Introduction
Nitrogen dioxide (NO2) and nitrogen oxide (NO) – together usually
referred to as nitrogen oxides (NOx = NO + NO2) –
are important trace gases in the Earth's atmosphere. They enter the
atmosphere due to anthropogenic (e.g. fossil fuel combustion, biomass
burning) and natural (e.g. microbiological processes in soils, wild fires,
lightning) processes. Over remote regions NO2 is primarily located in
the stratosphere. Stratospheric NO2 columns range from about
2 × 1015 to 7 × 1015 molec cm-2 between
the tropics and high latitudes. For polluted regions, up to 90 % of the
total NO2 column may be located in the troposphere. Tropospheric
NO2 columns over polluted areas are usually considerably higher, in
places even higher than 30 × 1015 molec cm-2. For
typical levels of OH, the lifetime of NOx in the lower troposphere
is less than 1 day (e.g. ).
Boundary layer NO2 directly affects human health . In
addition, nitrogen oxides are essential precursors for the photochemical
formation of ozone : they influence concentrations of OH
and thereby influence the lifetime of methane and
other gases. NO2 itself is a minor greenhouse gas, but the indirect
effects of NO2 on global climate change are probably larger, with a
presumed net cooling effect mostly driven by oxidation-fuelled aerosol
formation . Stratospheric NO2 originates mainly from
oxidation of N2O in the middle stratosphere, which leads to
NOx, which in turn acts as a catalyst for ozone destruction
. Stratospheric NOx can also
suppress ozone depletion by converting reactive chlorine and hydrogen
compounds into unreactive reservoir species (such as ClONO2 and
HNO3; ).
The important role of NO2 in both troposphere and stratosphere requires
monitoring of its concentration distribution on a global scale. Observations
from satellite instruments provide global coverage complementary to sparse
measurements by ground-based and in situ (balloon, aircraft) instruments.
NO2 column densities have been retrieved using the differential optical
absorption spectroscopy (DOAS) technique from space since the mid-1990s from
data acquired by the nadir-viewing UV/Vis backscatter instruments GOME
, SCIAMACHY , OMI
and the GOME-2 instruments aboard
MetOp-A and MetOp-B. TROPOMI , scheduled for launch in
2016, will extend the record of these observations.
The retrieval of NO2 from satellite measured spectra with DOAS is
certainly possible but not easy: the structure of the NO2 differential
absorption is weak and there are interfering signals from the surface,
atmosphere and instrumental issues. Most retrievals of NO2
concentrations are performed in the visible range between 400 and 500 nm,
taking into account other absorbers and processes relevant in this wavelength
range. Early satellite retrievals of NO2 focused on the dominant
absorbers NO2, ozone and water vapour, as well as rotational Raman
scattering (the so-called “Ring effect”). Recent years have shown
continuous improvements in the NO2 retrieval by accounting for weaker
absorbers, notably the O2–O2 collision complex and liquid water.
This paper describes a revision of NO2 slant column retrieval from
level-1b spectra measured by OMI since 2004, performed by a processor named
OMNO2A. The study was prompted by the observation, reported first by
N. Krotkov at the EOS-Aura meeting in October 2012 , that
OMI stratospheric NO2 concentrations are systematically higher than
those derived from SCIAMACHY and GOME-2 measurements by
0.5–1 × 1015 molec cm-2, after accounting for the
daytime increase in stratospheric NO2 . Recently,
confirmed the high bias in OMI stratospheric columns
compared to an ensemble of stratospheric NO2 retrievals from
satellite-based limb-sounding sensors. Section presents a
further comparison of OMI, SCIAMACHY and GOME-2 data, as well as
a comparison using ground-based measurements at the Jungfraujoch station, to confirm the
high bias in OMI NO2 data.
The revision of the OMNO2A settings and input is further motivated by a
number of issues regarding the absorption reference spectra
(Sect. ): (a) the need to update the spectra of ozone and
water vapour; (b) the need to account for the wavelength and row dependency
of the OMI slit function in the convolution of the spectra; (c) the need to
investigate whether including absorption by O2–O2 (so far omitted
from OMNO2A; cf. ) and liquid water
(cf. ) improves the NO2 retrieval
results. In addition, the effects on the DOAS NO2 retrieval of the
wavelength calibration of the OMI radiance spectra, introduced in OMNO2A
following the first appearance of the so-called row anomaly in 2007 but not
yet evaluated, has been investigated and the calibration settings have
been optimised (Sect. ). Lastly, it was recognised that it is
important for users of the OMI NO2 data to document the essential
elements, both the current and the updated, of the slant column retrieval in
one easily referable paper.
Observations of NO2 column densities
UV/Vis satellite-based NO2 observations
The main focus of this paper is NO2 data derived from measurements by
OMI , which are compared to NO2 data from the first
GOME-2 instrument and from SCIAMACHY
. All three instruments measure the backscattered and
direct sunlight in the UV and visible ranges from a sun-synchronous polar orbit.
OMI is aboard the EOS-Aura satellite and has been operating since 2004. The overpass is
at 13:40 local time (LT), with the satellite flying south to north on the
dayside of the Earth. Individual nadir ground pixels are 13 × 24 km2 at
the middle of the swath; the size of the pixels increases towards the edges
of the swath. The full swath width is about 2600 km and OMI achieves global
coverage each day.
Main settings of the DOAS retrieval of NO2 slant column
densities of the data versions used in this paper for the satellite
instruments OMI, GOME-2 and SCIAMACHY; for OMI the current settings and the
settings resulting from the discussion in this paper are given.
OMI – current
OMI – updated
GOME-2
SCIAMACHY
Wavelength range (nm)
405–465
405–465
425–450
426.5–451.5
Secondary trace gases
O3, H2Ovap
O3, H2Ovap, O2–O2, H2Oliq
O3, H2Ovap, O2–O2
O3, H2Ovap, O2–O2
Pseudo-absorbers
Ring
Ring
Ring
Ring
Degree of polynomial
5
5
3
2
Fitting method
non-linear
non-linear
linear
linear
Offset fitted
no
no
yes
yes
DOAS retrieval code
OMNO2A
OMNO2A
QDOAS
QDOAS
Retrieval responsible
KNMI
KNMI
BIRA-IASB
BIRA-IASB
Data version used
DOMINO v2.0
DOMINO v3.0
TM4NO2A v2.1
TM4NO2A v2.0
The first GOME-2 instrument is aboard the MetOp-A satellite and has
been operating since 2007.
