NASA logo

Aura Science

How atmospheric chemistry and transport drive surface variability of nitrous oxide and trichlorofluoromethane

Nitrous oxide (N2O) is a greenhouse gas exhibiting long-term increases in its surface and atmospheric abundance, as a result of emissions from agricultural and industrial sources. How can we better understand its global distribution and what affects its variations in both the stratosphere and the troposphere (near the surface)?

A combination of observational and model analyses is used to provide more insights into the natural variability components of stratospheric and surface N2O. The stratospheric loss of N2O (see Figure) can be constrained through the use of Aura Microwave Limb Sounder (MLS) observations of N2O, ozone and temperature. The stratosphere, in turn, has some influence on tropospheric distributions and variability.

  • Several chemical transport models (CTMs) are used to examine the troposphere and stratosphere to estimate the variability components (e.g., annual, quasi-biennial) in surface N2O and in CFC-11 (trichlorofluoromethane), another gas of interest (as an ozone-depleting substance).
  • The 3 models, run with no emission impacts, simulate most of the observed northern hemisphere (NH) seasonal and multi-year fluctuations in satellite and surface observations. The N2O imprint from the stratospheric loss signal (and not the N2O emissions) dominates NH surface variability.

However, model results disagree in the southern hemisphere annual cycle.

Estimates of stratospheric loss of N2O as a function of time based on Aura MLS data and  from model results

Estimates of stratospheric loss of N2O as a function of time based on Aura MLS data since 2004 (thick black curve), and from model results since as early as 1990 (colored curves from three different chemical transport models). The two y-axes show losses in different units.

Separation of the surface signatures of natural variability from those of human emissions enables better quantification of how to reduce emission impacts.

Technical Description of Figure:

Absolute loss of N2O (TgN/yr; left axis) and global mean loss frequency (%/yr, right axis) based on Aura MLS observations (2005-2018, black), and obtained from model results (GMI CTM, 1990-2018, green; LMDz5 CTM, 1995-2016, blue; UCI CTM, 1990-2017, red).

Scientific significance, societal relevance, and relationships to future missions:

Gases such as N2O and CFC-11 can have a non-negligible impact on the ozone layer and global surface warming, and hence, on society and health. Studies seeking to derive surface emissions must be able to model and remove the stratospheric variability from surface fluctuations; this work provides better constraints on losses and variability for these species at the surface. Future missions would need to have similar quality stratospheric data as Aura MLS (and with good enough sampling) in order to pursue improvements to such detailed analyses of integrated N2O loss as a function of latitude and time, or regarding other long-lived tracers with stratospheric loss terms that can be estimated well enough. No such mission is currently being planned by NASA.

Data Sources:

Aura MLS profiles on pressure surfaces were provided as Level 3 monthly zonal means by the Aura MLS team; both MLS Level 2 and Level 3 data files can be obtained from, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Ground-based datasets from NOAA (not shown here) are also used in these analyses and comparisons. The models used for the comparisons are Chemical Transport Models (CTMs), namely the Goddard Space Flight Center (GSFC) Global Modeling Initiative (GMI) CTM, the Laboratoire de Météorologie Dynamique, Zoom, Version 5 (LMDz5) CTM, and the University of California Irvine (UCI) CTM, each driven by different meteorological fields.

References: Ruiz, D., M. J. Prather, S. E. Strahan, R. L. Thompson, L. Froidevaux, and S. D. Steenrod, How Atmospheric Chemistry and Transport Drive Surface Variability of N2O and CFC-11, J. Geophys. Res., 2021, doi: 10.1029/2020JD033979.