TROPOMI on board the Copernicus Sentinel-5 Precursor platform can measure various atmospheric compositions at high spatial resolution and improved spectral resolution compared to its predecessors. Bromine monoxide (BrO) is one of the gases that can be derived from the measured radiances of TROPOMI using the differential optical absorption spectroscopy method. In this paper, we present the first retrieval results of BrO column amounts from TROPOMI observations on global and regional scales.
TROPOMI on board the Copernicus Sentinel-5 Precursor platform can measure various atmospheric...
First high-resolution BrO column retrievals from TROPOMI
First high-resolution BrO column retrievals from TROPOMI
First high-resolution BrO column retrievals from TROPOMIFirst high-resolution BrO column retrievals from TROPOMISora Seo et al.
Sora Seo,Andreas Richter,Anne-Marlene Blechschmidt,Ilias Bougoudis,and John Philip BurrowsSora Seo et al.Sora Seo,Andreas Richter,Anne-Marlene Blechschmidt,Ilias Bougoudis,and John Philip Burrows
Correspondence: Sora Seo (sora.seo@iup.physik.uni-bremen.de)
Received: 17 Oct 2018 – Discussion started: 18 Dec 2018 – Revised: 05 Apr 2019 – Accepted: 08 May 2019 – Published: 28 May 2019
Abstract
For more than 2 decades, satellite observations from
instruments such as GOME, SCIAMACHY, GOME-2, and OMI have been used for the
monitoring of bromine monoxide (BrO) distributions on global and regional
scales. In October 2017, the TROPOspheric Monitoring Instrument (TROPOMI)
was launched on board the Copernicus Sentinel-5 Precursor platform with the
goal of continuous daily global trace gas observations with unprecedented
spatial resolution. In this study, sensitivity tests were performed to find
an optimal wavelength range for TROPOMI BrO retrievals under various
measurement conditions. From these sensitivity tests, a wavelength range for
TROPOMI BrO retrievals was determined and global data for April 2018 as well
as for several case studies were retrieved. Comparison with GOME-2 and OMI
BrO retrievals shows good consistency and low scatter of the columns. The
examples of individual TROPOMI overpasses show that due to the better signal-to-noise ratio and finer spatial resolution of 3.5×7km2, TROPOMI BrO
retrievals provide good data quality with low fitting errors and unique
information on small-scale variabilities in various BrO source regions such
as Arctic sea ice, salt marshes, and volcanoes.
Bromine monoxide (BrO) plays an important role in atmospheric chemistry. In
the lower stratosphere, it is involved in chain reactions that deplete ozone
(Wennberg et al., 1994), and bromine in the troposphere changes the oxidizing
capacity through the destruction of ozone, which is a primary precursor of
atmospheric oxidation in the troposphere (von Glasow et al., 2004). In
particular, large amounts of BrO are often observed in the polar boundary
layer during springtime, known as “bromine explosion”, and lead to
severe tropospheric ozone depletion by autocatalytic reactions (McConnell et
al., 1992; Simpson et al., 2007). In addition to polar sea ice regions,
enhanced BrO concentrations were also detected over salt lakes/marshes
(Hebestreit et al., 1999; Tas, 2005; Hörmann et al., 2016), in the
marine boundary layer (Leser et al., 2003; Sander et al., 2003; Saiz-Lopez
et al., 2004), and in volcanic plumes (Bobrowski et al., 2003; Theys et al.,
2009; Schönhardt et al., 2017).
To understand the formation of BrO and the various chemical reactions
involving halogen oxides in the troposphere, BrO observations have been
carried out by in situ chemical ionization mass spectrometry (CIMS) (Liao et
al., 2011; Choi et al., 2012), ground-based differential optical absorption
spectroscopy (DOAS) measurements such as long-path DOAS (LP-DOAS)
(Hönninger et al., 2004; Liao et al., 2011; Stutz et al., 2011), and
multi-axis DOAS (MAX-DOAS) (Hönninger et al., 2004; Frieß et al.,
2011; Zhao et al., 2016). Using ground-based measurements, the diurnal
variation in and vertical distribution of BrO can be investigated with high
temporal resolution in specific source regions (Hönninger et al., 2004;
Hendrick et al., 2007). However, ground-based measurements with localized
spatial coverage are limited in observing large-scale BrO explosion events
and long-range transport of BrO plumes. This can be overcome by satellite
measurements having extensive spatial coverage albeit at coarse spatial
resolution and limited temporal sampling.
Since the launch in 1995 of the Global Ozone Monitoring Experiment (GOME) on
ERS-2, a series of UV–visible spectrometers on board satellites including
SCIAMACHY, GOME-2, and OMI have been used to monitor the global
distribution of BrO columns and large-scale BrO events over time. The first
global observations of BrO were retrieved from the measurements of GOME and
large-scale tropospheric BrO plumes in the polar sea ice region were
detected (Wagner and Platt, 1998; Richter et al., 1998; Chance, 1998).
SCIAMACHY, which followed GOME, not only measured BrO columns but also
vertical profiles of BrO in the stratosphere from limb measurements (Rozanov
et al., 2005; Kuhl et al., 2008). The higher-spatial-resolution data of
GOME-2 and OMI have been successfully used to monitor daily global
distribution as well as BrO emissions from various source regions such as
volcanoes (Theys et al., 2009; Hörmann et al., 2013; Schönhardt et
al., 2017), salt lakes (Hörmann et al., 2016), and polar sea ice regions
(Begoin et al., 2010; Salawitch et al., 2010; Theys et al., 2011; Sihler et
al., 2012; Blechschmidt et al., 2016; Suleiman et al., 2019). However, OMI's
coverage has been reduced since 2008 due to the so-called “row anomaly”,
which is the result of a physical obstruction of the instrument, and
currently the anomaly effect extends over about 50 % of the sensor's
viewing positions (Torres et al., 2018). This reduced viewing ability
affects the observation of emission events as well as the accuracy of the
long-term time series. Existing satellite BrO time series can potentially be
extended with data from the TROPOspheric Monitoring Instrument (TROPOMI)
on board the Copernicus Sentinel-5 Precursor platform, which was launched in
October 2017 for a mission of 7 years (Veefkind et al., 2012).
