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Mesospheric nitric oxide model from SCIAMACHY data

Bender, Stefan; Sinnhuber, Miriam; Espy, Patrick J.; Burrows, John P.

We present an empirical model for nitric oxide (NO) in the mesosphere (≈60–90 km) derived from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartoghraphY) limb scan data. This work complements and extends the NOEM (Nitric Oxide Empirical Model; Marsh et al., 2004) and SANOMA (SMR Acquired Nitric Oxide Model Atmosphere; Kiviranta et al., 2018) empirical models in the lower thermosphere. The regression ansatz builds on the heritage of studies by Hendrickx et al. (2017) and the superposed epoch analysis by Sinnhuber et al. (2016) which estimate NO production from particle precipitation.

Our model relates the daily (longitudinally) averaged NO number densities from SCIAMACHY (Bender et al., 2017b, a) as a function of geomagnetic latitude to the solar Lyman-α and the geomagnetic AE (auroral electrojet) indices. We use a non-linear regression model, incorporating a finite and seasonally varying lifetime for the geomagnetically induced NO. We estimate the parameters by finding the maximum posterior probability and calculate the parameter uncertainties using Markov chain Monte Carlo sampling. In addition to providing an estimate of the NO content in the mesosphere, the regression coefficients indicate regions where certain processes dominate.

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Verlagsausgabe §
DOI: 10.5445/IR/1000091224
Veröffentlicht am 19.02.2019
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 1680-7324
KITopen-ID: 1000091224
HGF-Programm 12.04.05 (POF III, LK 01)
Trends,Variaility,Large-Scale Processes
Erschienen in Atmospheric chemistry and physics
Band 19
Heft 4
Seiten 2135–2147
Vorab online veröffentlicht am 18.02.2019
Externe Relationen Abstract/Volltext
Nachgewiesen in Web of Science
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