Introduction
Monitoring of greenhouse gases (GHGs) is a crucial issue in the context of
global climate change. Carbon dioxide (CO2) is one of the key greenhouse
gases and its global annual mean concentration has increased rapidly from 278
to 400 ppm since the preindustrial data of 1750 (WMO greenhouse gas
bulletin, 2016). Radiative forcing due to changes in atmospheric CO2
accounts for approximately 65 % of the total change in radiative forcing
by long-lived GHGs (Ohyama et al., 2015 and reference therein). Human
activities such as burning of fossil fuels and land use change are the
primary drivers of the continuing increase in atmospheric greenhouse gases
and the gases involved in their chemical production (Kiel et al., 2016 and
reference therein). There is a global demand for accurate and precise
long-term measurements of greenhouse gases.
In the field of remote sensing techniques, solar absorption infrared
spectroscopy has been increasingly used to determine changes in atmospheric
constituents. Today, a number of instruments deployed on various platforms
(ground-based and space-borne) have been operated for measuring GHGs such as
CO2. The g-b FTS at the Anmyeondo station has been measuring several
atmospheric GHG and other gases such as CO2, CH4, CO, N2O, and
H2O operated within the framework of the Total Carbon Column Observing
Network (TCCON). XCO2 retrievals from the g-b FTS have been reported at
different TCCON sites (e.g., Ohyama et al., 2009; Deutscher et al., 2010;
Messerschmidt et al., 2010, 2012; Miao et al., 2013; Kivi and Heikkinen,
2016; Velazco et al., 2017). TCCON achieves accuracy and precision in
measuring the column averaged dry air mole fraction of CO2 (XCO2),
of about 0.25 %, or better than 1 ppm (Wunch et al., 2010), which is
essential to retrieve information about sinks and sources, as well as
validating satellite products (Rayner and O'Brien, 2001; Miller et al.,
2007). Precision for XCO2 of 0.1 % can be achieved during clear sky
conditions (Messerschmidt et al., 2010; Deutscher et al., 2010). The network
aims to improve global carbon cycle studies and supply the primary validation
data of different atmospheric trace gases for space-based instruments, e.g.,
the Orbiting Carbon Observatory 2 (OCO-2), the Greenhouse Gases Observing
Satellite (GOSAT, GOSAT-2) (Morino et al., 2011; Frankenberg et al., 2015).
This study is focused on the initial characteristics of XCO2 retrievals
from g-b FTS spectra over the Anmyeondo station, and comparison with in situ
aircraft overflights and the OCO-2 satellite. The FTS spectra have been
processed using the TCCON standard GGG2014 (Wunch et al., 2015) retrieval
software. One of the unique aspects in this work is a new homemade addition
to our g-b FTS instrument that reduces the solar intensity variations from
the 5% maximum allowed in TCCON to less than 2%. This paper presents
an introduction to the instrumentation and measurement site, and provides
initial results and discussion followed by conclusions.
Station and instrumentation
Station description
The g-b FTS observatory was established in 2013 at the Anmyeondo (AMY)
station, located at 36.32∘ N, 126.19∘ E, and 30 m above
sea level. This station is situated on the west coast of the Korean
Peninsula, 180 km SE of Seoul, the capital city of Republic of Korea. Figure 1
displays the Anmyeondo station. It is also a regional GAW (Global
Atmosphere Watch) station that is operated by the Climate Change Monitoring
Network of KMA (Korean Meteorological Administration). The AMY station has
been monitoring various atmospheric parameters such as greenhouse gases,
aerosols, ultraviolet radiation, ozone, and precipitation since 1999. The
total area of the Anmyeondo island is estimated to be ∼ 88 km2
and approximately 1.25 million people reside on the island. Some of the
residents in this area are engaged in agricultural activities. Vegetated
areas consisting of mainly pine trees are located in and around the FTS
observatory. The topographic features of the area are low level hills that are
on average about 100 m above sea level. The minimum temperature in winter
season is on average 2.7 ∘C, and the maximum temperature is about
25.6 ∘C during summer. Average annual precipitation amount is
1155 mm; with snow in winter. The site has been formally designated as a
provisional TCCON site since August 2014. Full acceptance requires
calibration via overflights with WMO-calibrated in situ vertical profiles, as
described in this paper. The AMY Station's TCCON wiki page can be found at:
https://tccon-wiki.Anmyeondo.edu
Anmyeodo (AMY) g-b FTS station.
