The AeroCom evaluation and intercomparison of organic aerosol in global models
This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participate...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-10-01
|
| Series: | Atmospheric Chemistry and Physics |
| Online Access: | http://www.atmos-chem-phys.net/14/10845/2014/acp-14-10845-2014.pdf |
| _version_ | 1828333672143519744 |
|---|---|
| author | K. Tsigaridis N. Daskalakis M. Kanakidou P. J. Adams P. Artaxo R. Bahadur Y. Balkanski S. E. Bauer N. Bellouin A. Benedetti T. Bergman T. K. Berntsen J. P. Beukes H. Bian K. S. Carslaw M. Chin G. Curci T. Diehl R. C. Easter S. J. Ghan S. L. Gong A. Hodzic C. R. Hoyle T. Iversen S. Jathar J. L. Jimenez J. W. Kaiser A. Kirkevåg D. Koch H. Kokkola Y. H Lee G. Lin X. Liu G. Luo X. Ma G. W. Mann N. Mihalopoulos J.-J. Morcrette J.-F. Müller G. Myhre S. Myriokefalitakis N. L. Ng D. O'Donnell J. E. Penner L. Pozzoli K. J. Pringle L. M. Russell M. Schulz J. Sciare Ø. Seland D. T. Shindell S. Sillman R. B. Skeie D. Spracklen T. Stavrakou S. D. Steenrod T. Takemura P. Tiitta S. Tilmes H. Tost T. van Noije P. G. van Zyl K. von Salzen F. Yu Z. Wang Z. Wang R. A. Zaveri H. Zhang K. Zhang Q. Zhang X. Zhang |
| author_facet | K. Tsigaridis N. Daskalakis M. Kanakidou P. J. Adams P. Artaxo R. Bahadur Y. Balkanski S. E. Bauer N. Bellouin A. Benedetti T. Bergman T. K. Berntsen J. P. Beukes H. Bian K. S. Carslaw M. Chin G. Curci T. Diehl R. C. Easter S. J. Ghan S. L. Gong A. Hodzic C. R. Hoyle T. Iversen S. Jathar J. L. Jimenez J. W. Kaiser A. Kirkevåg D. Koch H. Kokkola Y. H Lee G. Lin X. Liu G. Luo X. Ma G. W. Mann N. Mihalopoulos J.-J. Morcrette J.-F. Müller G. Myhre S. Myriokefalitakis N. L. Ng D. O'Donnell J. E. Penner L. Pozzoli K. J. Pringle L. M. Russell M. Schulz J. Sciare Ø. Seland D. T. Shindell S. Sillman R. B. Skeie D. Spracklen T. Stavrakou S. D. Steenrod T. Takemura P. Tiitta S. Tilmes H. Tost T. van Noije P. G. van Zyl K. von Salzen F. Yu Z. Wang Z. Wang R. A. Zaveri H. Zhang K. Zhang Q. Zhang X. Zhang |
| author_sort | K. Tsigaridis |
| collection | DOAJ |
| description | This paper evaluates the current status of global modeling of the organic
aerosol (OA) in the troposphere and analyzes the differences between models
as well as between models and observations. Thirty-one global chemistry
transport models (CTMs) and general circulation models
(GCMs) have participated in this intercomparison, in the framework of
AeroCom phase II. The simulation of OA varies greatly between models in terms
of the magnitude of primary emissions, secondary OA (SOA) formation, the
number of OA species used (2 to 62), the complexity of OA parameterizations
(gas-particle partitioning, chemical aging, multiphase chemistry, aerosol
microphysics), and the OA physical, chemical and optical properties. The
diversity of the global OA simulation results has increased since earlier
AeroCom experiments, mainly due to the increasing complexity of the SOA
parameterization in models, and the implementation of new, highly uncertain,
OA sources. Diversity of over one order of magnitude exists in the modeled
vertical distribution of OA concentrations that deserves a dedicated future
study. Furthermore, although the OA / OC ratio depends on OA sources and
atmospheric processing, and is important for model evaluation against OA and
OC observations, it is resolved only by a few global models.
