| In the past, differential optical absorption spectroscopy (DOAS) has
mostly been employed for atmospheric trace gas retrieval in the
UV/Vis spectral region. New spectrometers such as SCIAMACHY onboard
ENVISAT
also provide near infrared channels and thus allow for the detection of
greenhouse gases like CH4, CO2, or N2O.
However, modifications of the classical DOAS algorithm are necessary to account for the
idiosyncrasies of this spectral region, i.e. the temperature and
pressure dependence of the high resolution absorption lines.
Furthermore, understanding the sensitivity of the measurement of
these high resolution, strong absorption lines by means of a
non-ideal device, i.e. having finite spectral resolution, is of
special importance. This applies not only in the NIR, but can also
prove to be an issue for the UV/Vis spectral region.
This paper presents a modified iterative maximum a posteriori-DOAS
(IMAP-DOAS) algorithm based on optimal estimation theory
introduced to the remote sensing community by rodgers76.
This method directly iterates the vertical column densities of the
absorbers of interest until the modeled total optical density fits
the measurement. Although the discussion in this paper lays emphasis
on satellite retrieval, the basic principles of the algorithm also
hold for arbitrary measurement geometries.
This new approach is applied to modeled spectra based on a
comprehensive set of atmospheric temperature and pressure profiles.
This analysis reveals that the sensitivity of measurement strongly
depends on the prevailing pressure-height. The IMAP-DOAS algorithm
properly accounts for the sensitivity of measurement on pressure due
to pressure broadening of the absorption lines. Thus, biases in the
retrieved vertical columns that would arise in classical algorithms,
are obviated. Here, we analyse and quantify these systematic biases
as well as errors due to variations in the temperature and pressure
profiles, which is indispensable for the understanding of
measurement precision and accuracy in the near infrared as well as
for future intercomparisons of retrieval algorithms. |