Interhemispheric differences in seasonal cycles of tropospheric ozone in the marine boundary layer:observation - model comparisons
Marine boundary layer ozone seasonal cycles have been quantified by fitting the sum of two sine curves through monthly detrended observations taken at three stations: Mace Head, Ireland, and Trinidad Head, California, in the Northern Hemisphere and Cape Grim, Tasmania, in the Southern Hemisphere. Th...
| Published in: | Journal of Geophysical Research: Atmospheres |
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| Main Authors: | , , , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://eprints.lancs.ac.uk/id/eprint/80790/ https://eprints.lancs.ac.uk/id/eprint/80790/1/784831_3_merged_pdf_4154935_lblshm.pdf https://eprints.lancs.ac.uk/id/eprint/80790/4/Derwent_et_al_2016_Journal_of_Geophysical_Research_Atmospheres.pdf https://doi.org/10.1002/2016JD024836 |
| Summary: | Marine boundary layer ozone seasonal cycles have been quantified by fitting the sum of two sine curves through monthly detrended observations taken at three stations: Mace Head, Ireland, and Trinidad Head, California, in the Northern Hemisphere and Cape Grim, Tasmania, in the Southern Hemisphere. The parameters defining the sine curve fits at these stations have been compared with those from a global Lagrangian chemistry-transport model and from 14 Atmospheric Chemistry Coupled Climate Model Intercomparison Project chemistry-climate models. Most models substantially overestimated the long-term average ozone levels at Trinidad Head, while they performed much better for Mace Head and Cape Grim. This led to an underestimation of the observed (North Atlantic inflow-North Pacific inflow) difference. The models generally underpredicted the magnitude of the fundamental term of the fitted seasonal cycle, most strongly at Cape Grim. The models more accurately reproduced the observed second harmonic terms compared to the fundamental terms at all stations. Significant correlations have been identified between the errors in the different models' estimates of the seasonal cycle parameters; these correlations may yield further insights into the causes of the model-measurement discrepancies. |
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