We discuss the retrieval of carbon monoxide (CO)
vertical column densities from clear-sky and cloud contaminated
2311–2338 nm reflectance spectra measured by the Scanning Imaging
Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)
from January 2003 until the end of the mission in April 2012. These
data were processed with the Shortwave Infrared CO Retrieval
algorithm (SICOR) that we developed for the operational data
processing of the Tropospheric Monitoring Instrument (TROPOMI) that
will be launched on ESA's Sentinel-5 Precursor (S5P) mission. This
study complements previous work that was limited to clear-sky
observations over land. Over the oceans, CO is estimated from
cloudy-sky measurements only, which is an important addition to the
SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON
measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna
Loa and Reunion, a validation of SCIAMACHY clear-sky retrievals is
not meaningful because of the high retrieval noise and the few
collocations at these sites. The situation improves significantly
when considering cloudy-sky observations, where we find a low mean
bias
The Tropospheric Monitoring Instrument (TROPOMI) will be launched on board
the Copernicus Sentinel-5 Precursor (S5P) satellite. Besides the ultraviolet,
visible and near infrared spectral range, it will measure the Earth's radiance and
solar irradiance in the 2.3
The SWIR measurements around 2.3
A major limitation of the SCIAMACHY CO data set is its high retrieval noise,
which can exceed 100 % of the retrieved value for individual columns.
Hence, in practice the data need to be averaged spatially and temporally to
reduce the noise contribution
SCIAMACHY's SWIR measurements of clear skies over land have a good sensitivity for the vertical column density of CO. However, the clear-sky CO data product requires a strict cloud filter over land and the rejection of all observations over oceans due to the low reflectivity of the ocean surface in the SWIR. Hence, a retrieval that works for cloudy scenes is very desirable in order to extend spatial coverage beyond the small fraction of SCIAMACHY observations, which are clear skies over land.
In this study, we apply the SICOR algorithm to SCIAMACHY's 2.3
The inversion of CO vertical column densities from SCIAMACHY's
2.3
The inversion is based on the assumption that the measurement
The forward model
Equation (
Hence, when considering
Finally, the measurement noise described by the measurement covariance matrix
For SCIAMACHY CO retrievals, we use the recalibrated SCIAMACHY spectra
including estimates of the measurement noise as described by
The settings for the non-scattering retrieval are identical with the one
described by
The subsequent scattering retrieval is described in detail by
Compared to the previous work by
To gain experience with the SICOR cloud parameters, we compared the
retrieved cloud height
In the following, we use the SICOR cloud parameters to classify the retrievals
with respect to cloudiness. We distinguish between three CO retrieval
conditions: (1) clear-sky observations over land with
Scatter plot of the retrieved cloud height
Column averaging kernel values of one represent the ideal value for a
vertical integration (see Eq.
So under clear-sky conditions we can retrieve CO vertical column densities with
a sensitivity close to 1 at all altitudes (see yellow line in
Fig.
The null-space does not lead to a problem for application like data
assimilation if the averaging kernel is applied properly. Exploiting
the altitude sensitivity given by the averaging kernel, the
atmospheric state of the model can be adjusted adequately by the
assimilation scheme. Also, for the validation of the CO data product,
the null-space error does not impose principal limitation where
Eq. (
Example SCIAMACHY CO column averaging kernels over Australia in 2003 as a function of altitude for the following cases: clear-sky (yellow line), a cloud with 0.7 km centre height (dashed line) and a cloud with 2 km centre height (solid line). Cloud optical thickness of 2.5 for the relevant cases.
CO retrievals under cloudy conditions represent an interesting addition to
our clear-sky data product. Here, the retrieved column is mostly sensitive to
CO above the cloud and for varying cloud height, and due to the shielding
effect of clouds, different altitudes are probed. For the interpretation of
errors, it is important to note that for the scaling of a reference profile,
the interpretation of relative biases is the same for clear-sky and cloudy
retrieval. In both cases, it indicates the relative error to the CO
concentrations at all altitudes the retrieval is sensitive to. Furthermore,
the radiometric precision of SWIR measurements for cloudy scenes is generally
much better than for clear-sky observations because of the brightness of
clouds. In the 2.3
To illustrate this, Fig.
Percentage of cloudy-sky retrievals of all retrievals from January
2003 to the end of the SCIAMACHY mission in April 2012. Here, cloudy-sky
retrievals comprise all data products of categories 2 and 3, defined in
Sect.
