The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO₂, CH₄, N₂O, CO and O₂ are measured. CO₂ is constrained with a precision better than 0.25% (1-σ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO₂ column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.1% ± 0.2% low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO₂ measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellites

Blumenstock, T.

Chen, H.

Deutscher, N. M.

Engel, A.

Feist, D. G.

Geibel, M. C.

Gerbig, C.

Gisi, M.

Hase, F.

Katrynski, K.

Kolle, O.

Lavrič, J. V.

Messerschmidt, J.

Notholt, J.

Palm, M.

Ramonet, M.

Rettinger, M.

Schmidt, M.

Sussmann, R.

Toon, G. C.

Truong, F.

Warneke, T.

Wennberg, P. O.

Wunch, D.

Xueref-Remy, I.

English

Caltech Authors - Main

J. Messerschmidt et al.: The IMECC campaign: Results for CO2 7
3.6 Uncertainty discussion
Measurements are affected by three types of error sources:
random effects, known and unknown systematic effects.
Random effects result in a measurement to measurement
variability and can be quantified by the standard deviation.
Known systematic effects should not simply be encompassed
by increasing the estimated uncertainty, according to the
Joint Committee for Guides in Metrology (JCGM, 2008) rec-
ommendations. They rather should be corrected and the un-
certainty in the correction included in the total uncertainty
of the corrected quantity. The total uncertainty is calculated
as the sum in quadrature of random effects and the uncer-
tainty of the corrected known systematic effects. Unknown
systematic effects reveal in comparison to independent mea-
surements and can be corrected against a calibration stan-
dard, such as the WMO standards, the objective of this paper.
3.6.1 Uncertainty of FTS-derived DMFs
FTS measurements are known to be mainly affected by the
following systematic effects. Firstly the a priori profiles can
be wrong due to false estimations of the temperature, pres-
sure or water vapour profiles. Furthermore the volume mix-
ing ratio shape of the a priori profiles can be wrong. Sec-
ondly the sun tracker pointing at the middle of the sun can
be offset. Thirdly the instrumental line shape (ILS) can be
distorted due to shear or angular misalignment of the instru-
ment or field of view (FOV) failure (Wunch et al., 2011).
The calculation of XCO2 by Equation 1 reduces some of the
effects that are common to both gases (solar tracking point-
ing errors, zero level offsets, ILS errors or surface pressure
measurement errors).
Furthermore it is known that the XCO2 exhibit an airmass-
dependency, resulting in 1 % larger XCO2 at low solar
zenith angeles (SZA) than at high SZA. This dependency
is removed in the standard GFIT retrieval by a single em-
pirical correction (Section 3.1). A quantification of realistic
perturbations of the a priori profile, the tracking and the ILS
was done by Wunch et al. (2011). It could be estimated that
the XCO2 in total would be affected by 0.18 % for low SZA
(20◦) and 0.13 % for high SZA (70◦) .
Within the IMECC campaign, potential systematic ef-
fects introduced by the a priori profiles were eliminated
by using the assembled aircraft profiles as a priori profiles
(Section 3.1). Concerning the quality of the solar tracking, a
suitable indicator is the pointing error, which is the deviation
from pointing at the middle of the sun and can be estimated
by the Doppler Shift. The ILS is regularly monitored in all
TCCON FTS instruments (Section 3.1) and misalignments
could further be seen in the fitting residuals by characteristic
artifacts. All FTS instruments and their solar tracker were
optimized prior the IMECC campaign, and hence systematic
effects by the pointing error and the ILS were minimized.
One known source, systematically affecting FTS measure-
ments, was not diminished prior the campaign or is taken
care of in the retrieval. Messerschmidt et al. (2010) showed