The overpass is at 09:30 LT, with the satellite flying north to south
on the dayside of the Earth.
Individual ground pixels are 40 × 80 km2.
The full swath width is about 1920 km and GOME-2 achieves nearly
global coverage each day.
A second, identical GOME-2 instrument was launched aboard the MetOp-B
satellite in 2012.
In this paper, GOME-2 refers to the instrument aboard MetOp-A,
sometimes referred to as GOME-2A.
SCIAMACHY is aboard the satellite ENVISAT and operated in the
period 2002–2012.
The overpass was at 10:00 LT, with the satellite flying
north to south on the dayside of the Earth.
Individual ground pixels were 30 × 60 km2.
The full swath width was about 960 km and SCIAMACHY achieved global
coverage only once every 6 days, because it measured alternatively in a
nadir and limb viewing mode.
The DOAS retrieval technique, described in Sect. , is applied
to the backscattered spectra measured by the three satellite instruments to
obtain the NO2 slant column density (SCD). The SCD is the integrated
concentration of NO2 over light paths from the Sun through the Earth's
atmosphere to the satellite, weighted with their relative contribution to the
radiance.
The standard OMI NO2 SCD data are calculated at NASA by a processor
named OMNO2A. The retrieval results of OMNO2A are input for subsequent
processing to determine NO2 vertical column densities (VCDs), e.g. for
the DOMINO data product of KNMI (e.g. ;
) and NASA's NO2 Standard Product (SP;
e.g. ). For the OMI NO2 retrieval, the
selected spectral fitting window is 405–465 nm, wider than the often used
425–450 nm window in order to improve the effective signal-to-noise ratio.
For GOME-2 and SCIAMACHY NO2 SCD data, BIRA-IASB uses a processor based
on QDOAS , the multi-platform successor of their WinDOAS
package; see e.g. and . The DOAS
fit on GOME-2 and SCIAMACHY data uses almost the same wavelength window:
425.0–450.0 and 426.5–451.5 nm respectively (the small difference between
the fit windows is related to instrumental issues). The degree of the DOAS
polynomial is 3 for GOME-2 and 2 for SCIAMACHY.
Table provides an overview of the details of the
DOAS retrieval for the OMI, GOME-2 and SCIAMACHY sensors used in this study.
DOAS retrieval of NO2 slant column densities
The DOAS () technique matches an analytical
function that describes the relevant atmospheric physical processes
(scattering, reflection and absorption) to the satellite-measured spectrum.
In the OMNO2A setup, the modelled reflectance is expressed in terms
of intensities, which leads to a non-linear fit problem and allows
the effects of inelastic scattering to be described after a scattering event has
occurred:
Rmod(λ)=P(λ)⋅exp-∑k=1Nkσk(λ)⋅Nscd,k⋅1+CRingIRing(λ)I0(λ).
This physical model contains a low-order polynomial P(λ) of degree
Np that represents the slowly varying broad-band absorption, as well as
Rayleigh and Mie scattering processes in the atmosphere and smooth surface
reflection and absorption effects. Furthermore, the physical model includes
the spectrally varying absorption signatures σk(λ) and the
slant column amount Nscd,k of relevant absorbers k, notably
NO2, ozone (O3) and water vapour (H2Ovap).
Monthly average stratospheric NO2 VCD values (left axis; filled symbols)
and absolute differences (right axis; open symbols) in 1015 molec cm-2 of OMI,
GOME-2 and SCIAMACHY in March 2007 over the Pacific Ocean area
(60∘ S–60∘ N, 140–180∘ W), as a
function of latitude.
The error bars at the data points near the equator mark for that latitude
bin the average standard deviation of the total VCD (data source: http://www.temis.nl/).
The physical model accounts for inelastic Raman scattering of incoming
sunlight by N2 and O2 molecules that leads to filling-in of the
Fraunhofer lines in the radiance spectrum – the so-called “Ring effect”
(see ) – by describing these effects as a
pseudo-absorber, that is, by including a Ring reference absorption spectrum
along with the molecular absorption terms. In Eq. (),
CRing is the Ring fitting coefficient and IRing(λ)/I0(λ) the sun-normalised synthetic Ring spectrum. The term
between parentheses in Eq. () describes both the contribution
of the direct differential absorption (i.e. the 1) and the modification of
these differential structures by inelastic scattering (the
+CRingIRing(λ)/I0(λ) term) to the reflectance spectrum.
The DOAS procedure minimises the difference between the measured reflectance
spectrum Rmeas(λ) and the modelled spectrum Rmod(λ)
within a given wavelength window, in the form of minimisation of a
chi-squared merit function. The measured reflectance Rmeas(λ) is
determined from the radiance measured at top-of-atmosphere I(λ) and
the measured extraterrestrial solar irradiance spectrum I0(λ). Some
further details on the OMI NO2 DOAS slant column retrieval, such as the
merit function that is minimised and the definition of the RMS error, can be
found in Sect. S1 in the Supplement.
Intercomparisons of stratospheric NO2 columns
NO2 data from OMI, GOME-2 and SCIAMACHY are evaluated for 2007.
Stratospheric NO2 concentrations are best detected over the Pacific
Ocean, where tropospheric contributions to the NO2 column are small in
the absence of substantial sources of pollution. The Pacific Ocean area is
defined here as the area from 60∘ S to 60∘ N and from
140 to 180∘ W. DOMINO v2.0 data are used for OMI
, TM4NO2A v2.1 for GOME-2 and TM4NO2A v2.0 for SCIAMACHY
.
Figure shows the monthly average stratospheric
NO2 column for the three instruments and their mutual differences as a
function of latitude for March 2007; for other months (not shown) the
comparisons look quite similar. The OMI stratospheric columns are clearly
higher than those of GOME-2 by about
1.0 × 1015 molec cm-2, consistent with
, who reported a similar high bias in OMI and low bias in
SCIAMACHY data relative to stratospheric NO2 columns obtained from an
ensemble of limb and nadir sensors. The GOME-2 stratospheric columns (not
included in the study of ) in turn are higher than
those of
SCIAMACHY by 0.1–0.3 × 1015 molec cm-2.