Figure
The quality of our CO retrieval for cloudy atmospheres needs to be demonstrated
through validation. First, we validate the SCIAMACHY CO retrievals with airborne
profile measurements of the MOZAIC/IAGOS project, based on in situ measurements
on commercial airliners The The mean signal-to-noise ratio of the measurements in the fit
window must be The noise
These criteria represent a weak data filtering to remove outliers due
to unphysical retrievals. For example, the signal-to-noise threshold
corresponds to clear-sky measurements over the oceans (see Fig
The MOZAIC/IAGOS project provides profile measurements of reactive gases
performed on board long-distance passenger airliners. Since 1994, in situ
profile measurements are recorded during the ascent and descent phases of
more than 40 000 flights. These observations are used to derive vertical
column densities of CO with a precision of about 5 %
MOZAIC/IAGOS airports used for validation. The temporal coverage with the SCIAMACHY mission is given in years.
In this study, we consider the vertical profile measurements at three
cities: Tehran and Beijing, which are known to be affected by strong
local pollution events
To collocate SCIAMACHY retrievals with MOZAIC/IAGOS measurements, we select
all SCIAMACHY CO retrievals with a ground pixel in a radius of 850 km around
the airport site. The temporal collocation criterium is chosen dynamically
for each individual MOZAIC/IAGOS measurement and varies typically between 7
and 30 days. Centred around the recording time of the aircraft measurements,
the temporal collocation window is chosen such that the average of all
spatially collocated SCIAMACHY measurements have a precision
CO column mixing ratios of Tehran and Beijing measured by MOZAIC/IAGOS (yellow), MOZAIC/IAGOS with SCIAMACHY column averaging kernels applied (pink) and SCIAMACHY retrievals for optically thick high cloud conditions (black).
De Laat et al. (
Another interesting feature of our comparison is the better agreement
for Beijing than for Tehran, where at the same time the SCIAMACHY
mean CO column mixing ratio at Tehran is about 43.0 ppb smaller than
for Beijing with about 16.0 ppb less scatter. This may hint at a
larger representation error for Tehran than for Beijing, meaning that
SCIAMACHY, with its coarse spatial sampling, captures the enhanced CO
concentrations over Beijing better than those over Tehran and so it
explains the differences we see in Fig.
We complete our SCIAMACHY CO validation that is based on MOZAIC/IAGOS
aircraft measurements by analysing observations from the airport at
Windhoek. Figure
As Fig.
Mean CO column mixing ratio
Same as Table
The TCCON and NDACC networks perform direct sunlight measurements with ground-based Fourier transform spectrometers under clear-sky conditions. The
Infrared Working Group (IRWG) performs measurements in the mid-infrared
spectral range at 4.8
Because of the lack of profile information, it is not possible to apply
averaging kernels, and NDACC/TCCON data must be compared directly with the
SCIAMACHY cloudy-sky retrievals. The comparison depends critically on the CO
a priori profile information, and so we select near-coast measurement sites
in remote areas, where the TM5 model prediction of the relative CO profile is
most reliable: Ny-Ålesund, Wollongong
30-day median of CO column averaged mixing ratios measured by
SCIAMACHY (black) and at two NDACC-IRWG stations (pink).
Same as Fig.
The upper panel of Fig.
The correlations between the FTS and clear-sky SCIAMACHY measurements over land
are poor (about
Mean bias SCIAMACHY – FTS
CO column averaged mixing ratios in ppb over land and ocean from clear-sky and cloudy-sky measurements for optically thick low cloud conditions. The values are averaged from January 2003 to the end of the SCIAMACHY mission in April 2012.
When analysing SCIAMACHY cloudy-sky CO retrievals with
The presented validation analysis provided sufficient confidence to reprocess
the global full-mission SCIAMACHY CO data set including clear-sky and cloudy-sky
observations. In particular, the validation with NDACC and TCCON measurements
revealed that the CO column, retrieved from measurements with low, optically
thick clouds, can be used as an estimate of the true column (i.e. ignoring
effects of the column averaging kernel) in the absence of local sources of CO.
The full-mission averaged CO product is shown in
Fig.