In this study, we present retrievals of BrO column amounts from TROPOMI
observations on global and regional scales. This retrieval uses an optimized
and adapted DOAS retrieval algorithm developed for earlier satellite
missions. The aim of this study is a first demonstration of the feasibility
of these new BrO retrievals on TROPOMI data, investigation of their
precision, and the comparison to data from other satellites. Therefore, the
focus is on slant columns and simple vertical columns, determined using a
geometric approximation for the air mass factor. Stratospheric correction
schemes and more sophisticated air mass factor calculations accounting for
factors such as presence of clouds, varying surface albedo, and surface
altitude are not used in this study. In order to determine the best
retrieval window, sensitivity tests were performed for various measurement
scenarios by a systematic investigation of retrieval results in different
retrieval wavelength intervals in Sect. 3. TROPOMI BrO columns were
assessed by comparison with those from the two existing satellite
instruments, GOME-2B and OMI, with the consistency of the set of
measurements being investigated. In addition, some examples of interesting
cases in the TROPOMI BrO data are identified and described for different
source regions, such as the Arctic sea ice, salt lakes, and volcanoes.
2 S-5P TROPOMI instrument
TROPOMI is a push-broom imaging spectrometer which was launched on board
the European Space Agency (ESA) Sentinel-5 Precursor (S-5P) satellite in
October 2017 (Veefkind et al., 2012). The instrument has a large swath of
2600 km providing daily global coverage with high spatial resolution of
currently 3.5×7km2 at nadir. TROPOMI has spectral bands in the
ultraviolet (UV), visible (VIS), near-infrared (NIR), and shortwave infrared
(SWIR) ranges, which allows it to monitor key atmospheric constituents such as
O3, NO2, SO2, CO, CH4, HCHO, aerosols, clouds, and
various other trace gases. Compared to previous satellites, TROPOMI has
prominent advantages in extended spectral band range and higher spatial
resolution. From the eight spectral bands of TROPOMI, band 3 data covering a
spectral range of 320–405 nm with the spectral resolution of 0.5 nm and
sampling of 0.20 nm per pixel (McMullan and van der Meulen, 2013) have been used
for this BrO retrieval.
3 BrO retrieval
The retrieval algorithm for BrO uses the differential optical absorption
spectroscopy (DOAS) technique (Platt and Stutz, 2008) as applied for space
application (Burrows et al., 2011). The concept of DOAS is to separate the
wavelength-dependent extinction signal into two components, the low-frequency and the high-frequency part. The absorption by atmospheric gases
is identified from their higher-frequency structures of absorption
cross sections in spectral space and the low-frequency parts are treated as
a closure term fitted by a low-order polynomial. The absorber concentration
integrated along the light path, the slant column density (SCD), is
determined assuming the Beer–Lambert law is applicable.
BrO SCD retrievals are typically performed within the wavelength range from
320 to 364 nm which covers nine absorption peaks of BrO. In this spectral
region, interferences with O3 (Serdyuchenko et al., 2014), NO2
(Vandaele et al., 1998), HCHO (Meller and Moortgat, 2000), SO2 (Bogumil
et al., 2003), OClO (Kromminga et al., 2003), and O4 (Thalman and
Volkamer, 2013) can be found. Thus, not only the absorption cross section of
BrO (Wilmouth et al., 1999; Fleischmann et al., 2004) but also those of
these related molecules are included in the BrO retrieval. In addition to
the absorption cross sections of interfering species, a synthetic Ring
spectrum calculated using the SCIATRAN model (Vountas et al., 1998) is
included to account for the effect of rotational Raman scattering and a
linear intensity offset used as an additional closure term. All absorption
cross sections are convoluted with TROPOMI's row and wavelength-dependent
slit function.
3.1 Sensitivity test of retrieval fitting intervals
For the retrieval of a weak absorber such as BrO, the selection of the
optimal fitting wavelength window is one of the most important things in the
DOAS retrieval process (Vogel et al., 2013; Alvarado et al., 2014). The
optimal fitting window is a retrieval wavelength range that maximizes the
differential absorption structures for the trace gas of interest while
minimizing interferences of other gases. In general, larger fitting windows
can improve the quality of DOAS retrievals by using more spectral points,
but at the same time, they can increase the noise and bias resulting from
interfering signals with other absorbers and wavelength-dependent light path
lengths. Smaller fitting windows allow the fit to better compensate for errors
caused by interferences of other absorption gases, but can also lead to
increased cross correlation between reference absorption cross sections and
higher noise. Thus, finding a compromise for a fitting window that avoids
the disadvantages as well as making the best use of the advantages from the
retrieval wavelength interval is important to yield the best quality DOAS
retrieval result.
In this study, a sensitivity test of the wavelength interval on DOAS BrO
retrievals was performed by evaluating the BrO SCDs and fitting rms values
in many different wavelength ranges. In addition, the scatter of the slant
columns was also investigated over a clean background region. Vogel et al. (2013)
conducted a detailed study of the influence of the wavelength
interval on the quality of DOAS retrievals based on a novel method and
visualization of the results as contour plots. They applied this technique
to a theoretical study of BrO retrievals for stratospheric BrO and BrO in
volcanic plumes by using synthetic spectra, modeling zenith-sky DOAS
measurements of stratospheric BrO and tropospheric measurements of volcanic
plumes. In this way, effects of different wavelength intervals on DOAS
retrievals and appropriate spectral ranges for different study cases could
be easily identified from visualized maps. A similar systematic approach was
taken in this study. However, one important objective of this study is the
investigation of the TROPOMI BrO retrieval results for various measurement
cases and the identification of the overall best fitting window for TROPOMI
BrO measurements. Therefore, sensitivity tests were performed for different
BrO emission scenarios using real satellite data to identify a spectral
region with the best BrO results and the fewest interference problems. The
different measurement scenarios selected are enhanced BrO plumes in the
Arctic sea ice region, BrO plumes over a salt marsh, BrO enhancements in
volcanic plumes, and clear and cloudy scenes over the Pacific background
region. The selected scenarios have very different BrO amounts, slant
columns of interfering species, solar zenith angle, temperatures, and
geographical conditions. The influence of variations in the parameters for
these different cases is included, thereby enabling an optimal fitting
window to be identified for application in a global BrO retrieval. The
selected regions and dates for the different scenarios are summarized in
Table 1. The sensitivity tests were performed over a wide range of retrieval
wavelength intervals, which have start limits of 320–338 nm and end limits
of 342–364 nm with an interval step of 0.2 nm (Fig. 1). This retrieval
wavelength interval can contain up to nine absorption peaks, always including
at least the strongest absorption peak of BrO at 338–342 nm.
Apart from the retrieval wavelength range, other DOAS fit parameters were
kept constant to isolate the effect of the retrieval wavelength range on the
resulting BrO SCDs. The reference absorption cross sections used in this
sensitivity test include not only BrO but also the interfering species as
discussed in Sect. 3. Also, a row-dependent daily earthshine radiance
spectrum taken as the average of measurements over the Pacific region was
used as a reference background spectrum to minimize across-track
variability. In this sensitivity test, a polynomial of the order of 4 was used and
kept constant, which is problematic for small fitting windows for which a
lower-order polynomial might have been more appropriate, but changing the
polynomial degree within the sensitivity test would have introduced another
level of uncertainty. The DOAS retrieval technique is based on linear least-squares fitting of spectra by minimizing the fitting residuals
(chi-square
values).