that collocated FTS instruments agree within 0.07 %, but
only after correcting for a systematic effect introduced by
a mis-sampling of the internal reference laser provided in the
commercially available FTSs. Briefly, a periodic laser mis-
sampling leads to so called ghosts (artificial spectral lines),
which are mirror images of the original spectral lines. The
influence of the ghosts on the retrieved XCO2 was quanti-
fied as a function of the ghost and parent line intensities,
called the ghost/parent line ratio (GPR). For a typical GPR,
the retrieved XCO2 is affected by about 1 ppm. Therefore,
a correction scheme was introduced for solar measurements
afflicted with ghosts (Messerschmidt et al., 2010). The ef-
fect of the retrieved XCO2 was quantified and this correction
applied to all measurements during the IMECC campaign.
The Messerschmidt et al. (2010) correction scheme does
not predict the sign of the ghosts, which means that it is am-
biguous as to whether the ghosts lead to an over- or an un-
derestimation of the retrieved XCO2 . For three of the FTS in-
struments (BIK, BRE, ORL), this sign was inferred from the
side-by-side measurements detailed by Messerschmidt et al.
(2010). For the Garmisch and Karlsruhe FTS instruments,
the ghosts were minimized prior to the aircraft campaign and
did not introduce a large systematic effect. The Jena instru-
ment could not be corrected prior to the aircraft campaign,
and had significant ghosts, which affected the retrievals. The
results suggest an over-estimation of XCO2 . However, as we
cannot be sure of the sign, we investigate two ’worst-case’
scenarios in calculating the scaling factors for the FTS rel-
ative to the in-situ profile in Section 4. These correspond
to all ghosts (Table 3) leading to an (a) under- and (b) over-
estimation of the retrieved XCO2 . The difference between
these scenarios is used to check the correction of the system-
atic effect introduced by the ghost correction scheme in the
calculation of scaling factors.
One further source lead to systematic effects: Due to poor
weather in Jena and Bremen, not all overpasses could be
carried out at the same time as the FTS data were measured
(BRE_1, JEN_3, JEN_4). To account for a delay of two
hours in all three cases, the expected variation due to
the diurnal CO2 cycle was accounted for as a systematic
effect. At both sites, the magnitude of the diurnal cycle was
estimated from the trend of the FTS measurements on the
same day. The diurnal cycle was calculated for BRE_1 by
the trend of the FTS data taken for a 2 hour time period
prior to the overpass and for JEN_3 and JEN_4 by the
trend of the FTS data measured for a 2.5 hour time period
after the overpass. The trends were estimated with the FTS
data that met the filter criteria introduced in Section 3.1
and extrapolated to the overpass time. On-site in-situ
measurements showed for the extrapolated time period in
Jena a variability of ± 0.5 ppm and no significant trend
that indicate further influence e.g. from local pollution or
8 J. Messerschmidt et al.: The IMECC campaign: Results for CO2
Table 3. Systematic effects due to ghosts and a time delay between
the overpass and FTS measurements and the uncertainty sources
contributing to the total uncertainty of the FTS measurements. The
total uncertainty accounts for the FTS measurements variability dur-
ing the overpasses, an uncertainty in the estimation of the expected
variation due to the diurnal cycle and the uncertainty in the ghost
estimation, according to Messerschmidt et al. (2010).
code systematic uncertainties
effects [ppm] [ppm]
applied
correction of
ghosts time ghosts time overpass total
delay delay variability
BIK_1 -0.27 - 0.05 - 0.12 0.13
BIK_2 -0.27 - 0.05 - 0.13 0.14
BIK_3 -0.27 - 0.05 - 0.19 0.20
BIK_4 -0.27 - 0.05 - 0.19 0.20
BRE_1 +0.31 +0.07 0.06 0.01 0.41 0.41
BRE_2 +0.31 - 0.06 - 0.38 0.39
GAR_1 +0.06 - 0.02 - 0.35 0.35
JEN_1 -1.63 - 0.16 - 0.35 0.39
