Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3109-2018
https://doi.org/10.5194/gmd-11-3109-2018
Model experiment description paper
 | 
03 Aug 2018
Model experiment description paper |  | 03 Aug 2018

Age of air as a diagnostic for transport timescales in global models

Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield

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Cited articles

Arakawa, A. and Schubert, W. H.: Interaction of a Cumulus Cloud Ensemble with the Large-Scale Environment, Part I, J. Atmos. Sci., 31, 674–701, 1974.
Austin, P. M. and Houze Jr., R. A.: A technique for computing vertical transports by precipitating cumuli, J. Atmos. Sci., 30, 1100–1111, 1973.
Bândă, N., Krol, M., Noije, T., Weele, M., Williams, J. E., Sager, P. L., Niemeier, U., Thomason, L., and Rockmann, T.: The effect of stratospheric sulfur from Mount Pinatubo on tropospheric oxidizing capacity and methane, J. Geophys. Res.-Atmos., 120, 1202–1220, 2015.
Belikov, D. A., Maksyutov, S., Sherlock, V., Aoki, S., Deutscher, N. M., Dohe, S., Griffith, D., Kyro, E., Morino, I., Nakazawa, T., Notholt, J., Rettinger, M., Schneider, M., Sussmann, R., Toon, G. C., Wennberg, P. O., and Wunch, D.: Simulations of column-averaged CO2 and CH4 using the NIES TM with a hybrid sigma-isentropic (σ-θ) vertical coordinate, Atmos. Chem. Phys., 13, 1713–1732, https://doi.org/10.5194/acp-13-1713-2013, 2013.
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The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.