Table 1Geographical and time information for the different scenarios of
the sensitivity tests in Sect. 3.1.
Figure 1Reference absorption cross sections used in the
sensitivity test of DOAS BrO retrieval. The spectra have been scaled to the
order of 1 for presentation purposes. Black lines are the original cross
sections and red lines are absorption cross sections convolved with the
TROPOMI slit function (TROPOMI ISRF calibration key data v1.0.0). Pink
vertical dashed lines indicate start wavelength ranges and blue lines end
wavelength ranges of fitting windows for this sensitivity test.
3.1.1 BrO retrievals over the polar sea ice region
Satellite observations have shown large-scale BrO plumes (1000s of km)
occurring over polar sea ice regions in spring, which indicates that this
area is one of the most important BrO source regions (Simpson et al., 2007;
Begoin et al., 2010). Thus, one of the retrieval wavelength interval
sensitivity tests was performed for one BrO explosion event in the Arctic.
The results are shown in Fig. 2, where each pixel corresponds to the mean of
the retrieval results from a particular fitting wavelength interval taken
over the first region in Table 1 and is displayed on a color-coded scale.
As can be seen in Fig. 2, negative BrO SCDs with relatively high fitting rms
values are found in general for BrO fitting windows with start wavelengths
below 327 nm and end wavelengths below roughly 352 nm. These unphysical
negative SCDs and high fitting rms values may be attributed to interferences
of other absorbers, which have strong absorption structures at shorter
wavelengths, in particular O3, which has a maximum at high latitudes in
the spring season (Monks, 2000; Aliwell et al., 2002). This can potentially
be improved by introducing additional ozone cross sections, which attempt to
account for effects arising from changes in the light path with wavelength
(Puķīte et al., 2010) (see Appendix A).
Also, the map of mean BrO SCDs shows a strong gradient near start
wavelengths of 333.4 nm. As shown in Fig. 1, strong absorption features of
O3 are located at a shorter wavelength range than 333.4 nm, which
indicates that the sudden increase in BrO SCDs at the corresponding
wavelength is likely due to the interference of gases other than O3. In
order to find the gas that interferes the most with the BrO retrieval, we
investigated the retrieved SCDs maps of other reference gases used in this
DOAS retrieval test and found that HCHO has a sharp change in SCDs in the
vicinity of 333.4 nm similar to BrO with anticorrelations of both gases
(Fig. 3). This implies that HCHO has a significant interference in the DOAS
BrO retrieval at the wavelength range with a start limit of ∼333.4nm. Thus, to further examine the potential HCHO interference on the
BrO retrieval, we performed additional sensitivity tests in the same way as
before but excluding the HCHO absorption cross section for the Arctic BrO
measurement scenario where very low HCHO columns are expected. The mean
relative difference between BrO SCDs retrieved including the HCHO cross
section (S1) and those retrieved without including HCHO (S2) is defined as
(see Fig. 3).
Exclusion of the HCHO absorption cross section leads to reduction of the
retrieved BrO SCDs at start limits above ∼333nm and in the
range of start limits <325nm and end limits <351nm, while an
increase in BrO SCDs is observed mostly at the wavelength range with a start
limit below ∼333nm. The pattern of variations in the
retrieved BrO SCDs changes at the wavelength range between start limits of
333 and 333.4 nm where a strong absorption peak is present in BrO, while it
is absent in HCHO. Possible artifacts in the DOAS BrO retrieval caused by a
spectral cross correlation between BrO and HCHO were also identified in
Theys et al. (2011) and Vogel et al. (2013). From this sensitivity test for
the polar BrO measurement scenario, we can confirm that the main issues
impacting the accuracy of the DOAS BrO retrievals are the influence of the
strong O3 absorptions at a shorter wavelength range <327nm and
potential interferences between BrO and HCHO absorptions. In consequence, we
should choose a wavelength range that avoids strong O3 absorption
features as well as minimizing the interference between BrO and HCHO to
obtain the most accurate BrO retrieval results.
Figure 2Color-coded means of (a) BrO SCDs and (b) fitting rms values
retrieved over the selected Arctic sea ice region for a BrO
explosion event using TROPOMI measurements at different wavelength
intervals.
Figure 3Color-coded means of (a) HCHO SCDs and (b) relative
difference between BrO SCDs retrieved including the HCHO absorption cross
section and those without HCHO for the Arctic BrO measurement
scenario.
In addition to polar sea ice regions, salt lakes and marshes are important
BrO source regions. The selected study region (see Table 1), Rann of Kutch,
is known as one of the strongest natural sources of reactive bromine
compounds and has been monitored by satellite measurements for long-term
variations in BrO columns (Hörmann et al., 2016). In order to determine
the appropriate DOAS fitting wavelength range for BrO retrievals over salt
marshes, the sensitivity test was performed in the same way as for the polar
event. As shown in Fig. 4, BrO retrieval results in the salt marsh show
relatively high fitting rms values at shorter wavelengths below 322 nm, but
unlike for BrO retrievals in the Arctic sea ice region (Fig. 2), no negative
values are found for BrO SCDs. This is because the interference of O3
is smaller in this midlatitude region scenario than in the polar region
where the influence of O3 absorption is large. In general, high BrO
SCDs with low fitting errors are shown in the evaluation wavelength range at
start limits of 333–338 nm and end limits of 354–364 nm. This behavior is
similar to the appropriate retrieval wavelength range in the previous polar
BrO sensitivity test results.
Figure 4As Fig. 2 but for the Rann of Kutch salt marsh.
Volcanic eruptions emit various gases into the atmosphere and BrO is often
also detected in volcanic plumes (Bobrowski et al., 2003). The selected
volcanic BrO retrieval scenario is a small-scale BrO plume emitted by
volcanic activity at Ambae. In the sensitivity test for volcanic BrO, an
SO2 absorption cross section was added to the general DOAS BrO
retrieval settings due to high SO2 concentrations expected in the
volcanic plume. If we use a retrieval wavelength interval with start
wavelengths below 323 nm included or narrow fitting windows less than
8 nm
wide, negative BrO SCDs and high fitting rms values are found, as can be seen
in Fig. 5. These features may be attributed to the SO2 interference at
shorter wavelengths and the increase in cross correlation between BrO and
other absorption gases, in particular SO2 (Fig. 6). Relatively
higher fitting rms values are also found in the retrieval wavelength
intervals extending to longer wavelengths (>358nm). This is
attributed to the impact of the Ring effect, i.e., the in-filling of
Fraunhofer lines resulting from high aerosol loads and or the formation of
clouds after the volcanic eruption (Theys et al., 2009) (see Fig. 6).
