GIGeoscientific Instrumentation, Methods and Data SystemsGIGeosci. Instrum. Method. Data Syst.2193-0864Copernicus PublicationsGöttingen, Germany10.5194/gi-5-271-2016Fourier transform spectrometer measurements of column CO2 at Sodankylä, FinlandKiviRigelrigel.kivi@fmi.fihttps://orcid.org/0000-0001-8828-2759HeikkinenPauliFinnish Meteorological Institute, Sodankylä, FinlandRigel Kivi (rigel.kivi@fmi.fi)5July20165227127917December201520January20168June201613June2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://gi.copernicus.org/articles/5/271/2016/gi-5-271-2016.htmlThe full text article is available as a PDF file from https://gi.copernicus.org/articles/5/271/2016/gi-5-271-2016.pdf
Fourier transform spectrometer (FTS) observations at Sodankylä, Finland
(67.4∘ N, 26.6∘ E) have been performed
since early 2009. The FTS instrument is participating in the Total Carbon
Column Observing Network (TCCON) and has been optimized to measure
abundances of the key greenhouse gases in the atmosphere. Sodankylä is
the only TCCON station in the Fennoscandia region. Here we report the
measured CO2 time series over a 7-year period (2009–2015) and
provide a description of the FTS system and data processing at
Sodankylä. We find the lowest monthly column CO2 values in August
and the highest monthly values during the February–May season.
Inter-annual variability is the highest in the June–September period, which
correlates with the growing season. During the time period of FTS
measurements from 2009 to 2015, we have observed a 2.2 ± 0.2 ppm
increase per year in column CO2. The monthly mean column CO2
values have exceeded 400 ppm level for the first time in February 2014.
Introduction
Carbon dioxide (CO2) is the most abundant anthropogenic greenhouse gas
in the atmosphere (Hartman et al., 2013). The concentration of CO2
has increased rapidly since the industrial revolution due to the burning of
carbon-based fuels. Precise and accurate measurements of CO2 are
needed in order to better understand the carbon cycle. In addition to the
relatively long term in situ measurements of CO2, ground-based total column
measurements of carbon dioxide have become possible more recently. The
column-averaged, dry-air mole fractions of carbon dioxide (XCO2) have
been measured since the year 2004 by the Total Carbon Column Observing Network
(TCCON) sites, using solar Fourier transform spectrometers (FTSs), operating
in the near-infrared spectral region (Wunch et al., 2011a). The main goal of
the TCCON has been to provide precise and accurate measurements of
XCO2, but also other gases have been retrieved, including CH4, CO,
N2O, H2O, HDO and HF. Compared to the surface in situ measurements,
XCO2 is less affected by changes in the height of the planetary boundary
layer and the spatial sensitivity footprint is larger (Keppel-Aleks et al.,
2011). The accuracy and precision of the XCO2 measurements within TCCON
are better than 0.25 % (Wunch et al., 2011a). The high accuracy and
precision are needed to contribute to the carbon cycle research and
validation of spaceborne measurements. Satellite missions that have already
used the TCCON data include the Orbiting Carbon Observatory-2 (OCO-2; Crisp
et al., 2004); the Greenhouse Gases Observing Satellite (GOSAT; Yokota et
al., 2009) and the SCanning Imaging Absorption spectroMeter for Atmospheric
CHartographY (SCIAMACHY; Bovensmann et al., 1999).
Sodankylä in northern Finland is one of the stations in the TCCON. This
is currently the only TCCON station in the Fennoscandia region. We
established the FTS measurements at Sodankylä in early 2009. Since then,
the XCO2 retrievals have been used in several studies (e.g., Wunch et
al., 2011b; Oshchepkov et al., 2012; Saito et al., 2012; Belikov et al.,
2013; Guerlet et al., 2013; Yoshida et al., 2013; Agustí-Panareda,
2014; Deng et al., 2014; Reuter et al., 2014; Barthlott et al., 2015;
Heymann et al., 2015; Lindqvist et al., 2015; Belikov et al., 2016; Feng et
al., 2016; Inoue et al., 2016; Massart et al., 2016). This paper describes
the instrumentation, measurement procedures and data processing at the
Sodankylä FTS site, corresponding to the data retrieval version GGG2014
(Wunch et al., 2015). The quality-controlled data from May 2009 to
November 2015 have been used here to calculate the average seasonal cycle
and trend of XCO2 over the measurement period.
