The figure shows the correlation of monthly means of N2O and O3 in the
tropics for six different months of the year 2009 at two potential
temperature levels (500 and 650 K). The observational data are from the
satellite instruments Odin/SMR (grey), Aura/MLS (red), ENVISAT/MIPAS
(blue); the green symbols are from the chemistry-climate model WACCM.
Although the instruments reveal biases of ozone and N2O with respect to
each other, they reproduce the slope of the O3-N2O correlation rather
unambiguously, and almost constantly over the year. In contrast, the slope
of the O3-N2O correlation from WACCM deviates from the observational
data (esp. at the 500K level) and varies with time.
The correlations of O3 and N2O from the satellite instruments
ENVISAT/MIPAS, Odin/SMR, ACE-FTS, Aura/MLS, CRISTA-1, and CRISTA-2 at
two potential temperature levels in the tropics have been analyzed and
compared to O3-N2O correlations from the CCM WACCM, the atmospheric
general circulation model ECHAM5/Messy1, and the Karlsruhe Simulation
Model of the Middle Atmosphere (KASIMA). The tracer-tracer correlations
from observational data demonstrate that the slope of the O3-N2O
correlation curve is rather invariant with respect to seasonal and
inter-annual variability of the tracers themselves (e.g., due to QBO impact), and instrumental
biases. In contrast, deviations of the slopes of the tracer-tracer
correlations from the model outputs hint towards model deficiencies. In
particular, the differences between model simulations and observations
are most likely caused by an underestimation of the quasi-biennial
oscillation and tropical upwelling by the models. A realistic
consideration of the QBO in the model reduces the differences between
model simulation and observations significantly. The intercomparison between Odin/SMR,
Aura/MLS, ENVISAT/MIPAS and WACCM shows that these data sets are generally in
good agreement, although some known biases of the observational data
sets are clearly visible in the monthly averages. Nevertheless, the
differences caused by the uncertainties of the satellite data sets are
sufficiently small and can be clearly distinguished from model
deficiencies. Thus, the method applied in this study is not only a
valuable tool for model evaluation, but also for satellite data
intercomparisons. For more information, see
http://www.atmos-chem-phys.net/13/3619/2013/acp-13-3619-2013.pdf