Figure 5As Fig. 2, but for the selected volcanic plume case.
Figure 6(a) TROPOMI UV aerosol index (340/380 nm) from the operational
Level 2 product and (b) OMI SO2 vertical columns (DU) from the column
amount SO2 TRM (mid-troposphere) of the operational OMSO2 product for a
volcanic BrO measurement scenario. The domain used for the sensitivity test
is indicated by a gray dashed box.
3.1.4 BrO retrievals over clear scenes in the Pacific background region
The effect of different wavelength intervals on the BrO retrieval was also
tested for the case of a clear scene in the Pacific background region
without strong BrO sources and clouds. As this area is located within the
background region used for the mean background spectrum, the BrO SCD should
be minimal. As shown in Fig. 7a, in most of the retrieval wavelength
intervals, retrieved BrO SCDs are in fact close to the detection limit.
Retrieval wavelength intervals having a start wavelength smaller than
330 nm
yield overestimations of SCDs, while retrieval wavelength intervals which
start at wavelengths longer than 333.4 nm show mainly underestimations. In
addition to the mean of the retrieved BrO SCDs, the root-mean-square error
(RMSE) of the BrO SCDs in the clear background measurement scenario was also
computed for each retrieval wavelength interval (Fig. 7c). The RMSE value
represents the scatter of the BrO SCDs around the true BrO SCD, and thus a
lower RMSE value indicates a better retrieval result with reduced
uncertainty on the slant column. As can be seen in Fig. 7c, wider fitting
windows show lower RMSEs, while more narrow fitting windows show higher
RMSEs in general. This is reasonable because if the fitting window is
extended, we can exploit more spectral points in the retrieval and improve
the quality of the columns from more available information (Richter et al.,
2011). However, this advantage is reduced by the increasing importance of
interfering species, which is the reason for the increased RMSEs for fitting
windows starting between 321 and 323 nm. In the BrO fitting rms map, the
values change abruptly at the wavelength of 322.6 nm, and high fit errors
occur at wavelengths <322.6nm. This reduced fitting quality in the
short wavelength range is attributed to the influence of absorption by
stratospheric O3.
Figure 7Mean values of (a) BrO SCDs, (b) fitting rms values, and (c) root-mean-square deviation of BrO SCDs retrieved over the clear part of the scene
in the Pacific background region using TROPOMI measurements at different
wavelength intervals.
3.1.5 BrO retrievals over cloudy scenes in the Pacific background region
In order to investigate the effects of cloud on the retrieval of BrO at
different evaluation wavelength ranges, a cloudy area was selected in the
Pacific background region and the sensitivity test was performed in the same
way as in Sect. 3.1.4. Figure 8 shows the means of retrieved BrO SCDs,
root-mean-square errors of BrO SCDs, and fitting rms values for the
measurement scenario of cloudy scenes over the background region. The
retrieved BrO SCDs in the cloudy scene are closer to the true value (0) than
in the clear scene measurement scenario. In addition, the RMSEs for the
cloudy sky measurement scenario are lower than for the clear sky case, but
the variation pattern of RMSEs as a function of the retrieval wavelength
interval is similar. Both fewer over- and underestimations of the BrO SCDs and
smaller deviations from the true BrO indicate lower uncertainties on the
cloudy sky BrO SCDs. This is expected because clouds are bright compared to
the dark ocean surface and thus the instrument receives a much larger
signal. However, cloud effects are complex in DOAS retrievals using UV–vis
measurements and the sensitivity depends on cloud properties such as cloud
fraction, thickness, and top height (Burrows et al., 2011; Theys et al.,
2011). The dependence of the retrieved BrO SCDs on the Ring effect due to
the presence of clouds is also shown in the map of fitting rms values (Fig. 8b).
Unlike the fitting rms variations in the cloud-free condition (Fig. 7b),
the cloudy sky measurement scenarios show relatively higher fitting rms
values at wavelengths longer than 358 nm, in agreement with the findings for
the volcanic plume.
Figure 8As Fig. 7 but for the cloudy part of the Pacific background
region.
In the previous sections, the influence of the retrieval wavelength interval
on the DOAS BrO retrieval was tested for different measurement scenarios.
Based on these test results, we can determine the best fitting window for
TROPOMI BrO retrievals for global analysis as well as for the primary BrO
source regions. The optimal retrieval fitting windows can be defined as
those wavelength intervals which show higher BrO signals with lower fitting
residuals in the BrO source regions, while the BrO SCDs should be minimal
with narrow distributions of SCDs over the clean Pacific background region.
The test for polar BrO retrievals showed unphysical values in wavelength
intervals including lower wavelengths smaller than 327 nm due to strong
O3 interferences. The effect of SO2 interference with strong
absorptions at lower wavelengths was also confirmed in the volcanic BrO
measurement scenario. Their interfering influences are reduced at longer
wavelengths as overall absorption cross section structures decrease; thus
retrieval wavelength intervals with a start limit above 327 nm are preferred
to avoid the strong dependency on the lower wavelength limit. In addition to
O3 and SO2 absorptions at shorter wavelengths, HCHO can also
interfere in DOAS BrO retrievals through anticorrelation between the two
gases, especially at ∼333nm. This potential artifact may be
attributed to the cross correlation caused by the absorption band shape of
BrO and HCHO, and it is necessary to find a retrieval wavelength interval
that minimizes possible errors caused by the BrO–HCHO cross correlation. In
the case of DOAS retrievals over the cloudy background region and the
volcanic plume, higher fitting errors were found in the wavelength intervals
extending beyond 362 nm because of imperfect correction of the Ring effect
and possibly also poorer fitting of O4 related to the temperature
dependency of the cross section. While minimizing these sources of
uncertainty on the retrieval, the range of reasonable BrO SCDs and low
retrieval errors for all measurement scenarios are observed in the
wavelength range of start limits of 334–338 nm and end limits of 358–362 nm.
Finally, the fitting window 334.6–358 nm was selected for TROPOMI BrO
retrievals with other retrieval parameters set as shown in Table 2, by
comparing fit residuals and SCD distributions for the remaining fitting
windows. Figure 9 shows a spectral fitting example of a pixel from orbit 2207
on 17 March 2018 passing over the Arctic sea ice region (72.55∘ N, 200.40∘ E in Fig. 12c). The larger BrO SCD of 4.72×1014molecules cm−2
was retrieved with relative small fitting error of 6.2 %.
Although the choice of the optimal fitting window may seem arbitrary to some
degree, the analysis of several different relevant scenarios for many
possible combinations of fitting windows described above demonstrates that
this is an overall robust selection. However, further studies are needed to
address the remaining challenges identified through the sensitivity tests,
in particular the possible spectral cross correlation of BrO with HCHO
around the selected fitting window.
