Articles | Volume 8, issue 1
Earth Syst. Sci. Data, 8, 41–59, 2016
https://doi.org/10.5194/essd-8-41-2016
Earth Syst. Sci. Data, 8, 41–59, 2016
https://doi.org/10.5194/essd-8-41-2016

  11 Feb 2016

11 Feb 2016

Gridded global surface ozone metrics for atmospheric chemistry model evaluation

E. D. Sofen et al.

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Cited articles

AMEC Environment and Infrastructure, Inc.: Clean Air Status and Trends Network (CASTNET) 2012 Annual Report, Tech. rep., Prepared for U.S. Environmental Protection Agency (EPA), Washington, DC, contract No. EP-W-09-028, 2014.
Amman, M., Bertok, I., Cofala, J., Gyarfas, F., Heyes, C., Klimont, Z., Schöpp, W., and Winiwarter, W.: Baseline Scenarios for the Clean Air for Europe (CAFE) Programme: Final Report, Tech. rep., European Commission Directorate General for Environment, available at: http://ec.europa.eu/environment/archives/cafe/activities/pdf/cafe_scenario_report_1.pdf (last access: 29 July 2015), 2005.
Appel, K. W., Gilliland, A. B., Sarwar, G., and Gilliam, R. C.: Evaluation of the Community Multiscale Air Quality (CMAQ) model version 4.5: sensitivities impacting model performance: Part I – Ozone, Atmos. Environ., 41, 9603–9615, https://doi.org/10.1016/j.atmosenv.2007.08.044, 2007.
Ashmore, M. and Wilson, R. (Eds.): Critical Levels for Air Pollutants for Europe (UN-ECE Workshop Report), Department of the Environment, London, UK, 1994.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: model description and evaluation, J. Geophys. Res., 106, 23073, https://doi.org/10.1029/2001JD000807, 2001.
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Short summary
We have brought together all publicly available surface ozone observations from online databases from 1971–2015, with 2200 sites representing regional background conditions appropriate for the evaluation of chemical transport and chemistry-climate models for projects such as the Chemistry-Climate Model Initiative. Gridded data sets of ozone metrics (mean, percentiles, MDA8, SOMO35, etc.) are available from the British Atmospheric Data Centre.