Comparison of nitric oxide measurements in the mesosphere and lower thermosphere from ACE-FTS, MIPAS, SCIAMACHY, and SMR
- 1Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
- 2Instituto de Astrofísica de Andalucía, CSIC, Granada, Spain
- 3Department of Earth and Space Sciences, Chalmers University of Technology, Gothenburg, Sweden
- 4Department of Physics, University of Toronto, Toronto, Canada
- 5Institute of Environmental Physics, University of Bremen, Bremen, Germany
- †deceased, 14 August 2015
Abstract. We compare the nitric oxide measurements in the mesosphere and lower thermosphere (60 to 150 km) from four instruments: the Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE-FTS), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), and the Sub-Millimetre Radiometer (SMR). We use the daily zonal mean data in that altitude range for the years 2004–2010 (ACE-FTS), 2005–2012 (MIPAS), 2008–2012 (SCIAMACHY), and 2003–2012 (SMR).
We first compare the data qualitatively with respect to the morphology, focussing on the major features, and then compare the time series directly and quantitatively. In three geographical regions, we compare the vertical density profiles on coincident measurement days. Since none of the instruments delivers continuous daily measurements in this altitude region, we carried out a multi-linear regression analysis. This regression analysis considers annual and semi-annual variability in the form of harmonic terms and inter-annual variability by responding linearly to the solar Lyman-α radiation index and the geomagnetic Kp index. This analysis helps to find similarities and differences in the individual data sets with respect to the inter-annual variations caused by geomagnetic and solar variability.
We find that the data sets are consistent and that they only disagree on minor aspects. SMR and ACE-FTS deliver the longest time series in the mesosphere, and they agree with each other remarkably well. The shorter time series from MIPAS and SCIAMACHY also agree with them where they overlap. The data agree within 30 % when the number densities are large, but they can differ by 50 to 100 % in some cases.