Table 2DOAS settings used for the BrO slant column retrievals and
instrumental intercomparison.
Figure 9Example of a BrO fit result applying DOAS settings of
Table 2 in the Arctic BrO measurement case. The dashed line shows fit
results including the fitting residual and the solid line is the reference
spectrum scaled according to the fit result.
TROPOMI is an imaging spectrometer operating in push-broom configuration
where one direction of the two-dimensional charge-coupled device (CCD) detector is used for the
wavelength axis and the other for the across-track image of the instrument's 2600 km wide
field of view. This is similar in concept to OMI but with 450 instead of
60 spatial rows at much higher spatial resolution (Veefkind et
al., 2012). In this instrument configuration, across-track variability can
appear as stripes in trace gas columns due to small variations between the
rows which are not completely compensated for by lv1 calibration. Indeed, OMI
has shown this across-track striping problem (Boersma et al., 2007) and
explicit destriping is applied in many OMI products. In TROPOMI data,
stripes are also apparent in some trace gas maps when using solar irradiance
measurements as background. Two different approaches can be carried out to
correct for this: either the across-track variability is determined on a
daily basis over a region with minimal variability in trace gas columns and
subtracted from all retrieved slant columns, or irradiance background
spectra are replaced by averages of nadir observations taken over a
reference region. In this study, the second approach is used and daily
row-dependent mean radiances measured over a selected Pacific region
(30∘ S–30∘ N, 150–240∘ E) are used as
background spectrum. This approach can effectively remove across-track
stripes, but the retrieved differential BrO SCDs have to be corrected for
the viewing angle dependency of the column over the reference region. Here,
BrO SCDs were normalized to an assumed background level of a BrO vertical column density (VCD) of
3.5×1013molecules cm−2 over the Pacific background as suggested by
previous studies (Richter et al., 2002; Sihler et al., 2012) using a
two-step approach (see Fig. 10). First, an offset value for normalization of
the differential BrO SCDs is determined as the mode of the Gaussian
distribution of differences between the differential SCDs in the reference
sector and the normalized SCDs estimated by multiplying the background VCD
and a geometric air mass factor defined as
.
In a second step, this offset value is modified for each row depending on
the viewing zenith angle (VZA) to account for variations in the BrO air mass
factor. The normalized SCDs are finally calculated by subtracting the
VZA-dependent offset values from the measured SCDs.
Figure 10Illustration showing destriping and offset correction
steps described in Sect. 3.2 using TROPOMI orbit 2207 on 17 March 2018. (a) BrO
SCDs retrieved by daily row-dependent mean radiances in the Pacific
reference sector as background spectrum for the across-track correction,
(b) offset-corrected BrO SCDs treated by applying the normalization
approach including the VZA dependency on the BrO SCDs, and (c) BrO VCDs
computed by dividing the offset-corrected BrO SCDs by geometric AMFs.
Applying the retrieval settings described in Table 2, BrO vertical columns
have been computed from TROPOMI, OMI, and GOME-2B Level 1 spectra. It should
be noted that BrO VCDs were calculated using geometrical air mass factors
and data for solar zenith angles larger than 85∘ and chi-square
values greater than 0.01 were excluded. For OMI, ground/atmospheric scenes
affected by the row anomaly were also excluded by using the OMI
XTrackQualityFlags. The data in rows 42 to 45 were additionally ignored
because it was apparent from the BrO SCDs that they were affected by the row
anomaly although they were not marked as bad pixels. No cloud screening was
applied. Figure 11 shows the global distributions of the monthly averaged
BrO total vertical columns from the three satellites for April 2018. The
spatial distributions of BrO columns show a good consistency in spite of the
differences in instrument resolution and overpass times. High BrO values are
shown in the northern high-latitude region because of tropospheric bromine
explosions over the Arctic sea ice during springtime as discussed in
previous studies (Richter et al., 2002; Simpson et al., 2007; Begoin et al.,
2010), whereas BrO values are low in the tropics and midlatitudes where BrO
columns are primarily of stratospheric origin. Relatively higher BrO values
are found in the subpolar and Antarctic region compared to tropics and
midlatitudes. This might reflect real BrO column increases but could at
least partially be related to the use of geometric air mass factors (AMFs), which do not
consider the effects of surface albedo and clouds. The number of photons
detected at the satellite is larger over bright surface areas than over dark
surface areas. Therefore, the use of a simple AMF which does not consider
the sensitivity to surface albedo can underestimate BrO vertical columns
over dark surfaces such as the ocean in comparison to high-surface-albedo
regions such as the Antarctic region, north of Russia and Canada. In
addition to the surface albedo, clouds also affect signals detected at the
satellite. The light path length and intensity are significantly changed by
the cloud top height, cloud thickness, and cloud fraction. Using an AMF that
does not take into account the cloud effects can therefore result in errors
in the computed vertical columns, as can be seen from the slightly higher
BrO VCDs in the subpolar regions where cyclones are frequently observed due
to the subpolar low-pressure system (Fig. 11). Consequently, an improved AMF
reflecting the sensitivity of surface albedo, cloud properties, and BrO
vertical profile should be calculated to obtain more accurate vertical
column densities (Theys et al., 2011; Sihler et al., 2012), and this will be
investigated in detail in a follow-up study using surface albedo and cloud
information from the operational satellite products as they become
available.
To assess the random noise of the BrO retrievals for the different
instruments, distributions of SCDs and retrieval fitting rms values over a
clean Pacific region (10∘ S–10∘ N, 150–260∘ E)
were analyzed for April 2018. Here, differential BrO SCDs without the
background offset correction were used for more clear interpretation. As
shown in Fig. 11b, all three satellite BrO SCD distributions show nearly
Gaussian shape and are centered around zero with full width at half maximums (FWHMs) of 0.50, 0.80, and
0.79×1014molecules cm−2 for TROPOMI, GOME-2B, and OMI, respectively.
However, while TROPOMI and GOME-2B columns are symmetrically distributed
close to the detection limit, OMI data are slightly shifted towards positive
values. The latter is attributed to be a consequence of systematic biases
caused by the relatively lower quality of Level 1b radiance due to the
instrument degradation. TROPOMI shows the smallest scatter of BrO SCDs, with
OMI and GOME-2B having about 60 % larger FWHMs. TROPOMI retrievals also
show by far the smallest mode of the fitting rms distributions,
demonstrating the excellent signal-to-noise ratio per pixel even at the
unprecedented small footprint.
Figure 11(a) Global distributions of monthly mean BrO vertical columns
retrieved from TROPOMI, OMI, and GOME-2B measurements for April 2018. Data
with a solar zenith angle lower than 85∘ were used, and in the case
of OMI data, only data not affected by the row anomaly were included. (b) Distribution
of BrO SCDs and fitting rms values over a clean equatorial
Pacific region (10∘ S–10∘ N, 150–260∘ E)
for the same study period.