Instrumentation
The Sodankylä TCCON FTS station is part of the infrastructure of the
Finnish Meteorological Institute's Arctic Research Centre. The FTS is
located at 67.3668∘ N, 26.6310∘ E, 188 m.a.s.l. FTS measurements at Sodankylä are made using a Bruker 125HR FTS
(Bruker Optics, Germany). Since the beginning of the data record, the FTS
instrument has been installed in a two-story observational building. The
interior of the laboratory was rebuilt in late 2008 to mount the FTS
instrument. The instrument is placed on a concrete plate, which is designed
to absorb possible vibration. The solar tracker on the roof of the building
is of type A547N, manufactured by Bruker Optics. The cover of the tracker
was built locally at the institute's workshop.
The FTS instrument is equipped with two room-temperature detectors: an
indium gallium arsenide (InGaAs, covering 4000–11 000 cm-1) and a silicon
diode (Si, covering 9000–15 000 cm-1), which is similar to the other FTS
stations in the TCCON network. The measurements are performed in a vacuum to
improve stability and to reduce water vapor in the system. The system is
evacuated each night to avoid vibration during the solar measurements. The
optical path difference (OPD) is 45 cm and the spectral resolution is
0.02 cm-1; collection time for a single scan is 78 s. Column
abundances of CO2, O2, CH4, H2O, HDO, HF, CO and
N2O are retrieved from the spectra.
The FTS instrument has worked in a fully automated mode since July 2013.
Readings from rain and direct solar radiation sensors, combined with the
automated analysis of weather radar forecast data, determine the start and
cessation of daily measurements. A control system monitors the measurement
quality and automatically reports on error conditions, thus longer
measurement gaps have been minimized. Currently used settings are presented
in Table 1. In addition to the TCCON measurements, we also take longer
wavelength measurements, using a liquid nitrogen cooled indium antimonide
detector (InSb, covering 1800–6000 cm-1). The InSb measurements are
filtered, the pass band is at 2439–3125 cm-1. This filter choice is
designed for profile retrievals of methane and provides a possibility to
compare the mid-infrared and near-infrared retrievals of
CH4. The sequence of measurements is such that after two InGaAs/Si
scans, one InSb scan is taken. To be able to make the solar intensity
variation correction, we have recorded all interferograms in the DC mode.
To guarantee the optimal performance of the instrument, the optical
alignment is checked and adjusted at least once per year. Usually the
alignment is performed in winter, because then the solar measurements are
not possible due to the high-latitude location of the station. We have
applied the alignment procedure developed by Hase and Blumenstock (2001).
The alignment method is based on the inspection of laser fringes through a
telescope. In addition we monitor the instrument line shape (ILS) by taking
HCl reference gas measurements on a monthly basis. The ILS retrievals are
made using the LINEFIT14 software (Hase et al., 2013). Figure 1 presents a
selection of ILS retrievals. The upper panel corresponds to the amplitude of
the modulation and the lower panel to the phase error, both as functions of
optical path difference. Modulation amplitude for a well-aligned FTS should
be in the limits of 5 % loss at maximum optical path difference (Wunch et
al., 2011a). In the case of Sodankylä, the spread of the values of modulation
amplitude is within 3 %, which is very close to the ideal value. The
phase error values are measured as being close to zero (Fig. 1, lower
panel). A small increase in phase error was an indication of temporary
scanner problems in July 2012. In general, the temporal variability of the
modulation efficiency is caused by the scanner wear and slight mechanical
influences, which are related to small variabilities in temperature and
pressure. This level of small disturbances from the ideal value of
modulation efficiency is common to all well-aligned spectrometers (Hase et
al., 2013). Figure 1 shows that the derived modulation efficiency at maximum
OPD has remained relatively stable over time, indicating that the alignment
has been maintained.
Time series of measurements of modulation efficiency: amplitude
(upper panel) and phase errors (lower panel) are shown as a function of
optical path difference.
Measurement settings for the Sodankylä Bruker 125HR FTS
instrument.
Laser board settings and measurements. Ghost-to-parent intensity
ratio (GPR) and the ratio of the spurious signal to primary signal intensity
(SPR) are shown at different scanner velocities. The used scanner velocities
and the corresponding GPR and SPR values are shown in bold.
