Articles | Volume 18, issue 19
https://doi.org/10.5194/acp-18-14715-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-18-14715-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of mean age of air in five reanalyses using the BASCOE transport model
Simon Chabrillat
CORRESPONDING AUTHOR
Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Corinne Vigouroux
Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Yves Christophe
Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Andreas Engel
Institute for Atmospheric and Environmental Science, Goethe University Frankfurt, Frankfurt, Germany
Quentin Errera
Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Daniele Minganti
Royal Belgian Institute for Space Aeronomy, BIRA-IASB, Brussels, Belgium
Beatriz M. Monge-Sanz
European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Arjo Segers
TNO, Department of Climate, Air and Sustainability, P.O. Box 80015, Utrecht, the Netherlands
Emmanuel Mahieu
Institute of Astrophysics and Geophysics, University of Liège, Liège, Belgium
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23 citations as recorded by crossref.
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- New Insights on the Impact of Ozone‐Depleting Substances on the Brewer‐Dobson Circulation M. Abalos et al. 10.1029/2018JD029301
- A convolution of observational and model data to estimate age of air spectra in the northern hemispheric lower stratosphere M. Hauck et al. 10.5194/acp-20-8763-2020
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- The advective Brewer–Dobson circulation in the ERA5 reanalysis: climatology, variability, and trends M. Diallo et al. 10.5194/acp-21-7515-2021
- The stratospheric Brewer–Dobson circulation inferred from age of air in the ERA5 reanalysis F. Ploeger et al. 10.5194/acp-21-8393-2021
- Technical note: Reanalysis of Aura MLS chemical observations Q. Errera et al. 10.5194/acp-19-13647-2019
- Is the recovery of stratospheric O<sub>3</sub> speeding up in the Southern Hemisphere? An evaluation from the first IASI decadal record (2008–2017) C. Wespes et al. 10.5194/acp-19-14031-2019
- Hemispheric asymmetries in recent changes in the stratospheric circulation F. Ploeger & H. Garny 10.5194/acp-22-5559-2022
- Age of air from in situ trace gas measurements: insights from a new technique E. Ray et al. 10.5194/acp-24-12425-2024
- Microwave radiometer observations of the ozone diurnal cycle and its short-term variability over Switzerland E. Sauvageat et al. 10.5194/acp-23-7321-2023
- Estimating the Meridional Extent of Adiabatic Mixing in the Stratosphere Using Age‐Of‐Air A. Gupta et al. 10.1029/2022JD037712
- Satellite data validation: a parametrization of the natural variability of atmospheric mixing ratios A. Laeng et al. 10.5194/amt-15-2407-2022
- Stratospheric Fluorine as a Tracer of Circulation Changes: Comparison Between Infrared Remote‐Sensing Observations and Simulations With Five Modern Reanalyses M. Prignon et al. 10.1029/2021JD034995
- Impacts of a near-future supersonic aircraft fleet on atmospheric composition and climate S. Eastham et al. 10.1039/D1EA00081K
- Three-dimensional simulation of stratospheric gravitational separation using the NIES global atmospheric tracer transport model D. Belikov et al. 10.5194/acp-19-5349-2019
- Improved FTIR retrieval strategy for HCFC-22 (CHClF<sub>2</sub>), comparisons with in situ and satellite datasets with the support of models, and determination of its long-term trend above Jungfraujoch M. Prignon et al. 10.5194/acp-19-12309-2019
- Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates M. Zheng et al. 10.5194/gmd-16-7037-2023
- Mechanisms Linked to Recent Ozone Decreases in the Northern Hemisphere Lower Stratosphere C. Orbe et al. 10.1029/2019JD031631
- Gravitational separation of Ar∕N<sub>2</sub> and age of air in the lowermost stratosphere in airborne observations and a chemical transport model B. Birner et al. 10.5194/acp-20-12391-2020
Latest update: 20 Nov 2024
Short summary
Mean age of stratospheric air is computed for the period 1989–2015 with a kinematic transport model which uses surface pressure and wind fields from five reanalyses: ERA-I, MERRA-2, MERRA, CFSR, JRA-55. The spread between the resulting datasets is as large as in climate model intercomparisons; the age trends have large disagreement and depend strongly on the considered period. We highlight the need for similar studies using diabatic transport models which also use temperature and heating rates.
Mean age of stratospheric air is computed for the period 1989–2015 with a kinematic transport...
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