Articles | Volume 15, issue 12
Atmos. Chem. Phys., 15, 6721–6744, 2015

Special issue: POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface...

Atmos. Chem. Phys., 15, 6721–6744, 2015
Research article
17 Jun 2015
Research article | 17 Jun 2015

The POLARCAT Model Intercomparison Project (POLMIP): overview and evaluation with observations

L. K. Emmons1, S. R. Arnold2, S. A. Monks2, V. Huijnen3, S. Tilmes1, K. S. Law4, J. L. Thomas4, J.-C. Raut4, I. Bouarar4,*, S. Turquety5, Y. Long5, B. Duncan6, S. Steenrod6, S. Strode6,21, J. Flemming7, J. Mao8, J. Langner9, A. M. Thompson6, D. Tarasick10, E. C. Apel1, D. R. Blake11, R. C. Cohen12, J. Dibb13, G. S. Diskin14, A. Fried15, S. R. Hall1, L. G. Huey16, A. J. Weinheimer1, A. Wisthaler17,18, T. Mikoviny17,18, J. Nowak19,**, J. Peischl19, J. M. Roberts19, T. Ryerson19, C. Warneke19, and D. Helmig20 L. K. Emmons et al.
  • 1Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, CO, USA
  • 2Institute for Climate and Atmospheric Science, University of Leeds, Leeds, UK
  • 3Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
  • 4Sorbonne Universités, UPMC Univ. Paris 06, Université Versailles St-Quentin, CNRS/INSU, LATMOS-IPSL, UMR8190, Paris, France
  • 5Laboratoire de Météorologie Dynamique, IPSL, CNRS, UMR8539, 91128 Palaiseau CEDEX, France
  • 6NASA Goddard, Atmospheric Chemistry and Dynamics Laboratory, Code 614, Greenbelt, Maryland, USA
  • 7ECMWF, Reading, UK
  • 8NOAA GFDL and Princeton University, Princeton, NJ, USA
  • 9Swedish Meteorological and Hydrological Institute, 60176 Nörrkping, Sweden
  • 10Environment Canada, Downsview, Ontario, Canada
  • 11Department of Chemistry, University of California-Irvine, Irvine, CA, USA
  • 12Chemistry Department, University of California-Berkeley, Berkeley, CA, USA
  • 13University of New Hampshire, Durham, NH, USA
  • 14NASA Langley Research Center, Chemistry and Dynamics Branch, Hampton, VA, USA
  • 15University of Colorado, Boulder, CO, USA
  • 16Georgia Institute of Technology, Atlanta, GA, USA
  • 17University of Innsbruck, Innsbruck, Austria
  • 18University of Oslo, Oslo, Norway
  • 19NOAA Earth System Research Lab, Boulder, CO, USA
  • 20INSTAAR, University of Colorado, Boulder, CO, USA
  • 21Universities Space Research Association, Columbia, MD, USA
  • *now at: Max Planck Institute for Meteorology (MPI-M), Hamburg, Germany
  • **now at: Aerodyne Research, Inc., Billerica, MA, USA

Abstract. A model intercomparison activity was inspired by the large suite of observations of atmospheric composition made during the International Polar Year (2008) in the Arctic. Nine global and two regional chemical transport models participated in this intercomparison and performed simulations for 2008 using a common emissions inventory to assess the differences in model chemistry and transport schemes. This paper summarizes the models and compares their simulations of ozone and its precursors and presents an evaluation of the simulations using a variety of surface, balloon, aircraft and satellite observations. Each type of measurement has some limitations in spatial or temporal coverage or in composition, but together they assist in quantifying the limitations of the models in the Arctic and surrounding regions. Despite using the same emissions, large differences are seen among the models. The cloud fields and photolysis rates are shown to vary greatly among the models, indicating one source of the differences in the simulated chemical species. The largest differences among models, and between models and observations, are in NOy partitioning (PAN vs. HNO3) and in oxygenated volatile organic compounds (VOCs) such as acetaldehyde and acetone. Comparisons to surface site measurements of ethane and propane indicate that the emissions of these species are significantly underestimated. Satellite observations of NO2 from the OMI (Ozone Monitoring Instrument) have been used to evaluate the models over source regions, indicating anthropogenic emissions are underestimated in East Asia, but fire emissions are generally overestimated. The emission factors for wildfires in Canada are evaluated using the correlations of VOCs to CO in the model output in comparison to enhancement factors derived from aircraft observations, showing reasonable agreement for methanol and acetaldehyde but underestimate ethanol, propane and acetone, while overestimating ethane emission factors.

Short summary
Eleven 3-D tropospheric chemistry models have been compared and evaluated with observations in the Arctic during the International Polar Year (IPY 2008). Large differences are seen among the models, particularly related to the model chemistry of volatile organic compounds (VOCs) and reactive nitrogen (NOx, PAN, HNO3) partitioning. Consistency among the models in the underestimation of CO, ethane and propane indicates the emission inventory is too low for these compounds.
Final-revised paper