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Volume 16, issue 21
Atmos. Chem. Phys., 16, 13541-13559, 2016
https://doi.org/10.5194/acp-16-13541-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 16, 13541-13559, 2016
https://doi.org/10.5194/acp-16-13541-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Nov 2016

Research article | 01 Nov 2016

Intercomparison and evaluation of satellite peroxyacetyl nitrate observations in the upper troposphere–lower stratosphere

Richard J. Pope1,2, Nigel A. D. Richards1,2, Martyn P. Chipperfield1,2, David P. Moore3,4, Sarah A. Monks5,7, Stephen R. Arnold1, Norbert Glatthor6, Michael Kiefer6, Tom J. Breider8, Jeremy J. Harrison3,4, John J. Remedios3,4, Carsten Warneke5,7, James M. Roberts5, Glenn S. Diskin9, Lewis G. Huey10, Armin Wisthaler11,12, Eric C. Apel13, Peter F. Bernath14, and Wuhu Feng1,15 Richard J. Pope et al.
  • 1School of Earth and Environment, University of Leeds, Leeds, UK
  • 2National Centre for Earth Observation, University of Leeds, Leeds, UK
  • 3Department of Physics and Astronomy, University of Leicester, Leicester, UK
  • 4National Centre for Earth Observation, University of Leicester, Leicester, UK
  • 5Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
  • 6Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
  • 7Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 8School of Engineering and Applied Sciences, Harvard University, Cambridge, USA
  • 9NASA Langley Research Center, Chemistry and Dynamics Branch, Hampton, VA, USA
  • 10Georgia Institute of Technology, Atlanta, GA, USA
  • 11University of Innsbruck, Innsbruck, Austria
  • 12University of Oslo, Oslo, Norway
  • 13Atmospheric Chemistry Division, National Centre for Atmospheric Research, Boulder, CO, USA
  • 14Department of Chemistry and Biochemistry, Old Dominion University, Norfolk, VA, USA
  • 15National Centre for Atmospheric Science, University of Leeds, Leeds, UK

Abstract. Peroxyacetyl nitrate (PAN) is an important chemical species in the troposphere as it aids the long-range transport of NOx and subsequent formation of O3 in relatively clean remote regions. Over the past few decades observations from aircraft campaigns and surface sites have been used to better understand the regional distribution of PAN. However, recent measurements made by satellites allow for a global assessment of PAN in the upper troposphere–lower stratosphere (UTLS). In this study, we investigate global PAN distributions from two independent retrieval methodologies, based on measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, on board Envisat from the Institute of Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology, and the Department of Physics and Astronomy, University of Leicester (UoL). Retrieving PAN from MIPAS is challenging due to the weak signal in the measurements and contamination from other species. Therefore, we compare the two MIPAS datasets with observations from the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS), in situ aircraft data and the 3-D chemical transport model TOMCAT. MIPAS shows peak UTLS PAN concentrations over the biomass burning regions (e.g. ranging from 150 to  > 200pptv at 150hPa) and during the summertime Asian monsoon as enhanced convection aids the vertical transport of PAN from the lower atmosphere. At 150hPa, we find significant differences between the two MIPAS datasets in the tropics, where IMK PAN concentrations are larger by 50–100pptv. Comparisons between MIPAS and ACE-FTS show better agreement with the UoL MIPAS PAN concentrations at 200hPa, but with mixed results above this altitude. TOMCAT generally captures the magnitude and structure of climatological aircraft PAN profiles within the observational variability allowing it to be used to investigate the MIPAS PAN differences. TOMCAT–MIPAS comparisons show that the model is both positively (UoL) and negatively (IMK) biased against the satellite products. These results indicate that satellite PAN observations are able to detect realistic spatial variations in PAN in the UTLS, but further work is needed to resolve differences in existing retrievals to allow quantitative use of the products.

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