Using transport diagnostics to understand chemistry climate model ozone simulations

• Published in: Journal of Geophysical Research
• Main Authors: Strahan, S. E., Douglass, A. R., Stolarski, R. S., Akiyoshi, H., Bekki, Slimane, Braesicke, P., Butchart, N., Chipperfield, M. P., Cugnet, David, Dhomse, S., Frith, S. M., Gettelman, A., Hardiman, S. C., Kinnison, D. E., Lamarque, J.-F., Mancini, E., Marchand, Marion, Michou, M., Morgenstern, Olaf, Nakamura, T., Olivié, D., Pawson, S., Pitari, G., Plummer, D. A., Pyle, J. A., Scinocca, J. F., Shepherd, T. G., Shibata, K., Smale, Dan, Teyssèdre, H., Tian, W., Yamashita, Y.
• Other Authors: Universities Space Research Association Washington (USRA), NASA Goddard Space Flight Center (GSFC), National Institute for Environmental Studies (NIES), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre for Atmospheric Science Cambridge, UK, University of Cambridge UK (CAM), Met Office Hadley Centre (MOHC), United Kingdom Met Office Exeter, School of Earth and Environment Leeds (SEE), University of Leeds, Science Systems and Applications, Inc. Lanham (SSAI), National Center for Atmospheric Research Boulder (NCAR), University of L'Aquila Italy (UNIVAQ), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research Lauder (NIWA), Department of Geosciences Oslo, Faculty of Mathematics and Natural Sciences Oslo, University of Oslo (UiO)-University of Oslo (UiO), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Department of Physics Toronto, University of Toronto, Meteorological Research Institute Tsukuba (MRI), Japan Meteorological Agency (JMA)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2011
• Subjects: Stratospheric transport; [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]; [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology; Antarctic; Antarc*
• Online Access: https://hal.science/hal-00621937; https://hal.science/hal-00621937/document; https://hal.science/hal-00621937/file/2010JD015360.pdf; https://doi.org/10.1029/2010JD015360

International audience We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process-oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return-to-1980 dates for global (60°S-60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.