Photographs of the automated FTS laboratory. The Bruker Solar
Tracker type A547 is mounted in the custom made dome. A servo controlled
solar tracker directs the solar beam through a CaF2 window to the FTS
(125HR) in the laboratory. The server computer is used for data acquisition.
PC1 and PC2 are used for controlling the spectrometer, solar tracker, dome,
camera, pump, GPS satellite time, and humidity sensor.
Single spectrum recorded on 4 October 2014 with a resolution of
0.02 cm-1. A typical example for the spectrum of -XCO2 is shown in
the inset.
Modulation efficiency (a) and phase error (rad) (b) of HCl
measurements from the g-b FTS are displayed in the period from
October 2013 to September 2017. Resolution = 0.02 cm-1,
aperture = 0.8 mm.
G-b FTS instrument
Solar spectra are acquired using a Bruker IFS 125HR spectrometer (Bruker
Optics, Germany) under the guidelines set by TCCON. Currently, our g-b FTS
instrument operation is semi-automated for taking the routine measurements
under clear sky conditions. It is planned to make an FTS operation mode fully
automated in 2018. The solar tracker (A547, Bruker Optics, Germany) is
mounted inside a remotely controlled protective dome. The tracking ranges in
azimuthal and elevation angles are about 0 to 315 and -10 to 85∘,
respectively, while the tracking speed is about 2∘ s-1. The
tracking accuracy of the ±4 min arc is achieved by the Camtracker mode
which centers an image of the sun onto the spectrometer's input field stop.
Under clear sky conditions, the dome is opened and set to an automatic
tracking mode, in which the mirrors are initially moved to the calculated
solar position, then. The Camtracker control is activated in such a way that
the mirrors are finely and continuously controlled to fix the beam onto the
entrance stop of the spectrometer. Figure 2 displays an overview of the
general data acquisition system. This ensures that all spectra are recorded
under clear weather conditions.
The spectrometer is equipped with two room temperature detectors; an
Indium-Gallium-Arsenide (InGaAs) detector, which covers the spectral region
from 3800 to 12 800 cm-1, and Silicon (Si) diode detector
(9000–25 000 cm-1) used in a dual-acquisition mode with a dichroic
optic (Omega Optical, 10 000 cm-1 cut-on). A red longpass filter
(Oriel Instruments 59523; 15 500 cm-1 cut-on) prior to the Si diode
detector blocks visible light, which would otherwise be aliased into the
near-infrared spectral domain. TCCON measurements are routinely recorded at a
maximum optical path difference (OPDmax) of 45 cm leading to a
spectral resolution of 0.02 cm-1 (0.9/max OPD). Two scans, one forward
and one backward, are performed and individual forward–backward
interferograms are recorded. As an example, Fig. 3 shows a single spectrum
recorded on 4 October 2014 with a resolution of 0.02 cm-1. A single
forward-backward scan in one measurement takes about 112 s. Measurement
setting for the Anmyeondo g-b FTS spectrometer of the Bruker 125HR model is
summarized in Table 1. The pressure inside the FTS is kept at 0.1 to 0.2 hPa
with an oil-free vacuum pump to maintain the stability of the system and to
ensure clean and dry conditions.
Measurement setting for the Anmyeondo g-b FTS spectrometer of the
Bruker 125HR model.