To evaluate the consistency of TROPOMI BrO retrievals with those from other
satellites, a comparison of BrO satellite retrievals was performed using
GOME-2B and OMI retrievals obtained by applying the same retrieval setting
(Table 2) to Level 1b data. However, for the comparison of different
satellite retrievals, several things have to be considered. First of all,
the three satellites have different spatial resolution, 40×80km2 for
GOME-2B, up to 13×24km2 for OMI, and 3.5×7km2 for TROPOMI. To
establish a relationship between different satellite values with different
pixel sizes, a spatial coupling of the different data sets is required. Here,
the higher-spatial-resolution TROPOMI data were averaged based on a grid of
lower spatial resolution. Each GOME-2 and OMI BrO measurement was compared
to the averaged TROPOMI BrO that lay within the distance of 0.3 and 0.1∘
from their center of pixels, respectively. In addition to different
pixel sizes, the effect of different overpass times between satellites
should be considered. TROPOMI, which has an ascending orbit with a local
Equator crossing time of 13:30 LT, shows a different overpassing time than
GOME-2B, which has a descending node equatorial crossing time at 09:30 LT,
whereas it has a similar afternoon overpassing time to OMI. Although
having a similar overpassing time on the ascending node to TROPOMI, recent
OMI data provide only limited data due to the loss of spatial coverage with
the expansion of the row anomaly, especially in the middle and east
across-track segments of the orbit (Torres et al., 2018). This led to a
difficulty in utilizing orbits having similar measurement times for the two
satellite instruments.
Figure 12a shows a scatter plot comparison between TROPOMI and OMI BrO VCDs,
and Fig. 12b compares TROPOMI and GOME-2B BrO VCDs. As mentioned before, BrO
VCDs were converted from SCDs by dividing geometric AMFs. The comparison was
performed for enhanced BrO plumes in the Arctic sea ice region on 17 March 2018
(Fig. 12c). Despite the different spatial resolutions and measurement
times of the instruments, TROPOMI BrO shows good agreements with both OMI
and GOME-2B BrO with correlations of 0.84 and 0.84 and slopes of 0.89 and
0.72, respectively. This good agreement and consistency of TROPOMI data with
previous satellite sensors suggest that these data could be used to extend
the existing long-term data set of space-based BrO observations, in
particular for tropospheric BrO explosion events.
Figure 12Scatter plots of (a) TROPOMI and OMI BrO vertical columns and (b) TROPOMI
and GOME-2B BrO vertical columns in (c) the selected region of
enhanced BrO plumes on 17 March 2018.
4.3 BrO observations in tropospheric source regions
4.3.1 BrO plumes over Arctic sea ice
Explosive enhancements of BrO in the troposphere taking place in the polar
boundary layer during spring have been reported from ground-based
measurements and satellite observations (Hönninger et al., 2004; Begoin
et al., 2010; Choi et al., 2012). As an illustration of the signature of
such events in TROPOMI data, Fig. 13 presents maps of the TROPOMI, OMI, and
GOME-2 measurements of total column BrO on 10 April 2018. A small compact
BrO enhancement as well as a long BrO plume extending along the coastline
can be identified in the figures. The long and thin enhanced BrO plume near
the coastline is prominent in the map of TROPOMI, while it can hardly be
discerned in the OMI and GOME-2B maps. For the OMI retrievals, a significant
part of the scene is missing because of filtering for pixels affected by the
row anomaly. The GOME-2B orbit shown was taken about 1 h before the
TROPOMI and OMI measurement times but the BrO plumes are detected in similar
locations and have a size comparable to in the TROPOMI data. However, the
details of the spatial distribution and plume shape cannot be confirmed due
to the lower spatial resolution of GOME-2.
Another example of a BrO explosion event case is shown in Fig. 14. A
relatively narrow and long shape of enhanced BrO over the Beaufort Sea can
be found in all three satellite maps. As discussed for the previous example,
TROPOMI data with the high spatial resolution of 3.5×7km2 yield a more
detailed view of the BrO explosion event compared to OMI and GOME-2B. The
enhanced BrO plumes appear around open leads and sea ice cracks shown as
slightly darker areas in the matching MODIS image (arrows pointing at
examples). In particular, the elevated BrO around the Banks Island and the
eastern Beaufort Sea (70–77∘ N, −140 to −120∘ E) could be significantly linked to open
leads since frost flowers and sea salt aerosols, which act as the source of
reactive bromine, can be formed in such areas (Simpson et al., 2007). Also,
opening of sea ice leads can locally create enhanced vertical mixing and
uplifting of bromine sources. However, the analysis of the long enhanced BrO
plume from the coast of Alaska towards the north should be cautious. The MODIS
image composed of the 7-2-1 bands can distinguish clouds (as white) from the
sea ice (as sky blue), and this image shows that the shape of the enhanced
BrO plume is similar to that of clouds. Convective clouds can be formed
around open leads due to the supply of water vapor and enhanced vertical
mixing, but computed BrO enhancement over clouds may have an error because
of the use of AMFs, which do not consider the effects of clouds. In spite of
this uncertainty, the enhancement of vertical columns by up to 4×1013molecules cm−2
compared to the surrounding values indicates that open leads
could be associated with the BrO enhancement. Small-scale BrO explosion events
around open leads or polynyas can be better investigated with the high-spatial-resolution TROPOMI data and will be the topic of a follow-up study.
Figure 13BrO geometric vertical columns observed over the Arctic sea ice
region on 10 April 2018 by (a) TROPOMI, (b) OMI, and (c) GOME-2B.
Figure 14BrO geometric vertical columns observed over the Arctic sea ice
region on 19 April 2018 from (a) TROPOMI, (b) OMI, and (c) GOME-2B. (d) MODIS true color image (left) and image using
combinations of 7-2-1 bands (right) from the Aqua satellite for the same
scene on the same day. Leads are slightly darker in the MODIS image as
indicated by the arrows.
Salt lakes are one of the strongest and most localized natural sources of
reactive bromine. Consequently, BrO amounts over multiple salt lakes and
marshes have been investigated with ground-based DOAS instruments and
satellites. High BrO concentrations with peak mixing ratios of 86 ppt at the
Dead Sea were observed by long-path DOAS measurements in 1997 (Hebestreit et
al., 1999), followed by studies of the diurnal cycle of BrO and the
relationships between BrO and O3 and meteorological factors in the Dead
Sea region (Matveev et al., 2001; Tas, 2005). BrO over salt lakes was also
studied using satellite measurements. Chance (2006) showed BrO enhancement
over the Great Salt Lake using OMI measurements and Hörmann et al. (2016) found a typical annual BrO formation cycle over the Rann of Kutch
seasonal salt marsh using long-term GOME-2 and OMI data.
