Sentinel-5 (S5) and its precursor (S5P) are future European
satellite missions aiming at global monitoring of methane
(

The greenhouse gas methane (

Estimating such surface–atmosphere fluxes through inverse modeling,
however, poses stringent accuracy requirements on the retrieved
X

Here, we aim at mapping spectroscopic errors into X

This paper is organized as follows. Section

Characteristics of simulated measurements and retrieval simulations.
We investigate three retrieval configurations (SW1, SW3, and SW1+3) that take
into account the possible combinations of band SWIR1 and SWIR3. For each
channel, the signal to noise ratio (SNR) is modeled according to SNR

Remote sensing of atmospheric parameters in general requires a forward
model

The simulated measurements

The forward model

The spectra modeled by RemoTeC are convolved by the satellite's ISRF,
and noise is added as described above to simulate S5- and S5P-like
measurements. Section

The ensemble of scenes for which we perform retrieval simulations is
the same as the one described in detail by Butz
et al. (2010, 2012). While our former studies focus on errors
induced by aerosol and cirrus scattering, we neglect such effects here; therefore we assume all scenes to be free of scattering particles. The ensemble
covers 1 day in each of the following months: January, April, July, and October, respectively, for which we collect
atmospheric absorption and surface reflection properties on
an

Given the simulated measurements

Once the state vector solution

The first step in generating the spectroscopic forward model error for
the satellite retrieval simulations is selecting a set of spectra
recorded by the ground-based, direct-sun viewing FTS located at the Darwin
(Australia) TCCON station and operated by University of Wollongong.
The instrument, Bruker 125HR, provides spectral coverage in all
absorption bands relevant here (see Table

FTS transmittance spectrum in SWIR1 (upper panel), residual
transmittance at FTS spectral resolution (first middle panel) and residual
transmittance at S5/S5P spectral resolution (second lower panel). The last two panels show the average offour
illustrative humid spectra (reddish lines) and four illustrative dry spectra
(bluish lines) at FTS and S5/S5P spectral resolutions. The water vapor
absorption lines (with line intensity

FTS transmittance spectrum in SWIR3 (upper panel), residual
transmittance at FTS spectral resolution (first middle panel) and residual
transmittance at S5/S5P spectral resolution (second lower panel). The last two panels show the average of four
illustrative humid spectra (reddish lines) and four illustrative dry spectra
(bluish lines) at FTS and S5/S5P spectral resolutions. The water vapor
absorption lines (with line intensity

The methodology we introduce here assumes that the perturbation

For a ground-based, direct-sun viewing observer in a plane-parallel
atmosphere, the monochromatic atmospheric transmittance

Up to here we assume monochromatic light, but in order to introduce
the perturbed satellite measurement in the retrieval algorithm we have
to take in account the satellite spectral resolution. Therefore, if
the satellite retrieval is not aware of this perturbation, the
spectroscopic forward model error

Seasonal X

Air mass factor (AMF) for the four months considered. Latitudes with
solar zenith angles larger than 70

Figures

Additionally, three processing steps are carried out. First we
determine a small spectral shift between the ground-based and the
satellite spectra by comparing the FTS transmittance

X

X

X

Bi-dimensional histograms of methane retrieval
error (%) with respect to XH

This section discusses the spectroscopic X

The SW1 configuration (Fig.

To illustrate the dependence of the X

These results are consistent with the current status of

The goals of Sentinel 5 and the Sentinel 5 Precursor concerning
X

The key assumption of our approach is that a realistic spectroscopic
perturbation can be derived from spectral fitting residuals of
a ground-based, direct-sun viewing FTS. This assumption can be
criticized in two ways: (1) the FTS fitting residual contains only
that part of the spectroscopic errors that cannot be accounted for
through the free parameters of the FTS fit, i.e., only the part of the
spectroscopic errors that are in the null-space

Translating the ground-based FTS fitting residuals into our satellite
sounding ensemble, we consider dependencies on the air mass factor and
atmospheric water vapor content but neglect dependencies on other
variables such meteorological variables or the

However, our study only examines the standard configurations currently
foreseen for

Our retrieval simulations indicate that the spectroscopy-induced X

This research was funded by the European Space Agency (ESA) through
the