Average differences in stratospheric NO2 columns over the
Pacific Ocean area (60∘ S–60∘ N, 140–180∘ W) of 2007 of OMI, GOME-2 and SCIAMACHY, where the averages are
computed from monthly latitudinally binned data. The relative difference
(right column) is given as percentage of the column values of the second
instrument in the difference, e.g. w.r.t. SCIA in the difference OMI -
SCIA (data source: http://www.temis.nl/).
Absolute values
Relative difference
Instruments
[× 1015 molec cm-2]
[%]
OMI – SCIA
+1.28±0.15
+80.1±9.6
OMI – GOME-2
+1.14±0.18
+65.6±10.3
GOME-2 – SCIA
+0.14±0.09
+8.7±5.8
Figure shows that there is only a weak variability of the
intra-sensor differences with latitude and that the differences are similar
to within 0.2 × 1015 molec cm-2. This weak variability
with latitude and independence of the month indicates that the differences
between the instruments is dominated by an additive offset.
Table lists the annual averaged 2007 intra-sensor
differences over the Pacific Ocean area. The difference of
1.1–1.3 × 1015 molec cm-2 between OMI (overpass at
13:40 LT) and the two mid-morning sensors is considerably larger than the
increase of stratospheric NO2 between the respective measurement times.
Photochemical models suggest a latitude-dependent increase of 10–30 % in
stratospheric NO2 between 09:30 and 13:40 LT. This increase reflects
the production of NO2 from N2O5 photodissociation and
corresponds to an increase of 0.1–0.6 × 1015 molec cm-2
.
The comparison of data from the ground-based SAOZ and FTIR instruments at the
Jungfraujoch station with satellite data by was
repeated,
now also including OMI data and extending the GOME-2 and SCIAMACHY data sets
to the end of 2012 (see Sect. S2 in the Supplement). The results of the
comparisons also strongly suggest that OMI stratospheric NO2 is biased
high. Since the air-mass factor calculations for NO2 in the stratosphere
are straightforward (with an error of less than 1 %), the high bias in OMI
stratospheric columns originates from the slant column retrieval. As a result
of this finding, the details of the OMI NO2 spectral fitting OMNO2A were
revisited.
Improvements to the OMI NO2 retrieval
Reference spectra
The set of reference spectra in the current OMNO2A
processing has been introduced in August 2006.
Since then a number of improved reference spectra data sets have been
reported in the peer-reviewed literature.
In addition, the reference spectra used in the current OMNO2A processing
have been convolved with the OMI slit function, described by a
parametrised broadened Gaussian function , but without
taking the wavelength and row dependency (i.e. viewing angle
dependency) of the slit function into account.
For these reasons all relevant cross sections are generated anew, based on
the latest established absorption spectra, and convolved with the OMI slit
function while now taking the wavelength and row dependency of the slit
function into account in the form of a row-average slit function. The OMI
slit function and the
implementation of the convolution are given in Sect. S3 in the Supplement.
Details of the relevant reference spectra used in the current and forthcoming
OMNO2A slant column fit are given in Sect. S4. The updated reference spectra
are
solar spectrum Iref(λ), from
NO2 absorption, from
O3 absorption, from , version 3.0 (Dec. 2004)
water vapour (H2Ovap) absorption, based on the HITRAN 2012 database
O2–O2 absorption, from
liquid water (H2Oliq) absorption, from
Ring radiance spectrum IRing(λ), computed following
.
The reference spectra labelled “v2006” below refer to those used in the
current OMNO2A processor (used in, for example, the DOMINO v2.0 data set),
while “v2014” refers to the updated reference spectra. The relation between
these labels and the official version numbering of OMNO2A is described in
Sect. S5.
Other absorption features
Over tropical forests, detectable contributions from glyoxal (CHOCHO) have
been reported, and its retrieval requires the inclusion of NO2
absorption (e.g. ). Conversely, however, glyoxal
absorption is only a very minor interference for NO2 absorption, so that
it can be safely neglected.
have investigated absorption signatures attributable to
sand, e.g. over deserts, but this signature is broadband in the OMI NO2
fit window (any structure in the signature lies well beyond the fit window)
and is therefore not accounted for here.
Absorption by vibrational Raman scattering (VRS;
e.g. ) is known to play a role over open
waters and thus may have an impact on the NO2 retrieval; however, it is
unclear whether including VRS improves the retrieval results, partly
because its signature is apparent over areas where it certainly is not
playing a role, e.g. over deserts (A. Richter, personal communication, 2014). In addition, the
VRS signature does not seem to be independent from the signature of liquid
water absorption . For these reasons, absorption by VRS is
not investigated here.
Wavelength calibration
The measured solar irradiance spectrum I0(λ) used in the OMI
NO2 DOAS fit has been constructed from a yearly average of daily solar
irradiance measurements by OMI during 2005 and has an accurate wavelength
calibration.
From the start of the OMI mission, the level-1b radiance spectra I(λ)
of OMI are given on an initial assigned wavelength grid .
This assigned wavelength grid – hereafter referred to as “wcA” – was at the
time accurate enough for the NO2 retrieval with OMNO2A. After the onset
of the first row anomaly in June 2007 and the
subsequent growth of this issue after May 2008, however, the assigned
wavelength grid appeared to be less accurate and, consequently, hampered
sufficiently accurate NO2 retrievals in all rows, including those not
affected by the row anomaly.
Pacific Ocean test orbit average main results of the wavelength
calibration and spectral fit, using the v2014 reference spectra for the
wavelength calibration windows mentioned in Sect. .