Item
Setting
Aperture (field stop)
0.8 mm
Detectors
RT-Si Diode DC,
RT-InGaAs DC
Beamsplitters
CaF2
Scanner velocity
10 kHz
Low pass filter
10 kHz
High folding limit
15798.007
Spectral resolution
0.02 cm-1
Optical path difference
45 cm
Acquisition mode
Single sided, forward backward
Sample scan
2 scans, forward, backward
Sample scan time
∼ 110 s
Characterization of FTS-instrumental line shapes
For the accurate retrieval of total column amounts of the species of
interest, a good alignment of the g-b FTS is essential. The instrument line
shape (ILS) retrieved from the regular HCl cell measurements is an important
indicator of the status of the FTS's alignment (Hase et al., 1999). The
analyses of the measurements were performed using a spectrum fitting
algorithm (LINEFIT14 software) (Hase et al., 2013). In Fig. 4 we show time
series of the modulation efficiency (Fig. 4a) and phase error (rad) (Fig. 4b)
from the HCl cell measurement in the period of October 2013 to September 2017
using a tungsten lamp as light source. Modulation amplitudes for
TCCON-acceptable alignment should be within 5 % of the ideal case
(100 %) at the maximum optical path difference (Wunch et al., 2011). In
our g-b FTS measurements, it is found that the maximum loss of modulation
efficiency is within 1 %, close to the ideal value. The phase errors are
less than ± 0.0001 rad. Hase et al. (2013) reported that this level of
small disturbances from the ideal value of the modulation efficiency is
common to all well-aligned instruments. This result confirmed that the g-b
FTS instrument is well aligned and has remained stable during the whole
operation period.
We also confirmed that the ILS was not affected by the variable aperture
(OASIS) during the operation of this system (see Sect. 2.5). The modulation
efficiency and phase error were estimated to be 99.98 % and 0.0001 rad.
Sun et al. (2017) reported the detailed characteristics of the ILS with
respect to applications of different optical attenuators to FTIR
spectrometers within the TCCON and NDACC networks. They used both lamp and
sun as light sources for the cell measurements, which were conducted after
the insertion of five different attenuators in front of and behind the
interferometer.
Data processing
Using the TCCON standard retrieval strategy, we have derived the
column-averaged dry-air mole fractions CO2 (XCO2) and other
atmospheric gases (O2, CO, CH4, N2O, and H2O) using the
GFIT algorithm and software. The spectral windows used for the retrieval of
CO2 and O2 are given in Table 2. The TCCON standard GGG2014
(version 4.8.6) retrieval software was used to obtain the abundance of the
species from FTS spectra (Wunch et al., 2015). XCO2 is derived from the
ratio of retrieved CO2 column to retrieved O2 column,
XCO2=CO2columnO2column×0.2095.
Computing the ratio using Eq. (1) minimizes systematic and correlated errors
such as errors in solar zenith angle pointing error, surface pressure, and
instrumental line shape that may exist in the retrieved CO2 and O2
columns (Washenfelder et al., 2006; Messerschmidt et al., 2012). Figure 5a
depicts the time series of laser sampling error (LSE) obtained from InGaAs
spectra at the Anmyeondo FTS station in the measurement period of
February 2014 to December 2016. LSE is due to inaccuracies in the laser
sample timing, which have been reduced to acceptable levels by the instrument
manufacturer. In the AMY FTS, the LSE is small and centered around zero.
Slightly large LSE values were shown on 10 March 2014 (see Fig. 5a). On this
date, we conducted the laser adjustment in FTS.
Time series of LSE (a) and Xair (b)
from the g-b FTS during 2014–2017 is shown. Each marker represents a single
measurement.
Spectral windows used for the retrievals of the columns of CO2
and O2.
Gas
Center of spectral
Width
Interfering
window (cm-1)
(cm-1)
gas
O2
7885.0
240.0
H2O, HF, CO2
CO2
6220.0
80.0
H2O, HDO, CH4
CO2
6339.5
85.0
H2O, HDO
Summary of the column averaged dry-air mole fractions
obtained during the inter-comparison between the in situ instrument on board
the aircrafts and the g-b FTS at the Anmyeondo station. A and D represent
ascending and descending, respectively. Note that FTS values given below are
without TCCON common scale factor and FTS column averaging kernels are
applied to the aircraft data.
