The ENSO signal in atmospheric composition fields: emission driven vs. dynamically induced changes
Author:
Inness A.ORCID, Benedetti A., Flemming J., Huijnen V., Kaiser J. W.ORCID, Parrington M., Remy S.
Abstract
Abstract. The El Niño Southern Oscillation (ENSO) does not only affect meteorological fields but also has a large impact on atmospheric composition. Atmospheric composition fields from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis are used to identify the ENSO signal in tropospheric ozone, carbon monoxide, nitrogen oxide and smoke aerosols, concentrating on the months October to December. During El Niño years all these fields have increased concentrations over maritime South East Asia in October. The MACC Composition Integrated Forecasting System (C-IFS) model is used to quantify the relative magnitude of dynamically induced and emission driven changes in the atmospheric composition fields. While changes in tropospheric ozone are a combination of dynamically induced and emission driven changes, the changes in carbon monoxide, nitrogen oxide and smoke aerosols are almost entirely emission driven in the MACC model. The ozone changes continue into December, i.e. after the end of the Indonesian fire season while changes in the other fields are confined to the fire season.
Funder
European Commission Seventh Framework Programme
Publisher
Copernicus GmbH
Reference46 articles.
1. Allan, R. J., Lindesay, J., and Parker, D. E.: El Niño Southern Oscillation and climatic variability, CSIRO Publishing, Collingwood, Victoria, Australia, ISBN: 9780643058033, 416 pp., 1996. 2. Aouizerats, B., van der Werf, G. R., Balasubramanian, R., and Betha, R.: Importance of transboundary transport of biomass burning emissions to regional air quality in Southeast Asia during a high fire event, Atmos. Chem. Phys., 15, 363–373, https://doi.org/10.5194/acp-15-363-2015, 2015. 3. Barkley, M.: Description of MEGAN biogenic VOC emissions in GEOS-Chem, available at: http://acmg.seas.harvard.edu/geos/wiki_docs/emissions/megan.pdf (last access: 11 May 2015), 2010. 4. Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Mangold, A., Razinger, M., Simmons, A. J., Suttie, M., and the GEMS-AER Team: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res., 114, D13205, https://doi.org/10.1029/2008JD011115, 2009. 5. Cariolle, D. and Teyssèdre, H.: A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations, Atmos. Chem. Phys., 7, 2183–2196, https://doi.org/10.5194/acp-7-2183-2007, 2007.
|
|