Satellite-based evaluation of AeroCom model bias in biomass burning regions
<p>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 be...
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Copernicus Publications
2022-08-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/22/11009/2022/acp-22-11009-2022.pdf |
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| author | Q. Zhong N. Schutgens G. van der Werf T. van Noije K. Tsigaridis K. Tsigaridis S. E. Bauer S. E. Bauer T. Mielonen A. Kirkevåg Ø. Seland H. Kokkola R. Checa-Garcia D. Neubauer Z. Kipling H. Matsui P. Ginoux T. Takemura P. Le Sager S. Rémy H. Bian H. Bian M. Chin K. Zhang J. Zhu S. G. Tsyro G. Curci G. Curci A. Protonotariou B. Johnson J. E. Penner N. Bellouin R. B. Skeie G. Myhre |
| author_facet | Q. Zhong N. Schutgens G. van der Werf T. van Noije K. Tsigaridis K. Tsigaridis S. E. Bauer S. E. Bauer T. Mielonen A. Kirkevåg Ø. Seland H. Kokkola R. Checa-Garcia D. Neubauer Z. Kipling H. Matsui P. Ginoux T. Takemura P. Le Sager S. Rémy H. Bian H. Bian M. Chin K. Zhang J. Zhu S. G. Tsyro G. Curci G. Curci A. Protonotariou B. Johnson J. E. Penner N. Bellouin R. B. Skeie G. Myhre |
| author_sort | Q. Zhong |
| collection | DOAJ |
| description | <p>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 <span class="inline-formula">−93</span> % 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.</p> |
| first_indexed | 2024-04-13T23:39:13Z |
| format | Article |
| id | doaj.art-b3723aecf29f4bfe9bef6e57f1608660 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-13T23:39:13Z |
| publishDate | 2022-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-b3723aecf29f4bfe9bef6e57f16086602022-12-22T02:24:37ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242022-08-0122110091103210.5194/acp-22-11009-2022Satellite-based evaluation of AeroCom model bias in biomass burning regionsQ. Zhong0N. Schutgens1G. van der Werf2T. van Noije3K. Tsigaridis4K. Tsigaridis5S. E. Bauer6S. E. Bauer7T. Mielonen8A. Kirkevåg9Ø. Seland10H. Kokkola11R. Checa-Garcia12D. Neubauer13Z. Kipling14H. Matsui15P. Ginoux16T. Takemura17P. Le Sager18S. Rémy19H. Bian20H. Bian21M. Chin22K. Zhang23J. Zhu24S. G. Tsyro25G. Curci26G. Curci27A. Protonotariou28B. Johnson29J. E. Penner30N. Bellouin31R. B. Skeie32G. Myhre33Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the NetherlandsDepartment of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the NetherlandsDepartment of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the NetherlandsRoyal Netherlands Meteorological Institute, De Bilt, the NetherlandsCenter for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY, USANASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY, USACenter for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY, USANASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY, USAFinnish Meteorological Institute, Kuopio, FinlandNorwegian Meteorological Institute, Oslo, NorwayNorwegian Meteorological Institute, Oslo, NorwayFinnish Meteorological Institute, Kuopio, FinlandLaboratoire des Sciences du Climat et de l'Environnement, IPSL, Gif-sur-Yvette, FranceInstitute for Atmospheric and Climate Science, ETH Zurich, Zurich, SwitzerlandEuropean Centre for Medium-Range Weather Forecasts, Reading, UKGraduate School of Environmental Studies, Nagoya University, Nagoya, JapanGeophysical Fluid Dynamics Laboratory, NOAA, Princeton, NJ, USAResearch Institute for Applied Mechanics, Kyushu University, Fukuoka, JapanRoyal Netherlands Meteorological Institute, De Bilt, the NetherlandsHYGEOS, Lille, FranceJoint Center for Earth Systems Technology, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USANASA Goddard Space Flight Center, Greenbelt, MD, USANASA Goddard Space Flight Center, Greenbelt, MD, USAPacific Northwest National Laboratory, Richland, WA, USAInstitute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, ChinaNorwegian Meteorological Institute, Oslo, NorwayDepartment of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, ItalyCenter of Excellence in Telesensing of Environment and Model Prediction of Severe Events (CETEMPS), University of L'Aquila, L'Aquila, ItalyDepartment of Physics, University of Athens, Athens, GreeceMet Office, Exeter, UKDepartment of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USADepartment of Meteorology, University of Reading, Reading, UKCenter for International Climate and Environmental Research (CICERO), Oslo, NorwayCenter for International Climate and Environmental Research (CICERO), Oslo, Norway<p>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 <span class="inline-formula">−93</span> % 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.</p>https://acp.copernicus.org/articles/22/11009/2022/acp-22-11009-2022.pdf |
| spellingShingle | Q. Zhong N. Schutgens G. van der Werf T. van Noije K. Tsigaridis K. Tsigaridis S. E. Bauer S. E. Bauer T. Mielonen A. Kirkevåg Ø. Seland H. Kokkola R. Checa-Garcia D. Neubauer Z. Kipling H. Matsui P. Ginoux T. Takemura P. Le Sager S. Rémy H. Bian H. Bian M. Chin K. Zhang J. Zhu S. G. Tsyro G. Curci G. Curci A. Protonotariou B. Johnson J. E. Penner N. Bellouin R. B. Skeie G. Myhre Satellite-based evaluation of AeroCom model bias in biomass burning regions Atmospheric Chemistry and Physics |
| title | Satellite-based evaluation of AeroCom model bias in biomass burning regions |
| title_full | Satellite-based evaluation of AeroCom model bias in biomass burning regions |
| title_fullStr | Satellite-based evaluation of AeroCom model bias in biomass burning regions |
| title_full_unstemmed | Satellite-based evaluation of AeroCom model bias in biomass burning regions |
| title_short | Satellite-based evaluation of AeroCom model bias in biomass burning regions |
| title_sort | satellite based evaluation of aerocom model bias in biomass burning regions |
| url | https://acp.copernicus.org/articles/22/11009/2022/acp-22-11009-2022.pdf |
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