Calib. window
Shift
RMS
NO2 error
Begin
End
× 10-3
× 10-4
× 1015
Name
(nm)
(nm)
(nm)
(–)
(molec cm-2)
wcB
408.0
423.0
-3.63
0.97
0.99
wcN
409.0
428.0
-4.68
0.95
0.97
wcC
425.5
443.0
-7.70
1.09
1.10
wcF
405.0
465.0
-6.83
1.02
1.04
The NO2 fit results were improved by the introduction of a wavelength
calibration in OMNO2A in January 2009. This wavelength calibration determines a
wavelength shift for each individual radiance spectrum I(λ) from a
fit against the reference solar spectrum Iref(λ), taking the Ring
effect into account (cf. ), starting from the assigned
wavelength grid wcA. The wavelength calibration in the current OMNO2A
processing, called “wcB” hereafter, uses 408.0–423.0 nm as the
calibration window. This window was chosen because it covers some distinct Fraunhofer
features in the solar spectrum. Due to the construction of the OMI detector, a
squeezing or stretching of the wavelengths is unlikely (which is confirmed by
ongoing tests on OMI data as preparation for the implementation of a
wavelength calibration for TROPOMI which includes the possibility of a
squeeze/stretch in the calibration), so that the shift found from the
calibration window is representative for the whole NO2 fit window. The
relation between the wavelength calibration labels and the official version
numbering of OMNO2A is described in Sect. S5.
With the update of the solar reference spectrum Iref(λ) and the
Ring radiance spectrum IRing(λ), the wavelength shift determined in
calibration window wcB turns out to be different from the shift found in the
current OMNO2A setup. This change in the wavelength grid of the level-1b
spectra directly improves the fit results: both the RMS and the error on the
NO2 SCD are reduced. Using the v2006 reference spectra for NO2,
O3 and H2Ovap (and not yet including O2–O2 and
H2Oliq), the changes due to the introduction of the new solar and Ring
reference spectra in the wcB wavelength calibration, averaged between
60∘ S and 60∘ N over the Pacific Ocean test orbit (see
Sect. ), are as follows:
wavelength shift from +0.55 to -3.63 × 10-3 nm
RMS error from 1.39 to 1.15 × 10-4 (-17.4 %)
NO2 error from 1.29 to 1.17 × 1015 molec cm-2
(-9.2 %)
NO2 SCD from 8.54 to 8.04 × 1015 molec cm-2
(-5.8 %).
Since the spectral sampling of OMI is about 0.21 nm
, a shift of -3.62 × 10-3 nm corresponds to 1.7 % of
a wavelength pixel.
Given that the NO2 fit results depend so clearly on the wavelength
calibration, it was decided to test a range of calibration windows. Both the
starting and end point of the calibration window were varied in steps of
0.5 nm, with a minimum size of 10 nm for the window, over the complete
405–465 nm fit window for a total of 5151 possible calibration windows. The
fits were performed on the Pacific Ocean test orbit with all new v2014
reference spectra, including O2–O2 and H2Oliq absorption.
From these calculations the “optimal calibration window”, defined as the
window that results in the lowest RMS and NO2 error in the subsequent
DOAS fit, was found to be 409.0–428.0 nm. This new calibration window,
hereafter “wcN”, covers one more distinct Fraunhofer line than wcB
(cf. Fig. S4 in the Supplement).
Pacific Ocean test orbit average relationship between the RMS error and the
NO2 SCD for the 5151 wavelength calibration windows investigated.
The right axis of the main plot is an approximation: it gives the wavelength
shift constructed from the linear relationship with the NO2 SCD
mentioned in the text.
Table lists the calibration shift and the RMS and
NO2 error of the subsequent DOAS fit for calibration windows wcB and
wcN. For comparison, Table also gives the fit results using
two other calibration windows: one spanning the full fit window (“wcF”) and
one more or less at the centre of the fit window (“wcC”). For the other
orbits of the same day (not shown), minimal RMS is achieved either in the wcN
window or in a slightly different window, but the difference between that RMS
and the RMS of wcN is less than 0.05 %. Hence, wcN is selected as the
optimal wavelength calibration window to be implemented in the new version
of the OMNO2A processor.
Results of the NO2 SCD fit for the different steps of the
updates of the OMNO2A processing for the Pacific Ocean orbit. Case 0
represents the current OMNO2A version (v1) and case 4 is the updated version
(v2) settings. Cases 1 through 4 follow the updates listed at the beginning
of Sect. . The numbers between parentheses are percentage
changes w.r.t. case 0. The NO2 SCD error is given in absolute value and
as percentage of the NO2 SCD column. The NO2 VCD in the last
column is determined from the SCD and the geometric air-mass factor.
Solar
Calib.
NO2, O3
O2–O2
RMS error
NO2 SCD
NO2 SCD error
NO2 VCD
Case
Ring
window
H2Ovap
H2Oliq
(–)
(molec cm-2)
(molec cm-2)
(%)
(molec cm-2)
0
v2006
wcB
v2006
no
1.39 × 10-4
8.54 × 1015
1.29 × 1015
15.1
3.10 × 1015
1
v2014
wcB
v2006
no
1.15 (-17.4 %)
8.04 (-5.8 %)
1.17 (-9.2 %)
14.5
2.92 (-6.1 %)
2
v2014
wcN
v2006
no
1.13 (-18.7 %)
7.75 (-9.2 %)
1.16 (-10.1 %)
14.9
2.81 (-9.6 %)
3
v2014
wcN
v2014
no
1.06 (-23.6 %)
7.96 (-6.8 %)
1.09 (-15.2 %)
13.7
2.89 (-7.0 %)
4
v2014
wcN
v2014
yes
0.94 (-32.0 %)
7.38 (-13.5 %)
0.97 (-24.6 %)
13.1
2.68 (-13.7 %)
Uncertainty in NO2 SCD related to calibration
Figure shows the relationship between the RMS error
(horizontal axis) and the resulting NO2 SCD (left exist) for all
calibration windows of the Pacific Ocean test orbit. The minimum RMS is
achieved for calibration window wcN (409.0–428.0). There are 112 possible
calibration windows with an RMS within 0.5 % of the RMS of wcN, and these
calibration windows all have an end-wavelength below 430 nm. For these
windows, the NO2 error ranges from 0.97 (the value for wcN) to
0.98 × 1015 molec cm-2, and the NO2 SCD ranges from
7.23 to 7.47 × 1015 molec cm-2. The latter variation
can be considered a measure for the uncertainty in the NO2 SCD related
to the wavelength calibration: 0.12 × 1015 molec cm-2
(0.05 × 1015 molec cm-2 in terms of the NO2 VCD
when using a geometric air-mass factor).