PeriodLaserLaserPressureGhostFilterVelocityGPR (4150 cm-1)SPRboarddetectorshPaminimizedwavenumberkHz10-410-4kHzcm-1Up to 9 Mar 2010ECL02V010.4–431557.48.110138.220267.710 Mar 2010 to 2 Mar 2011ECL04V010.161059607.50.428.0100.758.1208.28.140338.03 Mar 2011 to presentECL05V020.71059607.50.198.3100.148.4200.568.4401.38.3Data processing and availability
Using the InGaAs detector, XCO2 values are retrieved in two bands,
centered at 6228 and 6348 cm-1. Within TCCON, the retrieval
of XCO2 and other gases is based on the GFIT algorithm as described by
Wunch et al. (2011a). The data processing and analysis scheme is common at
each TCCON site, although some sites may have a slightly different setup of
instrumentation. For example, not all the TCCON stations have the Si
detector available.
XCO2, the column-averaged, dry-air mole fraction of CO2, is defined
as the ratio of CO2 total column to the total column of all gases,
excluding water. The total dry air column can be calculated either from
surface pressure and water vapor column or from oxygen column, assuming the
constant dry-air mole fraction of 20.95 % for O2. The oxygen column
is retrieved from the TCCON FTS spectra and the method via oxygen is adopted
in TCCON. XCO2 is the ratio of CO2 column to O2 column,
XCO2=CO2columnO2column×0.2095.
By calculating the ratio, all errors that affect both columns cancel in the same
way. This improves the repeatability of the XCO2 retrieval.
The multiyear data have been reprocessed using the most recent analysis
software GGG2014 (Wunch et al., 2015). From the point of view of the
historical data homogenization, one of the major improvements in GGG2014
from GGG2012 is the laser sampling error (LSE) correction, which makes use
of the simultaneously measured Si spectra. The LSE correction derives the
laser sampling errors from Si detector measurements and resamples the
interferograms. In our data record, such corrections have been necessary for
measurements taken prior to 3 March 2010. Figure 2 shows the time series of
the LSE derived from the Si spectra at Sodankylä. In an ideal case, the
LSE is small and centered around zero. Errors in the sampling of the
metrology laser have been caused by faulty electronic boards in the Bruker
FTS. These boards were replaced twice in the case of our instrument. The ECL02
board was installed on 10 March 2010, and was replaced a year later (Table 2).
The currently used electronic board (ECL05) has been operational since
3 March 2011. Intermittent fluctuations in LSE from 27 August to
11 November 2012 and again from 6 July to 1 August 2013 can be
explained by scanner problems. The displacement sensor on the scanner
positioning board caused fluctuations in scanner moving speed. The
positioning board was replaced 2 August 2013 and since then the sampling
errors have been minimal.
Laser sampling error (LSE) since 2009. LSE correction is applied
during the retrieval process within GGG2014.
Time series of xAIR. Average xAIR values are shown for 2009–2011 (0.980)
and for 2012–2015 (0.978).
Distribution of FTS measurements per day at Sodankylä during
2009–2015. Criteria for an accepted measurement shown here is solar zenith
angle < 82∘ and solar intensity variation < 5 %.
In total, 123 715 spectra were recorded during the 7-year period,
corresponding to 1022 measurement days.
Time series of XCO2 measurements at Sodankylä since 2009
(upper panel). Each marker indicates a single measurement. Lower panels
correspond to other gases retrieved from the same measurements.
Time series of XCO2 measurements at Sodankylä
since May 2009. Each marker indicates monthly mean. A trend of
2.2 ± 0.2 ppm yr-1 has been observed during 2009–2015.
Average seasonal cycle of XCO2 over Sodankylä, monthly
averages (black dots) and standard deviations (vertical lines). The average
seasonal cycle was calculated after the trend removal.