The release of reactive bromine and enhanced BrO plumes over the Rann of
Kutch salt marsh are also readily detected by TROPOMI data. Daily mean BrO
VCDs over the Rann of Kutch area for TROPOMI and OMI, and MODIS true color
images for the time period from 11 April to 14 April 2018 are shown in
Fig. 15. It should be noted that the AMFs used in this work do not
consider surface albedo and cloud effects, and therefore BrO VCDs may be
overestimated over the bright salt marsh. BrO enhancements of up to
4.5×1013molecules cm−2 over background values are detected as
hot spots in both satellites. However, as can be seen in Fig. 15, TROPOMI
data show BrO plumes and small-scale variabilities much more clearly with
more spatial details than OMI data. In the case of OMI data, BrO plumes are
detected by only a few pixels, whereas TROPOMI can detect the same plumes by
hundreds of data points (∼150 pixels). This illustrates that
TROPOMI data will facilitate in-depth studies of localized small-scale BrO
events for multiple salt lakes and marshes.
Figure 15Daily BrO geometric vertical columns
(1013molecules cm−2)
over the Rann of Kutch salt marsh on 11, 12, 13, and 14 April 2018 from
TROPOMI (top row) and OMI (middle row) measurements as well as MODIS Aqua true
color images over the study region for the same days (bottom row).
Explosive volcanic eruptions lead to the formation of BrO in the
troposphere and lower stratosphere. The detections of BrO in volcanic plumes
has been reported by ground-based DOAS measurements for several volcanoes
(Bobrowski et al., 2003; Oppenheimer et al., 2006; Boichu et al., 2011). In
addition to ground-based measurements, BrO in a volcanic plume was first
detected in GOME-2 satellite data after the eruption of the Kasatochi
volcano by Theys et al. (2009). Following the first satellite volcanic BrO
detection, Hörmann et al. (2013) investigated 64 volcanic plumes and
BrO∕SO2 ratios using GOME-2. Schönhardt et al. (2017) found not
only volcanic BrO but also IO emissions using SCIAMACHY and GOME-2
measurements.
Not surprisingly, volcanic plumes containing BrO are also detected in
TROPOMI data. Figure 16 shows the plume over the Indonesian island of Bali
after volcanic activity at Mount Agung on 29 November 2017. Enhanced BrO
values of up to 8.5×1013 and dispersion of plumes by
the wind towards the southwest were detected by both TROPOMI and OMI. These
volcanic BrO plumes are associated with enhanced SO2 values as
identified from the NASA operational OMI product
(ColumnAmountSO2_TRM in OMSO2 version 3 product) with a
positive correlation between the species. As shown in Fig. 16, monitoring of
BrO emissions and their relationship to other gases from volcanic activities
is possible with TROPOMI data at higher spatial resolution and improved
sensitivity, which suggests that more detailed analysis of volcanic BrO will
be possible in the future.
Figure 16Volcanic BrO vertical columns (1013molecules cm−2) on 29 November 2017
after volcanic eruptions at Mount Agung on the Indonesian
island of Bali observed by (a) TROPOMI and (b) OMI. (c) Volcanic
SO2
vertical columns (DU) from the column amount SO2 TRM (mid-troposphere) of
the NASA operational OMSO2 product (https://disc.gsfc.nasa.gov/datasets/OMSO2_V003/summary, last access: 23 May 2019).
Adapting and optimizing the DOAS retrieval developed for earlier satellite
missions, a first BrO column retrieval for measurements of TROPOMI, the new
spaceborne instrument launched on the European Sentinel 5 Precursor
satellite in October 2017, was developed. One of the most important factors
in the DOAS retrieval is the wavelength interval selected as the fitting
window with the objective being to maximize the differential absorption
structures of the specific gas of interest and minimize the influence of
other interfering signals. However, finding the optimal retrieval wavelength
interval is not straightforward as instrumental factors as well as viewing
conditions and study area can impact the results. Similar to the approach
by Vogel et al. (2013), color-coded maps of DOAS retrieval results obtained
by systematically varying the retrieval wavelength interval were created for
various observation scenarios on TROPOMI data to determine the optimal
retrieval wavelength interval for BrO. Negative BrO SCDs, large deviations
from the expected BrO SCDs, and high fitting errors occur at shorter
wavelengths when strong absorption structures of O3 and SO2 are
included. The sensitivity of BrO retrieval to HCHO was also found by showing
anticorrelation between two gases. At wavelengths longer than 362 nm,
poorer results were found in the cloudy scene and volcanic plume measurement
scenario, presumably due to the wavelength dependency of the Ring effect and
imperfect fitting of O4. Based on the information gathered from the
sensitivity tests for different measurement scenarios, 334.6–358 nm was
selected as the optimal wavelength range for TROPOMI BrO retrievals for most
of the possible measurement situations. This fitting window yields reliable
BrO retrieval results with small fitting errors, but future studies on
quantitative assessments and cross correlations between BrO and all the
interfering absorbers are encouraged to further improve retrieval results.
As imaging instruments such as TROPOMI often show across-track offsets in
the retrieved columns, the DOAS BrO retrieval has to include a destriping
method. In this study, row-specific daily averaged earthshine radiances from
a Pacific background area are used as reference spectrum in the DOAS fitting
procedure and a post-processing offset correction is applied to convert the
resulting differential slant columns to absolute slant columns. Conversion
to vertical columns is achieved in this study by using a simple geometric
air mass factor.
As a first consistency test, TROPOMI BrO columns were compared with OMI and
GOME-2 data on both global and regional scales. TROPOMI BrO retrievals show
good agreements with OMI and GOME-2B BrO columns with high correlation
coefficients (slopes of the regression lines) of 0.84 (0.89) and 0.84 (0.72)
for enhanced BrO plumes in the Arctic sea ice region. Global maps of monthly BrO
columns also agree well between the three instruments. In addition to the
good consistency of TROPOMI BrO retrievals with other satellite products,
TROPOMI shows excellent performances with much smaller fitting rms values
and lower random scatter of BrO columns than OMI and GOME-2B. More
small-scale hot spots can be identified in greater detail by TROPOMI with its
improved signal-to-noise ratio and the excellent spatial resolution. Thus,
studies on small-scale BrO events in specific source regions where
comparatively lower-spatial-resolution satellite sensors such as GOME,
SCIAMACHY, GOME-2, and OMI provide only limited information and may even fail
to detect the small-scale plume will be enabled by TROPOMI data.