There appears to be an almost perfectly linear relationship between the
NO2 SCD and the shift of the calibration for the investigated range of
wavelength shifts: NO2 SCD
[× 1015 molec cm2] = 2.325 ⋅ shift [× 10-2 nm] + 8.470,
with a correlation coefficient of r=0.99997. This linear relationship
implies that an error in the wavelength shift of 1 × 10-3 nm (0.5 % of
a detector pixel) corresponds to a change in the NO2 SCD of about
0.2 × 1015 molec cm-2. Depending on the desired accuracy
of the retrieved NO2 column, e.g. for future satellite missions, the
relationship poses firm requirements on the accuracy of the wavelength grid.
The effect of spectral misalignments, i.e. a mismatch between the
wavelengths of the measured spectra and the reference spectra, on DOAS fit
results has also been investigated, e.g. by and
.
Absolute values (top row) and absolute differences (bottom row) of the orbit
average RMS error (left column, × 10-4) and NO2 SCD (right column,
× 1015 molec cm-2) as a function of the OMI orbit number on 1 July 2005; the
Pacific Ocean orbit is number 14.
The case numbers refer to the cases listed in Table .
The difference “case 0 – case 2” (blue line) refers to the updates of the
wavelength calibration, “case 2 – case 4” (black line) to the updates of
the reference spectra, and “case 0 – case 4” (red line) to all updates put
together.
Results of the OMI NO2 retrieval improvements
The improvements for the OMNO2A NO2 SCD retrieval discussed above
comprise four steps:
the update of the high-resolution solar reference
spectrum and the Ring spectrum used for the wavelength calibration;
the change of the wavelength calibration window from wcB to wcN;
the update of the reference spectra of NO2, O3 and
H2Ovap;
the inclusion of absorption by the O2–O2 collision complex
and by liquid water.
The current OMNO2A processing system is referred to as “v1” below, while the
processing using the updated spectral fit settings is named “v2”.
Current vs. updated NO2 fit results
For the comparison of the current and updated OMNO2A spectra fit results, the
OMI orbit over the Pacific Ocean on 1 July 2005 (orbit number 05121) is used.
Other orbits of this day and of some other days in 2005 are used to evaluate
the robustness of the findings. Only ground pixels with a solar zenith angle
less than 75∘ are considered; in most comparisons using orbit
averages, the data are limited to the latitude range
[-60∘:+60∘]. Since stratospheric NO2 is the main focus of
this study, no filtering of cloudy pixels is applied.
Absolute differences in the NO2 SCD as a function of latitude averaged
over all 15 orbits.
The case numbers refer to the cases listed in Table ,
similar to the bottom panels of Fig. .
For comparison, the concentration of O2–O2 as a function of latitude
is shown in arbitrary units (green short-dashed line).
Table lists the NO2 SCD, the NO2 SCD
error and the RMS error values for the step-by-step improvements listed
above. The first case in the table represents the current OMNO2A
settings for the SCDs used in the DOMINO v2.0 and NASA SP v2.1 NO2 data
products; case 2 represents the improved wavelength calibration; and case 4
the implementation of all updates together, i.e. the updated “v2” version of
OMNO2A. Figure shows the absolute values of and
differences between cases 0, 2 and 4 in Table of the RMS
error and the NO2 SCD for all 15 orbits of 1 July 2005.
These results show that the wavelength calibration update (case 2) leads to
large improvements in the spectral fitting of OMI NO2 and the updates of
the relevant reference spectra lead to smaller yet still significant
improvements of the fit. The lower panels indicate that differences in RMS
and NO2 SCD vary only a little from orbit to orbit. When averaging the 15
orbit averages and giving changes w.r.t. the case-0 averages, the conclusions
are that
the wavelength calibration updates reduce the RMS by 23 % and the SCD by
0.85 × 1015 molec cm-2,
updates in the reference spectra further reduce the RMS by 9 % and the SCD
by 0.35 × 1015 molec cm-2,
in total the RMS improves by 31 % and the SCD is smaller, on average, by
1.20 × 1015 molec cm-2.
The latitudinal dependency of the changes in the NO2 SCD
averaged over the 15 orbits is shown in Fig. .
The change in NO2 SCD resulting from the update of the wavelength
calibration (blue line with squares) shows little variation with latitude,
indicating that the imperfect wavelength calibration likely represents an
additive offset of 0.85 ± 0.04 × 1015 molec cm-2 in the current “v1 OMNO2A”
retrieval.
Absolute values of the updated data (case 4, top row) and absolute
differences between the current and the updated data (bottom row) of the
orbit average RMS error (left column, × 10-4) and NO2 SCD (right
column, × 1015 molec cm-2) as a function of the OMI orbit
number on 4 selected days.
The case numbers refer to the cases listed in Table .
Measurements from the rows affected by the row anomaly in the 2013
(rows 25–48 and 53) have been omitted from all data in this comparison.
However, the change in NO2 SCD due to the update of the trace
gas reference spectra and the inclusion of absorption by O2–O2 and
H2Oliq (black line with triangles in Fig. )
depends clearly on latitude in absolute numbers and as a percentage of the
NO2 SCD: the change ranges from
0.1 × 1015 molec cm-2 (3 %) in the tropics to
0.8 × 1015 molec cm-2 (5 %) at high latitudes. The
change in the NO2 SCD increases with latitude and reflects the inclusion of
O2–O2 absorption, which increases poleward as shown by the green
short-dashed line in Fig. .
Overall, the improved OMNO2A NO2 SCD is reduced by
1.0 to 1.8 × 1015 molec cm-2 (10 to 16 %), the
NO2 SCD error by 0.2 to 0.3 × 1015 molec cm-2
(16 to 30 %) and the RMS error by 24 to 35 %, depending on latitude.
The above settings of case 0 and case 4 have been evaluated on the 4 test
days used in the EU FP7 project QA4ECV to evaluate the robustness of the
improvements for other days of the test year (2 February and 16 August 2005) and
for more recent OMI data (4 February and 4 August 2013).
Figure shows the orbit average values of the RMS
error and the NO2 SCD the updated retrieval values and the differences
between the current and the updated values. The other fit coefficients (not
shown), such as ozone and water vapour, as well as the associated error
terms, show no systematic differences between the results of the current and
updated settings either. This comparison confirms that the improvements are
robust over time and can therefore be used for reprocessing the entire OMI
record.