Another important measure of data quality and instrument performance is
xAIR, the column-averaged, dry-air mole fraction of dry air (Wunch et al.,
2015). xAIR is the ratio of total dry air column, calculated from the
surface pressure (PS) and the measured XH2O, to the total dry air
column, obtained from the measured oxygen column:
xAIR=AIRcolumnO2column×0.2095-XH2O×mH2OmairdryAIRcolumn=PSgair×mairdryNA.mH2O and mairdry are the molecular masses of water vapor and
dry air, NA is Avogadro's constant and gair is
the column-averaged gravitational acceleration. Ideally this ratio should be
1, but typically the xAIR value is little less, around 0.98, in TCCON
measurements, related to errors in the O2 spectroscopy (Washenfelder et
al., 2006). In practice, xAIR is a measure of how well the instrument is
capable of obtaining the oxygen column. Large differences in xAIR values
compared to the network-wide mean are a sign of instrument problems. The
problems may be related to several factors, such as a poor optical
alignment, spectral ghosts or faulty pressure sensor.
The time series of xAIR are shown in Fig. 3. The average xAIR value for
2009–2011 is 0.980 and the average xAir for the time period of 2012–2015 is
0.978. The first 3 years, until 2012, correspond to the original alignment
by Bruker, while the realignment since 2012 was performed using the fringe
method. The method is considered an improvement over the original alignment
(Hase and Blumenstock, 2001; Heikkinen et al., 2012).
The xAIR record shows that the instrument has been stable during its
history. xAIR behaves consistently also during the period of relatively
large sampling errors, because of the resampling included in the GGG2014
processing scheme. This was not the case with the previous version of data
reprocessing system, GGG2012. In the previous data version, the xAIR level
was too low for the given period of measurements. During the first months of
year 2009 we did not have a dichroic beamsplitter installed and therefore we
had no Si measurements. Reprocessing the earliest data, from the time period
6 February 2009–15 May 2009 needs a different approach (Dohe et al., 2013).
Therefore, the data from this time period have not been reprocessed using GGG2014. For
the previous data version (GGG2012) we have made an additive LSE correction
for the given time period, based on the data collected at different scanner
speeds. Without any LSE correction, the xGAS values are too low for these
months by amounts ranging from 0.2 to 1.0 %. The calculated additive
correction for XCO2 is 2.5 ppm. For other gases, the correction is as
follows: XCO 0.86 ppb, XCH4 0.012 ppm, XH20 2.9 ppm and XN2O
2.4 ppb.
The GGG2014 data version in this study covers the time period from 15 May 2009
to 5 November 2015. During these years we have collected 111 825 individual
measurements, which have been spread over 966 days. In addition, 11 890
measurements were made over 56 days during 16 February–15 May 2009, which were
included in data version GGG2012. Thus the total number of measurements has
been 123 715 over 1022 days (Fig. 4). A single measurement was graded as
acceptable if the solar intensity variation during the measurement was less
than 5 % and the solar zenith angle was less than 82∘. Due to the
zenith angle constraint, good measurements are only possible from 8 February
to 11 November each year (268 days), resulting in a gap in winter that is
over 3 months long. On average, there have been 146 measurement days per
year. The main factor that limits the amount of measurements is cloudiness,
though measurement gaps also occur due to technical problems. A 1-month
gap in the measurements was caused by the failure of sampling laser on
20 May 2012; the laser was replaced on 20 June 2012. A slight increase in the
amount of measurements can be observed in 2013 because this was the first
year when the instrument worked in fully automatic mode.
The reprocessed GGG2014 data version of the Sodankylä FTS measurements
is available from the Carbon Dioxide Information Analysis Center (Kivi et
al., 2014).
XCO2 time series and the annual cycle
The XCO2 measurements are presented in Fig. 5 (upper panel),
corresponding to the time period of 2009–2015. All available data are shown,
including version GGG2012 data until 15 May 2009 and the proceeding data
retrieval version GGG2014 data. We have also included time series of other
gases that are retrieved together with the XCO2. The other time series
are for XCH4, XN2O, XCO, XH2O and XHF measurements. The
non-CO2 TCCON measurements from Sodankylä have been previously
published by, e.g., Saito et al. (2012); Belikov et al. (2013); Mielonen et
al. (2013); Yoshida et al. (2013); Saad et al. (2014); Tsuruta et al. (2015);
Dupuy et al. (2016); Inoue et al. (2016).
Over the 7-year time period, the trend of XCO2 is found to be
2.2 ± 0.2 ppm yr-1 (± 1 standard error). In Fig. 6, monthly mean
values are plotted for each month when measurements have been possible.
