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

Qirui Zhong (), Nick Schutgens, Guido R. Werf, Twan Noije, Susanne E. Bauer, Kostas Tsigaridis, Tero Mielonen, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Alf Kirkevåg, Dirk J. L. Olivié, Harri Kokkola, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Sager, Samuel Rémy, Huisheng Bian and Mian Chin
Additional contact information
Qirui Zhong: Vrije Universiteit Amsterdam
Nick Schutgens: Vrije Universiteit Amsterdam
Guido R. Werf: Vrije Universiteit Amsterdam
Twan Noije: Royal Netherlands Meteorological Institute
Susanne E. Bauer: NASA Goddard Institute for Space Studies
Kostas Tsigaridis: NASA Goddard Institute for Space Studies
Tero Mielonen: Finnish Meteorological Institute
Ramiro Checa-Garcia: Laboratoire des Sciences du Climat et de l’Environnement, IPSL
David Neubauer: ETH Zurich
Zak Kipling: European Centre for Medium-Range Weather Forecasts
Alf Kirkevåg: Norwegian Meteorological Institute
Dirk J. L. Olivié: Norwegian Meteorological Institute
Harri Kokkola: Finnish Meteorological Institute
Hitoshi Matsui: Nagoya University
Paul Ginoux: NOAA, Geophysical Fluid Dynamics Laboratory
Toshihiko Takemura: Kyushu University
Philippe Sager: Royal Netherlands Meteorological Institute
Samuel Rémy: HYGEOS
Huisheng Bian: University of Maryland, Baltimore County (UMBC)
Mian Chin: NASA Goddard Space Flight Center

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: Abstract 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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33680-4

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DOI: 10.1038/s41467-022-33680-4

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