To facilitate a comparison of the improved spectral fit for OMI with data
from SCIAMACHY, the NO2 slant columns of both instruments are converted
to vertical columns with the geometric air-mass factor Mgeo, taking the
curvature of the Earth's atmosphere into account . This
conversion ensures that the considerable differences in viewing angles
between the two instruments do not affect the comparison.
Comparison of the NO2 VCD values (lines with symbols) of the new v2
OMNO2A (red circles) and old v1 OMNO2A (blue squares) retrieval for the
Pacific Ocean orbit of 1 July 2005 and the average SCIAMACHY data (black
triangles) over Pacific Ocean of the same day.
The two lines without symbols show differences between the NO2 VCD
values.
A comparison between OMI and SCIAMACHY should be limited to
latitudes below 45∘, because for higher latitudes the instruments
cover different geographic areas.
Figure shows a comparison of the OMI Pacific Ocean
test orbit using the “v1 OMNO2A” and the “v2 OMNO2A” retrieval and of the
SCIAMACHY data over the Pacific Ocean of the same day (lines with symbols).
Given SCIAMACHY's poor geographic coverage, the data of its three orbits over
the Pacific are averaged for this comparison. The figure shows that the
discrepancy between OMI and SCIAMACHY has been reduced from 1.2 to
0.8 × 1015 molec cm-2.
The remaining offset between the new v2 OMNO2A and the SCIAMACHY NO2
VCDs of 0.8 × 1015 molec cm-2 can be explained in part
by the difference of about 0.5 × 1015 molec cm-2
expected due to the diurnal cycle of stratospheric NO2. It should,
furthermore, be kept in mind that SCIAMACHY has a negative bias of
0.1–0.2 × 1015 molec cm-2 w.r.t. GOME-2
(Sect. ; ) and w.r.t. an ensemble
of stratospheric NO2 limb sensor measurements .
In addition, the OMI NO2 is retrieved by OMNO2A with a non-linear fit
approach in the 405–465 nm window, while the SCIAMACHY NO2 is
retrieved by QDOAS with a linear fit approach in the 425–450 nm window
(cf. Table ). The difference in fit window and fit
approach explains another 0.1–0.2 × 1015 molec cm-2 in
the difference between OMNO2A and SCIAMACHY, as is shown in
Sect. .
Spectral residual of the NO2 retrieval fit with the updated reference
spectra without (case 3, red solid lines) and with (case 4, blue dashed
lines) O2–O2 and H2Oliq absorption included for two ground
pixels along row 29 (0-based): pixel 425 (located at 20.2∘ S, 135.4∘ W; top two curves, left axis) and pixel 592
(0.0∘ S, 139.8∘ W; bottom two curves, right axis) of the
Pacific Ocean test orbit.
To clarify the graph, the wavelengths of three detector pixels are averaged,
thus mimicking the fact that OMI's spectral resolution is about 3 times
its spectral sampling.
About including O2–O2 and liquid water
The spectral residual of the NO2 retrieval describes the unexplained
portion of the measured spectrum after a selected set of absorption
signatures is accounted for in the fit model. Figure
shows the spectral residual of two cloud-free pixels along row 29 (0-based)
of the Pacific Ocean test orbit: pixel 425 and pixel 592 using the updated
reference spectra without (case 3, red solid lines) and with (case 4, blue
dashed lines) taking absorption of O2–O2 and H2Oliq into
account. Pixel 425 is over clear open ocean water with a low chlorophyll
concentration
(0.028 mg m-3), while pixel 592 is over ocean water with a relatively high
chlorophyll concentration (0.351 mg m-3). An anti-correlation between the
chlorophyll concentration and the liquid water absorption coefficient is
expected, because the higher the chlorophyll concentration the more opaque
the water is and therefore the shorter the penetration depth of light will
be.
Figure shows that the residual of pixel 425 has a clear
structure in the range 445–465 nm in case liquid water absorption is not
accounted for, while this structure does not appear for pixel 592. If
H2Oliq is included in the fit, the residual of pixel 425 is much
reduced (the RMS decreases by -35 %), while there is hardly any change in
the residual of pixel 592 (by -2 %). For both pixels the NO2 SCD
reduces by about 6 % and the retrieved H2Oliq fit coefficients are
physically meaningful: for pixel 425 the H2Oliq fit coefficient is
10.49 m and for pixel 592 it is 0.83 m.
Retrieved H2Oliq coefficient (in m; red solid line, left axis)
as a
function of latitude for row 29 of the Pacific Ocean test orbit, showing
only ground pixels for which chlorophyll concentration data are available.
Also shown, with values along the right axis, are the chlorophyll
concentration (in mg m-3; blue dashed line) and the cloud cover fraction
(magenta dotted line).
The inset shows the H2Oliq coefficient as a function of the chlorophyll
concentration separately for ground pixels with latitudes between
± 40∘ (red crosses) and higher latitudes (green circles).
World map of the H2Oliq coefficient (in m) based on all 15 OMI orbits
of 1 July 2005; the Pacific Ocean test orbit is marked by a black triangle.
All ground pixels with solar zenith angle less than 75∘ are plotted;
no filtering for cloudy pixels was applied.
Figure shows the retrieved H2Oliq coefficient
(left axis, red solid line) as a function of latitude for all ground pixels of
detector row 29 for which a chlorophyll concentration is available. For
comparison the graphs also shows the chlorophyll concentration and the cloud
fraction for the same pixels (right axis); cloudiness clearly leads to lower
H2Oliq coefficients, as expected. The inset of Fig.
shows the relationship between the H2Oliq coefficient and the
chlorophyll concentration. The graph makes a distinction between the ground
pixels in the latitude range 40∘ S to 40∘ N (red crosses)
and outside that range (green circles). Pixels at latitudes above
40∘ N have chlorophyll concentration >0.3 mg m-3 and for that
reason low H2Oliq coefficients. Pixels at latitudes <40∘ S at
high solar zenith angle (above 70∘) have low H2Oliq coefficients
(below about 2 m) even though chlorophyll concentrations are low
(<0.2 mg m-3).
