AERONET, VIIRS). However, modelled AODs were biased low across other regions dominated by fires with lower fuel consumption, unless emissions were scaled up by a factor of 2. We therefore develop a means of selectively scaling up aerosol emissions from GFED4.1s pixels with lower area-averaged daily dry matter consumption (DM) and not scaling those with higher daily DM, associated with extremely large or intense fires. Applying daily emissions was crucial in capturing the spatial and temporal variability of AOD and instantaneous radiative forcing (IRF) during extreme events, although switching to monthly emissions made little difference to the regional monthly mean IRF. Our results indicate a way forward to ensure both means and extremes in biomass burning smoke events are represented.