Date of measurements
Aircraft
Aircraft
(hours in KST)
NIMS
g-b FTS
NIMS
g-b FTS
XCO2 (ppm)
XCO2 (ppm)
XCH4 (ppm)
XCH4 (ppm)
2017-10-29
09:59:16–10:31:08 (A)
409.152
404.242
1.8900
1.8460
10:31:09–11:03:24 (D)
409.336
403.877
1.8854
1.8454
12:58:58–13:37:07 (A)
407.011
401.051
1.8562
1.8265
13:37:07–14:19:40 (D) 406.898
400.537
1.8720
1.8249
2017-11-12
11:12:20–11:38:01 (A) 406.541
401.839
1.8513
1.8221
11:38:02–12:13:00 (D) 406.839
401.930
1.8512
1.8220
14:14:46–14:45:55 (A) 406.517
401.592
1.8479
1.8201
14:45:56–15:23:47 (D) 407.628
401.473
1.8504
1.8191
Mean ± SD
407.491 ± 1.137
402.068 ± 1.311
1.8630 ± 0.0170
1.8283 ± 0.011
KORUS
TCCON
KORUS
TCCON
2016-05-22
405.80 ± 0.42
401.91 ± 0.57
1.8641 ± 0.0132
1.8100 ± 0.002
G-b FTS XCO2 (a) and XCH4 (b) values
as function of time in KST (Korean Standard time, UTC+9) taken 23 October 2017
with OASIS system on (operating) and off (without operating) positions
are shown. Each marker represents a single measurement.
Xair is the ratio of atmospheric pressure to total column
O2, scaled such that for a perfect measurement Xair=1.0.
Xair is a useful indicator of the quality of measurements and the
instrument performance (Wunch et al., 2015). Due to spectroscopic limitations
there is a TCCON wide bias (Xair ∼ 0.98) and small solar
zenith angle (SZA) dependence. The retrieval of Xair deviating
more than 1 % from the TCCON-wide mean value of 0.98 would suggest a
systematic error. The time series of Xair is shown in the bottom
panel of Fig. 5. The Xair record reveals that the instrument
has been stable during the measurement period. It shows that the values of
Xair fluctuate between 0.974 and 0.985, and the mean value is
0.982 with a standard deviation of 0.0015 in which the scatter for
Xair is about 0.15 %. The low variability in time series of
Xair indicates the stability of the measurements.
Operational Automatic System for the Intensity of Sunray (OASIS)
effect on the retrieval results
The OASIS system was developed for improving the quality of the spectra
recorded by the spectrometer by maintaining a constant signal level. OASIS is
beneficial for minimizing the variability that may be induced in the spectra
due to intensity fluctuations of the incoming solar radiation that reaches
the instrument. The main function of the OASIS is to control an aperture
diameter in the parallel-inlet beam to the interferometer. This aperture is
placed inside the OASIS system, in the parallel input solar beam external to
the FTS. The fundamental purpose of this system is to optimize the
measurement of solar spectra by reducing the effect of the fluctuations of
the intensity of the incoming light due to changes in thin clouds along the
line of sight over the measurement site. The maximum threshold value of the
solar intensity variation (SIV) is 5 %, the TCCON standard value (Ohyama
et al., 2015). This value has been reduced to ≤ 2 % in our case by
introducing the OASIS system to our g-b FTS since December 2014.
NIMS CRDS instrument on board the King Air 90C.
Typical flight path (a), CO2 (b),
and CH4 (c) VMR profiles during ascent and descent of
the aircraft over Anmyeondo on 29 October 2017 are shown.
The comparisons of XCO2 and XCH4 between the aircraft
observation and g-b FTS data over Anmyeondo station are shown. The blue
square represents the aircraft campaign conducted by KORUS-AQ
(May 2016), whereas the green square indicates the aircraft campaign
operated by NIMS (2017). Note that FTS values shown in the figure are after
removing TCCON common scale factor.