Figure shows a global map of the H2Oliq
coefficient retrieved from all OMI orbits of 1 July 2005. Open water areas
are clearly visible on the map and land/sea boundaries show up sharply in
areas like the Mediterranean Sea, the Gulf of Mexico, around Madagascar and
the east coast of South America. Along the west coasts of South America,
North America and Africa, for example, the H2Oliq coefficient is very
low, consistent with high chlorophyll concentrations there. Note that since
the processing is not optimised for the retrieval of the H2Oliq coefficient, it is not possible to say how accurate the coefficient is, but
overall its values appear realistic. Positive H2Oliq fit coefficients
over areas with little or no liquid water absorption, such as over land or
cloudy scenes, are small.
Retrieved values for the O3 SCD (top-left), the O2–O2 SCD
(bottom-left) and H2Oliq coefficient (bottom-right) as a function of
latitude for the Pacific Ocean test orbit for retrievals without and with
absorption by O2–O2 and H2Oliq included in the fit as
specified by the legend in the top-right corner; case numbers 3 (black
dashed) and 4 (red solid) refer to the cases listed in
Table .
Also plotted are the O3 SCD value from the OMI ozone slant column
product OMDOAO3 (magenta long-dash-dotted) and the O2–O2 SCD value
from the OMCLDO2 cloud product (blue short-dash-dotted).
The inclusion of the absorption of H2Oliq and the O2–O2 collision
complex in the NO2 fit is justified since their absorption is known to
affect the radiance I(λ) – unless their inclusion would reduce the
quality of the NO2 fit, which is not the case.
Figure shows the effect of including
O2–O2 and H2Oliq in the retrieved O3 SCDs. Without
either of the two additional absorbers, ozone slant columns are negative in
the regions where absorption in open water is taking place. Adding both
absorbers brings the retrieved O3 SCD close to the values given in the
official OMI ozone SCD data product OMDOAO3; the improvement is mostly due to
including H2Oliq absorption.
Differences of the NO2 SCD values of the new v2 OMNO2A fit results
(i.e. the red line with circles in Fig. ) with QDOAS
retrievals using different fit windows with a linear fitting approach (filled
symbols) and using a non-linear fitting approach in the standard fit window
(open circles) for the Pacific Ocean test orbit.
The size of the steps along the vertical scale is the same as in
Fig. to ease comparison of the SCD differences.
Including O2–O2 absorption but not H2Oliq absorption does
not result in realistic O3 SCD values. Furthermore, the retrieved
O2–O2 SCD values appear realistic compared to the values given in
the official OMI cloud data product OMCLDO2 if H2Oliq is included in
the fit. Including O2–O2 absorption has a small effect on the
retrieved H2Oliq coefficient (bottom-right panel in
Fig. ).
In summary, (a) including liquid water absorption leads to significant
improvements in the NO2 retrieval fit for pixels over clear open waters,
without affecting other pixels, results in physically meaningful
H2Oliq and O3 absorption coefficients; and (b) simultaneously
including O2–O2 absorption results in realistic O2–O2 SCDs and improves the fit, especially if light paths are long.
Comparison between OMNO2A and QDOAS
Since the OMI, SCIAMACHY and GOME-2 spectral fits have been done with
different fitting approaches and fitting windows
(cf. Table ), the sensitivity of the NO2 SCD to the
spectral fitting approach is studied here. Such estimates are important for
satellite intercomparisons and the generation of long-term seamless
multi-sensor data records such as the QA4ECV project. The flexible QDOAS
package (version 2.105, May 2013), which provides a linear fit approach
(cf. the details on DOAS fitting in Sect. S1 in the Supplement), is used for
this study with the v2014 reference spectra on the OMI Pacific Ocean test
orbit.
Figure shows that the OMNO2A and QDOAS processors,
both applied in the 405–465 nm window, result in small differences in the
NO2 SCDs of -0.2 to +0.1 × 1015 molec cm-2. The
agreement between these two is therefore quite good considering there are
several differences between the processors: the fitting method differs, the
Ring effect is included differently and the wavelength calibration of QDOAS
differs from the OMNO2A wavelength calibration.
QDOAS has the option to apply a non-linear intensity fitting method instead
of the linear optical density fitting method Eq. (S4), similar to the OMNO2A
non-linear fitting method Eq. () but with the Ring effect
treated as a pseudo-absorber; cf. Eq. (S5). The red line with open circles in
Fig. shows the difference between the results of this
approach and the OMNO2A results, which appears to be larger than the
difference with the linear fitting method of QDOAS: about
-0.3 × 1015 molec cm-2, almost independent of
latitude.
The SCIAMACHY and GOME-2 NO2 data are retrieved in the fit window
425–450 nm, using a third-degree polynomial. The difference between the OMI
orbit processed with QDOAS in this manner and the OMNO2A data is shown by the
blue line with squares in Fig. . At
+0.2–0.6 × 1015 molec cm-2, the difference is clearly
larger than for the OMNO2A fit window.
In their study to improve the GOME-2 NO2 retrieval,
apply the extended fit window 425–497 nm. The black line with triangles in
Fig. shows that OMNO2A is higher by
0.4–0.9 × 1015 molec cm-2 than applying a linear fit in
this extended fit window.
The NO2 SCD differences in Fig. show a clear
latitudinal variation around latitudes 20∘ S and 20∘ N –
areas of the Pacific Ocean where absorption in liquid water plays a role
(cf. Sect. ) – for the three curves where QDOAS was used
in the linear fitting mode, while for QDOAS's non-linear fitting mode the
differences with OMNO2A are nearly independent of latitude. This may indicate
that the linear fitting method deals differently with the polynomial-like
signature of H2Oliq and/or O3 and/or O2–O2 absorption
(cf. Fig. S6) than the non-linear fitting method, which is possibly due to
interference of the reference spectra with the DOAS polynomial (a few
further remarks regarding this issue are given in Sect. S6).
In summary, the selection of the fit window (and with that the degree of the
polynomial) and the fitting method determines the NO2 fit results,
i.e. there is no “true” NO2 SCD but at most a fit window and fit method
specific slant column value. Judging from the curves in
Fig. , the variability in the fit window and fit method
selection introduces differences in the retrieved NO2 SCD between -0.3
and +0.6 × 1015 molec cm-2 (i.e. up to
0.2 × 1015 molec cm-2 in terms of the NO2 VCD). To
better understand the “true” NO2 SCD, a comparison with measurements
that do not depend on the DOAS technique is needed.