JEN_2 -1.63 - 0.16 - 0.35 0.39
JEN_3 -1.63 +0.37 0.16 0.03 0.26 0.31
JEN_4 -1.63 +0.30 0.16 0.03 0.26 0.31
KAR_1 -0.12 - 0.04 - 0.35 0.35
ORL_1 +0.38 - 0.08 - 0.33 0.34
ORL_2 +0.38 - 0.08 - 0.34 0.35
ORL_3 +0.38 - 0.08 - 0.40 0.41
ORL_4 +0.38 - 0.08 - 0.38 0.39
changing meteorological conditions. For Bremen no on-site
in-situ measurements exist. The BRE_1, JEN_3, JEN_4
data are not included in the calculation of the calibration
factor, due to the remaining lack of information during the
overpasses, but the results will be discussed in Section 4.2.
Random effects, such as noise and variations in the so-
lar tracker and instrument performance, are quantified by
the measurement to measurement variability during the
overpasses.
The total uncertainty for the FTS data is the sum in quadra-
ture of the contributing standard uncertainties: the standard
deviation about the mean during the overpass, the standard
uncertainty of the ghost estimation and the standard uncer-
tainty of the diurnal cycle estimation. Table 3 summarizes
the magnitude of the systematic corrections, the uncertain-
ties and the total uncertainty for all overpasses.
3.6.2 Uncertainty of the assembled in-situ data
The uncertainty of the assembled in-situ data is derived from
the uncertainty of the aircraft measurements, the uncertain-
ties in extrapolating the profiles and the usage of contempo-
rary profiles (Table 4).
The GFIT a priori CO2 profiles are used to extend the in-
situ data above the tropopause, as explained in Section 3.4.
Thus a typical profile of mean age (Andrews et al., 2001)
above the local tropopause is used to calculate the lag of
stratospheric CO2 values with respect to mean tropospheric
values. Furthermore a decrease of the seasonal cycle with
altitude is taken into account. Seasonally resolved aircraft
measurements during the SPURT project (Engel et al., 2006)
revealed that the seasonal cycle in the lowermost strato-
sphere (i.e. the region of the stratosphere between the local
tropopause and the 380K isentrope) is not only attenuated
with increasing vertical distance to the local tropopause but
is also shifted with respect to the troposphere (Hoor et al.,
2004; Bönisch et al., 2008, 2009; Hintsa et al., 1998). The
seasonal cycle magnitude can be as large as 3 ppm at the
mid latitude tropopause and decreases to about half of that
value at about 50 K potential temperature above the local
tropopause. The amplitude and timing of the seasonal cycle
at the tropopause is captured quite well in the a priori pro-
files with a maximum in May. The variability in this area is,
however, very high, especially when using pressure coordi-
nates. Therefore a conservative uncertainty estimate is used
by assuming that the CO2 seasonal cycle in the lowermost
stratosphere can not be correctly represented and that this
seasonal cycle leads to an additional uncertainty of the CO2
a priori profile of about 2 ppm, that is a typical amplitude
of the seasonal cycle in the lowermost stratosphere. This un-
certainty is independent of contributions from the absolute
uncertainty of the mean age profile, that is estimated to be
about 0.3 ppm (Wunch et al., 2010). The total uncertainty of
the stratospheric CO2 values is thus estimated as the sum in
quadrature and on the order of 2.02 ppm.
For some overpasses, the profiles could not be measured
up to the tropopause. If no contemporary aircraft profile was
available, the upper troposphere was filled with the highest
aircraft measurement; e.g. as clearly seen in Figure A2. The
CO2 variability in the upper troposphere, measured at the
European TCCON sites, is within 2 ppm and applied as un-
certainty for the filling. If a contemporary aircraft profile
was available, it was used to estimate the profile above the
last aircraft measurement (Figure A1,A3, A4). It is assumed
that the profile can therewith be better estimated than by us-
ing the highest aircraft measurement and an uncertainty of