In this study, we derived a full-mission SCIAMACHY CO column data set that
comprises retrievals from clear-sky and cloudy-sky reflectance measurements in
the spectral range 2311–2338 nm over land and ocean scenes. The inversion uses
the SICOR CO retrieval code that is developed for the operational data
processing of the Sentinel-5 Precursor mission. It allows us to retrieve effective
cloud parameters
simultaneously with trace gas columns. The data product includes the CO column
and its column averaging kernel for each individual sounding, and so it
provides information on the vertical CO retrieval sensitivity, which changes
with the cloudiness of the observed scene. This study focused on the validation
of SCIAMACHY CO retrievals for cloudy-sky observations with MOZAIC/IAGOS
aircraft measurements and TCCON and NDACC ground-based observations. It
represents an significant extension with respect to the previous work by
The effective cloud parameters (cloud height
SICOR uses the profile-scaling approach to infer CO vertical column densities from the measurement, which involves a regularisation of the inversion problem. When interpreting the retrieved column as an estimate of the truth, a null-space error is introduced. This null-space error depends on the accuracy of the profile shape to be scaled by the inversion. Generally for clear-sky observations the null-space error is small, but for cloudy conditions it can easily exceed 30 %. Here, clouds shield the atmosphere below and the a priori CO profile shape is used to add the lacking information. The sensitivity of the retrieved CO column with respect to the true CO density is provided by the column averaging kernel for each individual retrieval. For the validation, we can thus interpret the retrieved column as a vertically integrated CO column density weighted by the column averaging kernel, and so the null-space error becomes less relevant for the comparison of the retrieval product with independent atmospheric measurements of the CO profile.
Validating SCIAMACHY retrievals with MOZAIC/IAGOS airborne measurements
confirmed the approach.
Direct comparison of the MOZAIC/IAGOS CO columns
estimated at Beijing, Tehran and Windhoek with collocated SCIAMACHY cloudy-sky
retrievals of the CO column show a small bias of 0.5–9.5 ppb. However,
for clear-sky SCIAMACHY observations, the
bias exceeds 120.0 ppb for Tehran and 30.0 ppb for Beijing which is
in agreement with previous studies
We completed our validation study using ground-based FTS measurements from the
NDACC and TCCON networks for the coastal sites Ny-Ålesund, Lauder, Mauna
Loa, Reunion and Wollongong. At these validation sites, an independent measurement
of the CO profile is not available, and so we assumed the shape of the CO
profile. Hence, we directly compare the column densities
from FTS with those of SCIAMACHY measurements for both clear-sky conditions and cloudy conditions with low
clouds. Considering only clear-sky SCIAMACHY observations over land at Lauder,
Mauna Loa and Reunion, the comparison was dominated by the SCIAMACHY retrieval
noise because of the low surface albedo and the insufficient number of
collocations. Filtering the SCIAMACHY data set to select for optically thick low clouds
over land and oceans, we found good agreement with the FTS ground-based
measurements with a correlation coefficient of
Finally we processed the full-mission data record of SCIAMACHY SWIR measurements. This data set clearly demonstrates the asset of cloudy-sky CO retrievals over oceans, providing a global coverage of the SCIAMACHY CO data product. The correct interpretation of these data requires the use of the column averaging kernel. In future, the data may be used to discriminate the vertical distribution of CO in the atmosphere, e.g. by means of data assimilation. For this, retrievals under optically thick clouds with varying cloud heights are essential because the shielding of the atmosphere below the cloud reveals information about CO in different altitudes.
It is the first time that the operational TROPOMI CO algorithm is tested successfully on real data for clear-sky and cloudy atmospheres, which is an important milestone for the preparation of the S5P mission. Although TROPOMI SWIR measurements will have the same spectral coverage and resolution as SCIAMACHY, we expect a much better data product due to its better radiometric performance and its better spatial resolution and sampling. After the launch of SP5, this techniques used in this study will allow us to use IAGOS/MOZAIC and FTS measurements from the TCCON and NDACC networks for the validation of TROPOMI CO. Additionally, using the same retrieval approach for SCIAMACHY and TROPOMI CO retrievals will help to provide a consistent long-term CO data set for both missions.
The full-mission SCIAMACHY CO data set of this study including clear-sky and
cloudy-sky observations is available for download at
The authors declare that they have no conflict of interest.
SCIAMACHY is a joint project of the German Space Agency DLR and the Dutch Space Agency NSO with contributions from the Belgian Space Agency. The work performed is (partly) financed by NSO through the SCIAvisie project and in collaboration with the SCIAMACHY Quality Working Group (SQWG) by ESA. We acknowledge the European Commission for the support to the MOZAIC project (1994–2003) and the preparatory phase of IAGOS (2005–2012), the partner institutions of the IAGOS Research Infrastructure (FZJ, DLR, MPI, KIT in Germany, CNRS, CNES, Météo-France in France and the University of Manchester in UK), ETHER (CNES-CNRS/INSU) for hosting the database, the participating airlines (Lufthansa, Air France, Austrian, China Airlines, Iberia, Cathay Pacific) for transporting the MOZAIC/IAGOS instrumentation free of charge. We acknowledge the NDACC-IRWG and TCCON ground-based FTS networks for providing data. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative. Edited by: L. Lamsal Reviewed by: R. Lang and one anonymous referee