Atmospheric Chemistry and Physics (Sep 2018)

An empirical model of nitric oxide in the upper mesosphere and lower thermosphere based on 12 years of Odin SMR measurements

  • J. Kiviranta,
  • K. Pérot,
  • P. Eriksson,
  • D. Murtagh

DOI
https://doi.org/10.5194/acp-18-13393-2018
Journal volume & issue
Vol. 18
pp. 13393 – 13410

Abstract

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Nitric oxide (NO) is produced by solar photolysis and auroral activity in the upper mesosphere and lower thermosphere region and can, via transport processes, eventually impact the ozone layer in the stratosphere. This work uses measurements of NO taken between 2004 and 2016 by the Odin sub-millimeter radiometer (SMR) to build an empirical model that links the prevailing solar and auroral conditions with the measured number density of NO. The measurement data are averaged daily and sorted into altitude and magnetic latitude bins. For each bin, a multivariate linear fit with five inputs, the planetary K index, solar declination, and the F10.7 cm flux, as well as two newly devised indices that take the planetary K index and the solar declination as inputs in order to take NO created on previous days into account, constitutes the link between environmental conditions and measured NO. This results in a new empirical model, SANOMA, which only requires the three indices to estimate NO between 85 and 115 km and between 80° S and 80° N in magnetic latitude. Furthermore, this work compares the NO calculated with SANOMA and an older model, NOEM, with measurements of the original SMR dataset, as well as measurements from four other instruments: ACE, MIPAS, SCIAMACHY, and SOFIE. The results suggest that SANOMA can capture roughly 31 %–70 % of the variance of the measured datasets near the magnetic poles, and between 16 % and 73 % near the magnetic equator. The corresponding values for NOEM are 12 %–38 % and 7 %–40 %, indicating that SANOMA captures more of the variance of the measured datasets than NOEM. The simulated NO for these regions was on average 20 % larger for SANOMA, and 78 % larger for NOEM, than the measured NO. Two main reasons for SANOMA outperforming NOEM are identified. Firstly, the input data (Odin SMR NO) for SANOMA span over 12 years, while the input data for NOEM from the Student Nitric Oxide Experiment (SNOE) only cover 1998–2000. Additionally, some of the improvement can be accredited to the introduction of the two new indices, since they include information of auroral activity on prior days that can significantly enhance the number density of NO in the MLT during winter in the absence of sunlight. As a next step, SANOMA could be used as input in chemical models, as a priori information for the retrieval of NO from measurements, or as a tool to compare Odin SMR NO with other instruments. SANOMA and accompanying scripts are available on http://odin.rss.chalmers.se (last access: 15 September 2018).