GGG2014 data version has been used for the trend calculation. The trend is
in broad agreement with earlier studies (e.g., Lindqvist et al., 2015),
though it is based on a longer time period. It is noteworthy that in
February 2014, the monthly mean XCO2 values have 400 ppm level for the
first time, while individual measurements have achieved the 400 ppm level
already in spring 2012 and 2013. Similar to the XCO2, we find a
significant trend in XCH4. In the case of XCH4, the observed increase
has been 7.1 ± 0.8 ppb yr-1.
The average annual cycle of XCO2 is shown in Fig. 7, based on the 7 years
of measurement and the GGG2014 retrieval. The highest values of
XCO2 are obtained in February to May period, before the start of the
growing season. The minimum monthly XCO2 occurs in August due to the
uptake of carbon into the biosphere, which correlates with the period of
plant growth. The inter-annual variability is found to be the smallest in
spring (March–May) and largest in summer and autumn (June–September). The
shape of the annual cycle can be explained by the imbalance between
ecosystem respiration and gross primary production. This is often referred
to as net ecosystem exchange (NEE). At high latitudes a negative NEE is
observed during the growing season, because the gross primary production has
a peak around the summer solstice, while ecosystem respiration has a maximum
later in summer, in correlation with the increase in ground and air
temperature (Lloyd and Taylor, 1994). Based on the TCCON measurements, Wunch
et al. (2013) found that the minima in the XCO2 annual cycle is correlated
with summertime surface temperature anomalies. The amplitude of the column
CO2 seasonal cycle at high latitudes of the Northern Hemisphere is
smaller than the one based on surface measurement (Olsen and Randerson,
2004). Column CO2 seasonal variability can be explained by the
variability in the terrestrial biospheric fluxes (Keppel-Aleks et al.,
2011), while the long-term trend is driven by the fossil fuel emissions
(Hartman et al., 2013). CarbonTracker (Peters et al., 2007) has been widely
used to study the annual cycle of XCO2. It has been shown that
CarbonTracker is able to simulate the seasonal cycle at Sodankylä with
an average model-measurement bias less than 0.4 ppm (Reuter et al., 2014).
Recently the daily forecasts of CO2 have also become available through
Monitoring of Atmospheric Composition and Climate – Interim Implementation
(MACC-II) service at the European Centre for Medium-Range Weather Forecasts
(Agustí-Panareda et al., 2014).
Conclusions and outlook
XCO2 measurements have been made at Sodankylä since early 2009. The
FTS instrument has been relatively stable. Regular instrument alignments and
HCl cell measurements have been performed. The instrument has run in fully
automatic mode since 2013, therefore the temporal data coverage is
relatively good, given the high-latitude conditions at Sodankylä. The
historical data have been reprocessed using the GGG2014 software (Wunch et
al., 2015). The data have been made available via the Carbon Dioxide
Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge,
Tennessee, USA (Kivi et al., 2014). Measurements from other TCCON sites are
also available from the same data center.
Based on the measurements at Sodankylä we find a 2.2 ± 0.2 ppm
increase per year in XCO2 values. In February 2014 the monthly mean
XCO2 values have exceeded 400 ppm level for the first time in the
history of these measurements. The lowest monthly XCO2 values within
the seasonal cycle are found in August and the highest in February–May.
Year-to-year variability is lowest in March–May and highest during the
growing season in June–September.
Relevant to the FTS measurements, we have started with balloon borne AirCore
(Karion et al., 2010) profile measurements of CO2, CH4 and CO at
Sodankylä in September 2013. The balloon measurements have the benefit
of reaching much higher vertical altitudes (up to 30–35 km), compared to the
aircraft in situ measurements. In addition, year-round measurements by AirCore are
possible. The AirCore used in Sodankylä is a 100 m long coiled sampling
tube, with a volume of ≈ 1400 ml (Paul et al., 2016). The sampling
tube is filled during the payload descent and is automatically closed 9 s
after the landing. Gas analysis have been performed by a cavity
ring-down spectrometer (Picarro Inc., CA, model G2401), typically with a
start of the analysis within 2–3 h after each AirCore flight. Total gas
column measured by an AirCore sampling system is directly related to the
World Meteorological Organization in situ trace gas measurement scales.
Therefore, the measured AirCore data can be used to contribute to the TCCON calibration
(Wunch et al., 2010).
Acknowledgements
Financial support from the Academy of Finland through grant no. 140408
and funding through the EU Project GAIA-CLIM is gratefully
acknowledged.Edited by: C. Ménard
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