Scatter plots of current data (case 0, top row) and absolute differences
between the current and the updated data (bottom row) of the RMS error (left
column, × 10-4) and NO2 SCD (right column,
× 1015 molec cm-2) as a function of the updated data
(case 4) using the July 2005 average gridded data.
Dashed blue lines show linear fits through the data; the fit and
correlation coefficients are shown in the top-left of each graph.
Reprocessed OMI NO2 data of 2005
All OMI NO2 slant column data of the year 2005 have been reprocessed to
evaluate the consistency of the proposed improvements.
Figure shows the current (case 0) data on the top row and the difference between the
current and update data on the bottom row as a function of the updated (case 4)
data. The linear relationship between
the NO2 SCD of the current and updated retrieval in the top-right panel
shows an offset, reflecting the improved wavelength calibration. The slope of
the linear fit is 1.04, which implies that high NO2 SCD values will
decrease more than low SCDs but not by much. This suggests that the effect
of the updated retrieval settings on high (tropospheric) NO2 SCDs will
be small compared to the overall decrease of the NO2 values.
Figure shows a map of the monthly average
gridded NO2 slant columns of the updated (case 4) data and the
corresponding difference with the current (case 0) data for July 2005. The
RMS error data for the same month are shown in
Fig. . Similar maps of the month of January
2005 are shown in Sect. S7 in the Supplement. In some areas with high
NO2 levels related to pollution, the decrease of the NO2 slant
column is relatively large, such as for the Highveld area in South Africa in
Fig. for July. The average change in the RMS error
shown in the lower panel of Fig. is about
0.33 × 10-4. For clear-sky pixels only (not shown), the decrease of the
RMS is much smaller, namely 0.14 × 10-4 on average, while for cloudy
pixels (not shown) the decrease is much larger: 0.80 × 10-4 on average.
Notably above clouds, the quality of the fit is evidently improved by the
changes made to the OMNO2A retrieval.
Monthly average gridded updated (case 4; top panel) NO2 slant column
data for July 2005 and the corresponding difference with the current (case 0)
data (lower panel).
Section S7 in the Supplement shows monthly average maps for July 2005 similar
to Figs. – of the results
of the other fit parameters.
Monthly average gridded updated (case 4; top panel) RMS error
data for July 2005 and the corresponding difference with the
current (case 0) data (lower panel).
Concluding remarks
The OMI NO2 slant column density retrieval, OMNO2A, lies at the
basis of the stratospheric and tropospheric NO2 vertical column data
products of OMI, notably the Dutch OMI NO2 (DOMINO) and NASA SP data sets. This paper describes important updates for OMNO2A in
order to improve the quality of the OMI NO2 SCD data. The investigation
was triggered by the high bias in OMI stratospheric NO2 columns
w.r.t. other satellite sensors and ground-based measurements as well as the
need to investigate a number of other elements of the OMNO2A processor. The
improvements for the OMNO2A processor are
implementation of the wavelength and viewing angle dependency of the OMI slit
function,
optimisation of the wavelength calibration window based on minimising RMS and
NO2 errors,
an update of the reference spectra of the trace gases included in the
spectral fit,
inclusion of absorption by O2–O2 and H2Oliq to further
reduce the RMS error.
The updates of the wavelength calibration have the effect of removing an
additive offset in the NO2 SCD of
0.85 × 1015 molec cm-2 and reducing the RMS by about
23 % on average. The updates of trace gas reference spectra and the
improved use of the OMI slit function for the convolution of these spectra
lead to a reduction of the NO2 SCD that depends on latitude, mainly
related to the inclusion of O2–O2 absorption, varying from 0.2
to 0.6 × 1015 molec cm-2 (on average
0.35 × 1015 molec cm-2); the RMS is reduced by about
9 % on average.
Absorption by the O2–O2 collision complex increases with solar
zenith angle due to increased light path length and is therefore important at
higher latitudes, and the resulting O2–O2 SCDs have realistic
values. Accounting for absorption by liquid water (H2Oliq) is
particularly important for pixels over clear open waters with low chlorophyll
concentrations and results in marked improvements of the spectral fit and
assures that O3 SCDs in the fit window have physically realistic values.
Inclusion does not deteriorate the spectral fit for other, non-clear water
pixels. The values found for the H2Oliq fit coefficient are physically
meaningful for the areas where absorption in liquid water is relevant.
NO2 SCD retrievals for other satellite and ground-based instruments
employ different spectral fit windows and use different implementations of
the DOAS technique, which leads to small differences in the resulting SCD
values. A short investigation of this using the QDOAS software
shows that the uncertainty in NO2 SCD related to
the choice of the fit window and fit method may be as large as
0.3 × 1015 molec cm-2.
The combination of improvements to the OMNO2A spectral fit lead to an overall
reduction of the NO2 SCD by about
1.2 × 1015 molec cm-2, a reduction of the NO2
fitting error by 0.2–0.3 × 1015 molec cm-2 and a reduction of the
RMS by 24–35 %. The reduction of the SCD is largely an additive offset,
implying that the improvements in OMNO2A will probably affect stratospheric
NO2 most and smaller effects may be expected on tropospheric NO2.
Comparing the updated OMNO2A data with SCIAMACHY data over the Pacific Ocean
shows that the discrepancy between the two instruments is reduced from 1.2
to 0.8 × 1015 molec cm-2. The remaining difference can
be explained largely by the difference expected due to the diurnal cycle of
stratospheric NO2, which is higher by about
0.5 × 1015 molec cm-2 at 13:40 LT (when OMI measures)
than at 09:30 (when SCIAMACHY measures), the different choice of the fitting
window and the low bias of SCIAMACHY relative to other instruments.
The updates to the OMNO2A retrieval systems are sufficient to remove the bias
between the stratospheric NO2 columns from OMI and those from other
satellite and ground-based instruments. A final test of this requires the
conversion of the retrieved SCD to the separate stratospheric and
tropospheric NO2 columns. This issue will be discussed in a forthcoming
study that describes improvements to the data assimilation system of DOMINO,
leading to a new DOMINO v3.0 data set for the entire OMI period. The settings
of the updated OMNO2A processing will be the initial configuration of the
NO2 retrieval for TROPOMI for reasons of consistency
.