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Using modelled relationships and satellite observations to attribute modelled aerosol biases over biomass burning regions

Q Zhong, N Schutgens, GR van der Werf, T van Noije, SE Bauer, K Tsigaridis, T Mielonen, R Checa-Garcia, D Neubauer, Z Kipling, A Kirkevåg, DJL Olivié, H Kokkola, H Matsui, P Ginoux, T Takemura, P Le Sager, S Rémy, H Bian, M Chin

Biomass burning (BB) is a major source of aerosols that remain the most uncertain components of the global radiative forcing. Current global models have great difficulty matching observed aerosol optical depth (AOD) over BB regions. A common solution to address modelled AOD biases is scaling BB emissions. Using the relationship from an ensemble of aerosol models and satellite observations, we show that the bias in aerosol modelling results primarily from incorrect lifetimes and underestimated mass extinction coefficients. In turn, these biases seem to be related to incorrect precipitation and underestimated particle sizes. We further show that boosting BB emissions to correct AOD biases over the source region causes an overestimation of AOD in the outflow from Africa by 48%, leading to a double warming effect compared with when biases are simultaneously addressed for both aforementioned factors. Such deviations are particularly concerning in a warming future with increasing emissions from fires.

Bibliografische gegevens

Q Zhong, N Schutgens, GR van der Werf, T van Noije, SE Bauer, K Tsigaridis, T Mielonen, R Checa-Garcia, D Neubauer, Z Kipling, A Kirkevåg, DJL Olivié, H Kokkola, H Matsui, P Ginoux, T Takemura, P Le Sager, S Rémy, H Bian, M Chin. Using modelled relationships and satellite observations to attribute modelled aerosol biases over biomass burning regions
Journal: Nat. Commun., Volume: accepted, Year: 2022, doi: -

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