Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models part...

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Main Authors: C. Orbe, H. Yang, D. W. Waugh, G. Zeng, O. Morgenstern, D. E. Kinnison, J.-F. Lamarque, S. Tilmes, D. A. Plummer, J. F. Scinocca, B. Josse, V. Marecal, P. Jöckel, L. D. Oman, S. E. Strahan, M. Deushi, T. Y. Tanaka, K. Yoshida, H. Akiyoshi, Y. Yamashita, A. Stenke, L. Revell, T. Sukhodolov, E. Rozanov, G. Pitari, D. Visioni, K. A. Stone, R. Schofield, A. Banerjee
Format: Article
Language:English
Published: Copernicus Publications 2018-05-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/18/7217/2018/acp-18-7217-2018.pdf
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author C. Orbe
C. Orbe
C. Orbe
C. Orbe
H. Yang
D. W. Waugh
G. Zeng
O. Morgenstern
D. E. Kinnison
J.-F. Lamarque
S. Tilmes
D. A. Plummer
J. F. Scinocca
B. Josse
V. Marecal
P. Jöckel
L. D. Oman
S. E. Strahan
S. E. Strahan
M. Deushi
T. Y. Tanaka
K. Yoshida
H. Akiyoshi
Y. Yamashita
Y. Yamashita
A. Stenke
L. Revell
L. Revell
T. Sukhodolov
T. Sukhodolov
E. Rozanov
E. Rozanov
G. Pitari
D. Visioni
K. A. Stone
K. A. Stone
K. A. Stone
R. Schofield
R. Schofield
A. Banerjee
spellingShingle C. Orbe
C. Orbe
C. Orbe
C. Orbe
H. Yang
D. W. Waugh
G. Zeng
O. Morgenstern
D. E. Kinnison
J.-F. Lamarque
S. Tilmes
D. A. Plummer
J. F. Scinocca
B. Josse
V. Marecal
P. Jöckel
L. D. Oman
S. E. Strahan
S. E. Strahan
M. Deushi
T. Y. Tanaka
K. Yoshida
H. Akiyoshi
Y. Yamashita
Y. Yamashita
A. Stenke
L. Revell
L. Revell
T. Sukhodolov
T. Sukhodolov
E. Rozanov
E. Rozanov
G. Pitari
D. Visioni
K. A. Stone
K. A. Stone
K. A. Stone
R. Schofield
R. Schofield
A. Banerjee
Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
Atmospheric Chemistry and Physics
author_facet C. Orbe
C. Orbe
C. Orbe
C. Orbe
H. Yang
D. W. Waugh
G. Zeng
O. Morgenstern
D. E. Kinnison
J.-F. Lamarque
S. Tilmes
D. A. Plummer
J. F. Scinocca
B. Josse
V. Marecal
P. Jöckel
L. D. Oman
S. E. Strahan
S. E. Strahan
M. Deushi
T. Y. Tanaka
K. Yoshida
H. Akiyoshi
Y. Yamashita
Y. Yamashita
A. Stenke
L. Revell
L. Revell
T. Sukhodolov
T. Sukhodolov
E. Rozanov
E. Rozanov
G. Pitari
D. Visioni
K. A. Stone
K. A. Stone
K. A. Stone
R. Schofield
R. Schofield
A. Banerjee
author_sort C. Orbe
title Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
title_short Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
title_full Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
title_fullStr Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
title_full_unstemmed Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations
title_sort large-scale tropospheric transport in the chemistry–climate model initiative (ccmi) simulations
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2018-05-01
description Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.
url https://www.atmos-chem-phys.net/18/7217/2018/acp-18-7217-2018.pdf
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spelling doaj-3804d5f2cc0d4e038251289a554bb6362020-11-24T23:15:33ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-05-01187217723510.5194/acp-18-7217-2018Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulationsC. Orbe0C. Orbe1C. Orbe2C. Orbe3H. Yang4D. W. Waugh5G. Zeng6O. Morgenstern7D. E. Kinnison8J.-F. Lamarque9S. Tilmes10D. A. Plummer11J. F. Scinocca12B. Josse13V. Marecal14P. Jöckel15L. D. Oman16S. E. Strahan17S. E. Strahan18M. Deushi19T. Y. Tanaka20K. Yoshida21H. Akiyoshi22Y. Yamashita23Y. Yamashita24A. Stenke25L. Revell26L. Revell27T. Sukhodolov28T. Sukhodolov29E. Rozanov30E. Rozanov31G. Pitari32D. Visioni33K. A. Stone34K. A. Stone35K. A. Stone36R. Schofield37R. Schofield38A. Banerjee39Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD, USAGlobal Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USADepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USAnow at: NASA Goddard Institute for Space Studies, New York, NY, USADepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USADepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USANational Institute of Water and Atmospheric Research, Wellington, New ZealandNational Institute of Water and Atmospheric Research, Wellington, New ZealandNational Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations and Modeling (ACOM) Laboratory, Boulder, USANational Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations and Modeling (ACOM) Laboratory, Boulder, USANational Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations and Modeling (ACOM) Laboratory, Boulder, USAClimate Research Branch, Environment and Climate Change Canada, Montreal, QC, CanadaClimate Research Branch, Environment and Climate Change Canada, Victoria, BC, CanadaCentre National de Recherches Météorologiques UMR 3589, Météo-France/CNRS, Toulouse, FranceCentre National de Recherches Météorologiques UMR 3589, Météo-France/CNRS, Toulouse, FranceDeutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyAtmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USAAtmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USAUniversities Space Research Association, Columbia, MD, USAMeteorological Research Institute (MRI), Tsukuba, JapanMeteorological Research Institute (MRI), Tsukuba, JapanMeteorological Research Institute (MRI), Tsukuba, JapanClimate Modeling and Analysis Section, Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, JapanClimate Modeling and Analysis Section, Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, JapanJapan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, JapanInstitute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, SwitzerlandInstitute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, SwitzerlandBodeker Scientific, Christchurch, New ZealandInstitute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, SwitzerlandPhysikalisch-Meteorologisches Observatorium Davos/World Radiation Centre, Davos, SwitzerlandInstitute for Atmospheric and Climate Science, ETH Zürich (ETHZ), Zürich, SwitzerlandPhysikalisch-Meteorologisches Observatorium Davos/World Radiation Centre, Davos, SwitzerlandDepartment of Physical and Chemical Sciences, Universitá dell'Aquila, L'Aquila, ItalyDepartment of Physical and Chemical Sciences, Universitá dell'Aquila, L'Aquila, ItalySchool of Earth Sciences, University of Melbourne, Melbourne, Victoria 3010, AustraliaARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, New South Wales 2052, Australianow at: Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, USASchool of Earth Sciences, University of Melbourne, Melbourne, Victoria 3010, AustraliaARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, New South Wales 2052, AustraliaDepartment of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USAUnderstanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.https://www.atmos-chem-phys.net/18/7217/2018/acp-18-7217-2018.pdf