<br><br>
The median global primary OA (POA) source strength is 56 Tg a<sup>−1</sup> (range
34–144 Tg a<sup>−1</sup>) and the median SOA source strength (natural and
anthropogenic) is 19 Tg a<sup>−1</sup> (range 13–121 Tg a<sup>−1</sup>). Among the
models that take into account the semi-volatile SOA nature, the median source
is calculated to be 51 Tg a<sup>−1</sup> (range 16–121 Tg a<sup>−1</sup>), much
larger than the median value of the models that calculate SOA in a more
simplistic way (19 Tg a<sup>−1</sup>; range 13–20 Tg a<sup>−1</sup>, with one model
at 37 Tg a<sup>−1</sup>). The median atmospheric burden of OA is 1.4 Tg (24
models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a
median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported
both OA and sulfate burdens, the median value of the OA/sulfate burden ratio
is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9
models higher than 1. For 26 models that reported OA deposition fluxes, the
median wet removal is 70 Tg a<sup>−1</sup> (range 28–209 Tg a<sup>−1</sup>), which
is on average 85% of the total OA deposition.
<br><br>
Fine aerosol organic carbon (OC) and OA observations from continuous
monitoring networks and individual field campaigns have been used for model
evaluation. At urban locations, the model–observation comparison indicates
missing knowledge on anthropogenic OA sources, both strength and seasonality.
The combined model–measurements analysis suggests the existence of increased
OA levels during summer due to biogenic SOA formation over large areas of the
USA that can be of the same order of magnitude as the POA, even at urban
locations, and contribute to the measured urban seasonal pattern.
<br><br>
Global models are able to simulate the high secondary character of OA
observed in the atmosphere as a result of SOA formation and POA aging,
although the amount of OA present in the atmosphere remains largely
underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51)
based on the comparison against OC (OA) urban data of all models at the
surface, −0.15 (+0.51) when compared with remote measurements, and
−0.30 for marine locations with OC data. The mean temporal correlations
across all stations are low when compared with OC (OA) measurements: 0.47
(0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for
marine stations with OC data. The combination of high (negative) MNB and
higher correlation at urban stations when compared with the low MNB and lower
correlation at remote sites suggests that knowledge about the processes that
govern aerosol processing, transport and removal, on top of their sources, is
important at the remote stations. There is no clear change in model skill
with increasing model complexity with regard to OC or OA mass concentration.
However, the complexity is needed in models in order to distinguish between
anthropogenic and natural OA as needed for climate mitigation, and to
calculate the impact of OA on climate accurately. |
| first_indexed | 2024-04-13T21:24:07Z |
| format | Article |
| id | doaj.art-6b4dc766e0e34c96ad3b8a06255cfabb |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-13T21:24:07Z |
| publishDate | 2014-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-6b4dc766e0e34c96ad3b8a06255cfabb2022-12-22T02:29:23ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242014-10-011419108451089510.5194/acp-14-10845-2014The AeroCom evaluation and intercomparison of organic aerosol in global modelsK. Tsigaridis0N. Daskalakis1M. Kanakidou2P. J. Adams3P. Artaxo4R. Bahadur5Y. Balkanski6S. E. Bauer7N. Bellouin8A. Benedetti9T. Bergman10T. K. Berntsen11J. P. Beukes12H. Bian13K. S. Carslaw14M. Chin15G. Curci16T. Diehl17R. C. Easter18S. J. Ghan19S. L. Gong20A. Hodzic21C. R. Hoyle22T. Iversen23S. Jathar24J. L. Jimenez25J. W. Kaiser26A. Kirkevåg27D. Koch28H. Kokkola29Y. H Lee30G. Lin31X. Liu32G. Luo33X. Ma34G. W. Mann35N. Mihalopoulos36J.-J. Morcrette37J.-F. Müller38G. Myhre39S. Myriokefalitakis40N. L. Ng41D. O'Donnell42J. E. Penner43L. Pozzoli44K. J. Pringle45L. M. Russell46M. Schulz47J. Sciare48Ø. Seland49D. T. Shindell50S. Sillman51R. B. Skeie52D. Spracklen53T. Stavrakou54S. D. Steenrod55T. Takemura56P. Tiitta57S. Tilmes58H. Tost59T. van Noije60P. G. van Zyl61K. von Salzen62F. Yu63Z. Wang64Z. Wang65R. A. Zaveri66H. Zhang67K. Zhang68Q. Zhang69X. Zhang70Center for Climate Systems Research, Columbia University, New York, NY, USAEnvironmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, GreeceEnvironmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, GreeceDepartment of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USAUniversity of São Paulo, Department of Applied Physics, BrazilScripps Institution of Oceanography, University of California San Diego, CA, USALaboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, FranceCenter for Climate Systems Research, Columbia University, New York, NY, USAMet Office Hadley Centre, Exeter, UKECMWF, Reading, UKFinnish Meteorological Institute, Kuopio, FinlandUniversity of Oslo, Department of Geosciences, Oslo, NorwayEnvironmental Sciences and Management, North-West University, Potchefstroom, South AfricaUniversity of Maryland, Joint Center for Environmental Technology, Baltimore County, MD, USASchool of Earth and Environment, University of Leeds, Leeds, UKNASA Goddard Space Flight Center, Greenbelt, MD, USADepartment of Physics CETEMPS, University of L'Aquila, ItalyNASA Goddard Space Flight Center, Greenbelt, MD, USAPacific Northwest National Laboratory; Richland, WA, USAPacific Northwest National Laboratory; Richland, WA, USAAir Quality Research Branch, Meteorological Service of Canada, Toronto, Ontario, CanadaNational Center for Atmospheric Research, Boulder, CO, USAPaul Scherrer Institute, Villigen, SwitzerlandECMWF, Reading, UKDepartment of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USAUniversity of Colorado, Department of Chemistry & Biochemistry, Boulder, CO, USAECMWF, Reading, UKNorwegian Meteorological Institute, Oslo, NorwayCenter for Climate Systems Research, Columbia University, New York, NY, USAFinnish Meteorological Institute, Kuopio, FinlandDepartment of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USADepartment of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, MI, USAPacific Northwest National Laboratory; Richland, WA, USAState University of New York, Albany, NY, USAEnvironment Canada, Victoria, CanadaNational Centre for Atmospheric Science, University of Leeds, Leeds, UKEnvironmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, GreeceECMWF, Reading, UKBelgian Institute for Space Aeronomy, Brussels, BelgiumCenter for International Climate and Environmental Research – Oslo (CICERO), Oslo, NorwayEnvironmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, GreeceSchool of Chemical and Biomolecular Engineering