Odin stratospheric proxy NOy measurements and climatology
1Department of Radio and Space Science, Chalmers University of Technology, SE-412 96 Göteborg, Sweden
2Environment Canada, 4905 Dufferin Street, Toronto, Ontario, M3H 5T4, Canada
3Centre for Research in Earth and Space Science, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada
4Department of Physics, University of Toronto, M5S 1A7 Toronto, Ontario, Canada
Abstract. Five years of OSIRIS (Optical Spectrograph and InfraRed Imager System) NO2 and SMR (Sub-Millimetre Radiometer) HNO3 observations from the Odin satellite, combined with data from a photochemical box model, have been used to construct a stratospheric proxy NOy data set including the gases: NO, NO2, HNO3, 2×N2O5 and CIONO2. This Odin NOy climatology is based on all daytime measurements and contains monthly mean and standard deviation, expressed as mixing ratio or number density, as function of latitude or equivalent latitude (5° bins) on 17 vertical layers (altitude, pressure or potential temperature) between 14 and 46 km. Comparisons with coincident NOy profiles from the Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE-FTS) instrument were used to evaluate several methods to combine Odin observations with model data. This comparison indicates that the most appropriate merging technique uses OSIRIS measurements of NO2, scaled with model NO/NO2 ratios, to estimate NO. The sum of 2×N2O5 and CIONO2 is estimated from uncertainty-based weighted averages of scaled observations of SMR HNO3 and OSIRIS NO2. Comparisons with ACE-FTS suggest the precision (random error) and accuracy (systematic error) of Odin NOy profiles are about 15% and 20%, respectively. Further comparisons between Odin and the Canadian Middle Atmosphere Model (CMAM) show agreement to within 20% and 2 ppb throughout most of the stratosphere except in the polar vortices. A particularly large disagreement within the Antarctic vortex in the upper stratosphere during spring indicates too strong descent of air in CMAM. The combination of good temporal and spatial coverage, a relatively long data record, and good accuracy and precision make this a valuable NOy product for various atmospheric studies and model assessments.