1.5 ppm is assigned.
For the aircraft data, the standard uncertainty provided by
the post-flight analysis at the MPI-BGC’s lab was applied.
The uncertainties given for the mixing ratios contain uncer-
tainties from extension with the lowest aircraft measurement
to the surface pressure, as well as from interpolation across
missing values (e.g. due to instrument calibration periods).
Also included is the statistical uncertainty from sampling
only a limited number of seconds at each pressure interval.
In addition, an uncertainty related to the calibration of the
standard gases (working tanks) against WMO primary gases
J. Messerschmidt et al.: The IMECC campaign: Results for CO2 9
Table 4. Contributing uncertainties to the total uncertainty of the
assembled in-situ data. The total uncertainty is calculated by the
sum in quadrature of the weighted fraction in terms of pressure with
respect to the completed in-situ profile.
Uncertainties contributing to the total uncertainty [ppm]
stratospheric extrapolation 2.02
missing tropospheric values 2.00
usage of contemporary profile 1.50
mean aircraft profile 0.11
is added. The mean standard deviation for the IMECC cam-
paign aircraft profiles is 0.11 ppm. The total uncertainty is
calculated from the sum in quadrature of these contributing
uncertainties weighted by their relative contribution to the
completed profile in terms of pressure.
Due to poor weather conditions a profile was not flown
above the Karlsruhe TCCON site. Aircraft measurements
were, however, recorded during a stop-over 50 km to the
south of the site. The Karlsruhe data are therefore treated
similarly to the other overflights, but because of these
exceptional circumstances, they are not included in the
calculation of the calibration factor. They will be discussed
in Section 4.2.
The resulting uncertainties for the FTS measurements
and for the integrated column-averaged assembled aircraft
CO2 profiles are listed for all overpasses in Table 5.
10 J. Messerschmidt et al.: The IMECC campaign: Results for CO2
Table 5. The IMECC campaign results: The code of each overpass, the type, the solar zenith angle (SZA), the aircraft ceiling/- floor, spiral
range, nearest distance, number of FTS measurements during the overpass, and the column-integrated CO2 abundances measured by in-situ
instrumentations and FTS are given.
code type SZA [◦] aircraft aircraft spiral [km] nearest number of FTS aircraft
(min-max) ceiling [km] floor [m] (ceiling,width) distance [km] FTS data [ppm] [ppm]
BIK_1 descent 56.2-61.1 11.5 500 (5,10) 0 65 378.3± 0.1 382.6 ± 0.1
BIK_2 ascent 56.2-61.1 8 500 (3,5) 0 67 378.3± 0.1 382.5 ± 0.2
BIK_3 descent 66.8-72.4 8 800 (5,8) 0 35 378.1± 0.2 382.5 ± 0.2
BIK_4 ascent 66.8-72.4 10.5 800 (5,10) 0 35 378.1± 0.2 382.5 ± 0.1
BRE_1 descent 58.0-75.5 13 500 (6,10) 0 30 379.1 ± 0.4 383.7 ± 0.1
BRE_2 descent 59.5-62.8 13 500 (10,10) 0 37 378.7 ± 0.4 383.5 ± 0.1
GAR_1 descent 53.9-62.3 12.5 1500 (7,15) 5 19 379.6 ± 0.4 384.1 ± 0.1
JEN_1 descent 59.0-63.8 12.5 800 (7,10) 0 8 379.7 ± 0.4 383.7 ± 0.1
JEN_2 ascent 59.0-63.8 8 800 - 0 8 379.7 ± 0.4 383.8 ± 0.2
JEN_3 descent 59.9-61.7 12.5 500 (9,15) 0 7 380.0 ± 0.3 384.1 ± 0.1
JEN_4 ascent 59.9-61.7 12.5 500 - 0 7 380.0 ± 0.3 384.1 ± 0.1
KAR_1 54.2-64.3 7 200 - 10 26 380.8± 0.4 384.6 ± 0.2
ORL_1 descent 68.9-83.6 11.5 700 (9,15) 30 45 380.1 ± 0.3 384.2 ± 0.1
ORL_2 ascent 68.9-83.6 7 700 (3,5) 0 45 380.0 ± 0.4 384.2 ± 0.2
ORL_3 descent 51.8-52.5 11 700 (8,30) 12 10 380.3 ± 0.4 384.1 ± 0.1
ORL_4 ascent 51.8-52.5 8 700 (5,5) 0 10 380.3 ± 0.4 384.2 ± 0.2


Calibration of TCCON column-averaged CO₂: the first aircraft campaign over European TCCON sites

https://authors.library.caltech.edu/103571/2/acp-11-10765-2011-supplement-1.pdf

Calibration of TCCON column-averaged CO₂: the first aircraft campaign over European TCCON sites

Abstract

Similar works

Full text

Available Versions

Caltech Authors - Main