and School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USAMax Planck Institute for Meteorology, Hamburg, GermanyDepartment of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, MI, USAEurasia Institute of Earth Sciences, Istanbul Technical University, TurkeyDepartment of Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, GermanyLaboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, FranceNorwegian Meteorological Institute, Oslo, NorwayLaboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, FranceNorwegian Meteorological Institute, Oslo, NorwayCenter for Climate Systems Research, Columbia University, New York, NY, USADepartment of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, MI, USACenter for International Climate and Environmental Research – Oslo (CICERO), Oslo, NorwaySchool of Earth and Environment, University of Leeds, Leeds, UKBelgian Institute for Space Aeronomy, Brussels, BelgiumUniversities Space Research Association, Greenbelt, MD, USAResearch Institute for Applied Mechanics, Kyushu University, Fukuoka, JapanEnvironmental Sciences and Management, North-West University, Potchefstroom, South AfricaNational Center for Atmospheric Research, Boulder, CO, USAInstitute for Atmospheric Physics, Johannes Gutenberg University, Mainz, GermanyRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsEnvironmental Sciences and Management, North-West University, Potchefstroom, South AfricaEnvironment Canada, Victoria, CanadaState University of New York, Albany, NY, USALaboratory for Climate Studies, Climate Center, China Meteorological Administration, Beijing, ChinaChinese Academy of Meteorological Sciences, Beijing, ChinaPacific Northwest National Laboratory; Richland, WA, USALaboratory for Climate Studies, Climate Center, China Meteorological Administration, Beijing, ChinaPacific Northwest National Laboratory; Richland, WA, USADepartment of Environmental Toxicology, University of California, Davis, CA, USAChinese Academy of Meteorological Sciences, Beijing, ChinaThis paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. <br><br> The median global primary OA (POA) source strength is 56 Tg a<sup>−1</sup> (range 34–144 Tg a<sup>−1</sup>) and the median SOA source strength (natural and anthropogenic) is 19 Tg a<sup>−1</sup> (range 13–121 Tg a<sup>−1</sup>). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a<sup>−1</sup> (range 16–121 Tg a<sup>−1</sup>), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a<sup>−1</sup>; range 13–20 Tg a<sup>−1</sup>, with one model at 37 Tg a<sup>−1</sup>). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a<sup>−1</sup> (range 28–209 Tg a<sup>−1</sup>), which is on average 85% of the total OA deposition. <br><br> Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. <br><br> Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.http://www.atmos-chem-phys.net/14/10845/2014/acp-14-10845-2014.pdf |
| spellingShingle | K. Tsigaridis N. Daskalakis M. Kanakidou P. J. Adams P. Artaxo R. Bahadur Y. Balkanski S. E. Bauer N. Bellouin A. Benedetti T. Bergman T. K. Berntsen J. P. Beukes H. Bian K. S. Carslaw M. Chin G. Curci T. Diehl R. C. Easter S. J. Ghan S. L. Gong A. Hodzic C. R. Hoyle T. Iversen S. Jathar J. L. Jimenez J. W. Kaiser A. Kirkevåg D. Koch H. Kokkola Y. H Lee G. Lin X. Liu G. Luo X. Ma G. W. Mann N. Mihalopoulos J.-J. Morcrette J.-F. Müller G. Myhre S. Myriokefalitakis N. L. Ng D. O'Donnell J. E. Penner L. Pozzoli K. J. Pringle L. M. Russell M. Schulz J. Sciare Ø. Seland D. T. Shindell S. Sillman R. B. Skeie D. Spracklen T. Stavrakou S. D. Steenrod T. Takemura P. Tiitta S. Tilmes H. Tost T. van Noije P. G. van Zyl K. von Salzen F. Yu Z. Wang Z. Wang R. A. Zaveri H. Zhang K. Zhang Q. Zhang X. Zhang The AeroCom evaluation and intercomparison of organic aerosol in global models Atmospheric Chemistry and Physics |
| title | The AeroCom evaluation and intercomparison of organic aerosol in global models |
| title_full | The AeroCom evaluation and intercomparison of organic aerosol in global models |
| title_fullStr | The AeroCom evaluation and intercomparison of organic aerosol in global models |
| title_full_unstemmed | The AeroCom evaluation and intercomparison of organic aerosol in global models |
| title_short | The AeroCom evaluation and intercomparison of organic aerosol in global models |
| title_sort | aerocom evaluation and intercomparison of organic aerosol in global models |
| url | http://www.atmos-chem-phys.net/14/10845/2014/acp-14-10845-2014.pdf |
| work_keys_str_mv | AT ktsigaridis theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ndaskalakis theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mkanakidou theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT pjadams theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT partaxo theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rbahadur theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ybalkanski theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sebauer theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nbellouin theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT abenedetti theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tbergman theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tkberntsen theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jpbeukes theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hbian theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kscarslaw theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mchin theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gcurci theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tdiehl theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rceaster theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sjghan theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT slgong theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ahodzic theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT crhoyle theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tiversen theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sjathar theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jljimenez theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jwkaiser theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT akirkevag theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dkoch theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hkokkola theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT yhlee theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT glin theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xliu theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gluo theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xma theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gwmann theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nmihalopoulos theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jjmorcrette theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jfmuller theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gmyhre theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT smyriokefalitakis theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nlng theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dodonnell theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jepenner theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT lpozzoli theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kjpringle theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT lmrussell theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mschulz theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jsciare theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT øseland theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dtshindell theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ssillman theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rbskeie theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dspracklen theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tstavrakou theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sdsteenrod theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ttakemura theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ptiitta theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT stilmes theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT htost theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tvannoije theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT pgvanzyl theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kvonsalzen theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT fyu theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT zwang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT zwang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT razaveri theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hzhang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kzhang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT qzhang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xzhang theaerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ktsigaridis aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ndaskalakis aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mkanakidou aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT pjadams aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT partaxo aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rbahadur aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ybalkanski aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sebauer aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nbellouin aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT abenedetti aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tbergman aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tkberntsen aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jpbeukes aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hbian aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kscarslaw aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mchin aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gcurci aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tdiehl aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rceaster aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sjghan aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT slgong aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ahodzic aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT crhoyle aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tiversen aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sjathar aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jljimenez aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jwkaiser aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT akirkevag aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dkoch aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hkokkola aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT yhlee aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT glin aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xliu aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gluo aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xma aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gwmann aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nmihalopoulos aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jjmorcrette aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jfmuller aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT gmyhre aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT smyriokefalitakis aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT nlng aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dodonnell aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jepenner aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT lpozzoli aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kjpringle aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT lmrussell aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT mschulz aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT jsciare aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT øseland aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dtshindell aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ssillman aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT rbskeie aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT dspracklen aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tstavrakou aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT sdsteenrod aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ttakemura aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT ptiitta aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT stilmes aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT htost aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT tvannoije aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT pgvanzyl aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kvonsalzen aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT fyu aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT zwang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT zwang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT razaveri aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT hzhang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT kzhang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT qzhang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels AT xzhang aerocomevaluationandintercomparisonoforganicaerosolinglobalmodels |