In spite of the overall good performance of BrO retrievals on TROPOMI data,
poor BrO spectral fits are sometimes found over inhomogeneous reflectance
scenes such as fractional clouds and ice shelves due to inhomogeneous slit
illumination. This inhomogeneous scene effect on the DOAS retrieval should
be corrected to obtain more accurate retrieval results. In this
demonstration study, a simplified air mass factor and no stratospheric
correction were applied because the main purpose of this study is to find
the optimal DOAS retrieval settings for BrO that reduce systematic biases by
minimizing effects of interfering absorbers and to assess the consistency
with previous satellite results. However, for future quantitative studies of
tropospheric BrO explosion events, stratospheric correction and improved air
mass factor calculation taking into account the observation conditions are
essential. In particular, investigation and evaluation of high-resolution
input data applicable to the unprecedented small footprint of TROPOMI should
be performed, which will be a subject of further work. In addition to the
satellite intercomparisons shown here, validation with ground-based
measurements is needed for more detailed assessment of the quality of
TROPOMI BrO columns. Judging from the examples evaluated in this study, BrO
columns from TROPOMI will contribute relevant high-resolution information to
many future studies exploring the halogen chemistry in the atmosphere.
Data availability
The sensitivity test results and monthly mean BrO VCD retrieved from TROPOMI, OMI, and GOME-2B (April 2018) presented in this publication can be found at http://www.iup.uni-bremen.de/doas/data/bro/s5p/seo_2019/ (last access: 27 May 2019). The underlying data of the figures are available upon request (contact persons are Sora Seo and Andreas Richter).
Appendix A: Improvement of the BrO retrieval with the Puķīte Taylor series
approach
To investigate the possibility of a DOAS fit improvement for the polar BrO
measurement scenario by applying the Taylor series approach (Puķīte et al.,
2010), we performed an additional sensitivity test. The test was conducted
in the same way and with the same measurement scenario as described in
Sect. 3.1.1, but two pseudo cross sections of O3 at 223 K ( and ) were added to the standard
DOAS settings. The reason for choosing the lower-temperature O3 cross
section is that this temperature is closer to the polar lower stratospheric
temperature in spring. These two fitting parameters are terms derived by a
Taylor series expansion to account for the wavelength dependency of the SCD,
which results from changes in light path distribution with wavelength and
absorption strength (Puķīte et al., 2010). Puķīte et al. (2010) demonstrated
that the application of the Taylor series approach to strong absorber
O3 leads to an improvement for the fit of the weaker absorber BrO in
the UV range of limb measurements.
Figure A1Color-coded means of (a) BrO SCDs and (b) fitting rms values
retrieved when including the Taylor series approach for O3 in
the DOAS analysis.
Figure A2Color-coded means of differences for (a) BrO SCDs and (b) fitting
rms values between analyses including the Taylor series approach
(see Fig. A1) and the standard DOAS (see Fig. 2 in Sect. 3.1.1).
Figure A1 shows BrO retrieval results obtained with the DOAS settings
including the Taylor series approach for the TROPOMI polar BrO measurement
scenario. Compared with the standard retrieval results (Fig. 2 in Sect. 3.1.1),
BrO retrieval results applying the Taylor series approach show
reduced fitting rms values across the whole retrieval wavelength range (see
Fig. A2b). In particular, fitting results at wavelength ranges
with a start limit between 323 and 327.6 nm where negative BrO SCDs and high
fitting errors occurred due to strong O3 interference are significantly
improved as BrO SCDs increased by molecules cm−2
and fitting errors decreased by ∼32 %. Also, the
abrupt changes of BrO SCDs around 333 nm of start wavelength and wavelength
range with start limits of 335–337.6 nm and end limits of 349–353.6 nm are
moderated by use of the Taylor series expansion for O3. These
sensitivity test results using TROPOMI nadir measurements clearly
demonstrate that introducing the Taylor series approach for O3 results
in an improvement of the DOAS fit. However, as is also clear from Fig. A1,
not all of the problems at low wavelengths apparent in Fig. 2 are solved
by including the Puķīte terms.
For the fitting window selected in this study (334.6–358 nm), the
application of the Taylor series approach for O3 does not significantly
affect BrO retrieval results compared with the standard DOAS retrieval.
However, as can be seen from Fig. A2, effects of the Taylor series expansion
for O3 on the BrO SCD retrieval vary depending on the retrieval
wavelength interval. The strength of absorption and the slant path of
scattered light in the atmosphere vary considerably with wavelength, and
thus the degree of improvement by the Taylor series approach for O3 in
the BrO retrieval is also different depending on the fitting wavelength
range. Therefore, it is necessary to evaluate the improvement of the SCD
retrieval by the Taylor series approach with respect to standard DOAS
retrieval according to the fitting window selected. Moreover, we showed only
sensitivity test results applying the Taylor series expansion of the lower
temperature O3 cross section to TROPOMI polar BrO measurements in this
section, but note that the effect of the Taylor series approach may be
different for different trace gas cross sections, temperature, and
measurement scenarios.
Author contributions
SS, AR, AMB, IB, and JPB were active in designing the study and analyzing results. SS performed the sensitivity tests and carried out data analysis. All authors discussed the results and commented on the paper.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “TROPOMI on Sentinel-5 Precursor: first year in operation (AMT/ACPT inter-journal SI)”.
It is not associated with a conference.
Acknowledgements
Parts of this study were funded through the University of Bremen, the DLR
project 50EE1618, and the SFB/TR 172 “ArctiC Amplification: Climate Relevant
Atmospheric and SurfaCe Processes, and Feedback Mechanisms
(AC)3” in sub-project C03 by the DFG. GOME-2 lv1 data were
provided by EMETSAT, and OMI lv1 and lv2 data were provided by NASA. Copernicus Sentinel-5P
lv1 data from 2018 were used in this study. Sentinel-5 Precursor is a
European Space Agency (ESA) mission implemented on behalf of the European
Commission (EC). The TROPOMI payload is a joint development by ESA and the
Netherlands Space Office (NSO). The Sentinel-5 Precursor ground segment
development has been funded by ESA and with national contributions from the
Netherlands, Germany, Belgium, and UK.
Financial support
The article processing charges for this open-access
publication were covered by the University of Bremen.
Review statement
This paper was edited by Diego Loyola and reviewed by two anonymous referees.
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TROPOMI on board the Copernicus Sentinel-5 Precursor platform can measure various atmospheric compositions at high spatial resolution and improved spectral resolution compared to its predecessors. Bromine monoxide (BrO) is one of the gases that can be derived from the measured radiances of TROPOMI using the differential optical absorption spectroscopy method. In this paper, we present the first retrieval results of BrO column amounts from TROPOMI observations on global and regional scales.
TROPOMI on board the Copernicus Sentinel-5 Precursor platform can measure various atmospheric...