Satellite-based evaluation of AeroCom model bias in biomass burning regions
Authors: Zhong Qirui , Schutgens Nick , van der Werf Guido , van Noije Twan , Tsigaridis Kostas , Bauer Susanne E. , Mielonen Tero , Kirkevåg Alf , Seland Øyvind , Kokkola Harri , Checa-Garcia Ramiro , Neubauer David , Kipling Zak , Matsui Hitoshi , Ginoux Paul , Takemura Toshihiko , Le Sager Philippe , Rémy Samuel , Bian Huisheng , Chin Mian , Zhang Kai , Zhu Jialei , Tsyro Svetlana G. , Curci Gabriele , Protonotariou Anna , Johnson Ben , Penner Joyce E. , Bellouin Nicolas , Skeie Ragnhild B. , Myhre Gunnar 
Published: August 2022

Abstract. Global models are widely used to simulate biomass burning
aerosol (BBA). Exhaustive evaluations on model representation of aerosol
distributions and properties are fundamental to assess health and climate
impacts of BBA. Here we conducted a comprehensive comparison of Aerosol
Comparisons between Observations and Models (AeroCom) project model simulations with
satellite observations. A total of 59 runs by 18 models from three AeroCom
Phase-III experiments (i.e., biomass burning emissions, CTRL16, and CTRL19)
and 14 satellite products of aerosols were used in the study. Aerosol
optical depth (AOD) at 550 nm was investigated during the fire season over
three key fire regions reflecting different fire dynamics (i.e.,
deforestation-dominated Amazon, Southern Hemisphere Africa where savannas
are the key source of emissions, and boreal forest burning in boreal North
America). The 14 satellite products were first evaluated against AErosol
RObotic NETwork (AERONET) observations, with large uncertainties found. But
these uncertainties had small impacts on the model evaluation that was
dominated by modeling bias. Through a comparison with Polarization and Directionality of the Earth’s Reflectances measurements with the Generalized Retrieval of Aerosol and Surface Properties algorithm (POLDER-GRASP), we
found that the modeled AOD values were biased by −93 % to 152 %, with most
models showing significant underestimations even for the state-of-the-art
aerosol modeling techniques (i.e., CTRL19). By scaling up BBA emissions, the
negative biases in modeled AOD were significantly mitigated, although it
yielded only negligible improvements in the correlation between models and
observations, and the spatial and temporal variations in AOD biases did not
change much. For models in CTRL16 and CTRL19, the large diversity in modeled
AOD was in almost equal measures caused by diversity in emissions, lifetime,
and the mass extinction coefficient (MEC). We found that in the AeroCom
ensemble, BBA lifetime correlated significantly with particle deposition (as
expected) and in turn correlated strongly with precipitation. Additional
analysis based on Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP)
aerosol profiles suggested that the altitude of the aerosol layer in the
current models was generally too low, which also contributed to the bias in
modeled lifetime. Modeled MECs exhibited significant correlations with the
Ångström exponent (AE, an indicator of particle size). Comparisons
with the POLDER-GRASP-observed AE suggested that the models tended to
overestimate the AE (underestimated particle size), indicating a possible
underestimation of MECs in models. The hygroscopic growth in most models
generally agreed with observations and might not explain the overall
underestimation of modeled AOD. Our results imply that current global models
contain biases in important aerosol processes for BBA (e.g., emissions,
removal, and optical properties) that remain to be addressed in future
research.