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A study of the Arctic NO budget above Eureka, Canada

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Published copy (DOI)

Author(s)

  • R. Lindenmaier
  • K. Strong
  • A.I. Jonsson
  • F. Kolonjari
  • K.A. Walker
  • R.L. Batchelor
  • P.F. Bernath
  • S. Chabrillat
  • M.P. Chipperfield
  • W. Feng
  • W.H. Daffer
  • G.L. Manney
  • J.R. Drummond
  • C. McLinden
  • R. Ménard

Department/unit(s)

Publication details

JournalJournal of Geophysical Research: Atmospheres
DatePublished - 1 Jan 2011
Issue number23
Volume116
Original languageEnglish

Abstract

Four years of trace gas measurements have been acquired using the Bruker 125HR Fourier Transform Infrared (FTIR) spectrometer installed at the Polar Environment Atmospheric Research Laboratory (PEARL) in the Canadian high Arctic. These have been compared with data from three models, namely the Canadian Middle Atmosphere Model Data Assimilation System (CMAM-DAS), the Global Environmental Multiscale stratospheric model with the online Belgium Atmospheric CHemistry package (GEM-BACH), and the off-line 3D chemical transport model SLIMCAT to assess the total reactive nitrogen, NO , budget above Eureka, Nunavut (80.05°N, 86.42°W). The FTIR data have been also compared with satellite measurements by the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS). The FTIR is able to measure four of the five primary species that form NO : NO, NO , HNO , and ClONO , while the fifth, N O , was obtained using the N O /(NO + NO ) ratio derived from the models and ACE-FTS. Combining these results, a four-year time series of NO 15-40 km partial columns was calculated. Comparisons with each model were made, revealing mean differences (± standard error of the mean) relative to the FTIR of (-16.0 ± 0.6)%, (5.5 ± 1.0)%, and (-5.8 ± 0.4)% for CMAM-DAS, GEM-BACH, and SLIMCAT, respectively. The mean difference between the ACE-FTS and FTIR NO partial columns was (5.6 ± 2.3)%. While we found no significant seasonal and interannual differences in the FTIR NO stratospheric columns, the partial columns display nearly twice as much variability during the spring compared to the summer period.

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