In order to assess the impact of the OASIS system on the retrieval results of
XCO2 and XCH4, we have conducted experiments on recording alternate
FTS spectra with and without operation of this system under clear sky
conditions. As an example, Fig. 6 depicts the retrieval results of XCO2
(Fig. 6a) and XCH4 (Fig. 6b) as a function of time (KST, UTC+9), taken
23 November 2017 with OASIS on (blue) and off (red) positions. Mean
differences of 0.12 ppm for XCO2 and 7.0 × 10-4 ppm for
XCH4 were found between OASIS on and off position (i.e., with and
without operating of OASIS system). This suggests that the impact of OASIS
system on the retrieval is negligible.
Time series of XCO2, XCO, and XCH4 from top to
bottom panels (a–c), respectively in the period between February 2014 and
November 2017. Each marker indicates a single retrieval. Fitting
curves (red solid lines) are also displayed.
Aircraft observation campaigns over Anmyeondo station
Aircraft instrumentation
In this section, we present a comparison between aircraft in situ
observations and g-b FTS column measurements over the Anmyeondo station. In
situ profiles were conducted over Anmyeondo station by the National Institute
of Meteorological Sciences (King Air C90) and as part of the KORUS-AQ
campaign from NASA's DC8
(https://www-air.larc.nasa.gov/missinns/korus-aq). For the NIMS
profiles, the flight take-off and landing was carried out from Hanseo
University which is approximately 5 km away from the Anmyeondo FTS station.
The aircraft was equipped with a Wavelength Scanned Cavity Ring Down
Spectrometer (CRDS; Picarro, G2401-m), (see Fig. 7) providing mixing ratio
data recorded at 0.3 Hz intervals. The position of the aircraft was monitored
by GPS and information on the outside temperature, static pressure, and
ground speed was provided by instruments carried on the plane. The
temperature and pressure of the gas sample have to be tightly controlled at
45∘ and 140 Torr in the CRDS, which leads to highly stable
spectroscopic features (Chen et al., 2010). Any deviations from these values
cause a reduction of the instrument's precision. Data recorded beyond the
range of variations in cavity pressure and temperature were discarded in this
analysis. Variance of the cavity pressure and temperature during flight
results in variance in the CO2 and CH4 mixing ratios. The Picarro
CRDS instrument has been regularly calibrated with respect to the standard
gases within the error range recommended by the World Meteorological
Organization. Measurements were made in wet air, and dry air mixing ratios
were derived following the method described in Chen et al. (2010). Water was
measured and its effect was accounted for in the column integration of
CO2 and CH4
On NASA's DC8, CO2 was measured by the Atmospheric Vertical Observations
of CO2 in the Earth's troposphere (AVOCET) instrument, a non-dispersive
IR spectrometer (Vay et al., 2009) with an uncertainty of 0.25 ppm, CH4
was measured by the Differential Absorption of CO Measurement (DACOM)
instrument, a mid-IR absorption sensor (Sachse et al., 1987) with an accuracy
of 1 % and a precision of 1 ppb. Both instruments were calibrated
in-flight with standard gases traceable to the respective World
Meteorological scales. The aircraft static pressure and altitude were
recorded via a pressure transducer and radar altimeter, respectively,
recorded by the aircraft data system. As with the NIMS profiles, the vertical
profiles of CO2 and CH4 mixing ratio were obtained during a
downward flight centered on the Anmyeondo.
Aircraft CO2 and CH4 data
The NIMS vertical profiles of CO2 and CH4 mixing ratio were
obtained during a downward spiral flight centered over the Anmyeondo FTS
station, on 29 October and 12 November 2017. As an example, the flight
trajectory is shown in the left panel of Fig. 8 while the profiles of
CO2 and CH4 from flight during the ascent and descent on
29 October 2017 are depicted in the middle and right panels of Fig. 8,
respectively. All flights were performed under clear sky conditions. The
campaign was performed for 2 h on both days. Specifically, the respective
measurements were taken from 11:00:37 to 12:03:25 KST (UTC+9) and from
13:58:58 to 15:19:40 KST on 29 October 2017 and similarly from 11:12:20 to
12:13:00 KST and from 14:14:46 to 15:14:46 KST on 12 November 2017. The
altitude range of the aircraft measurements was limited to approximately 0.1
to a 9.1 km. We constructed the complete CO2 and CH4 profiles in a
similar way as performed by Deutscher et al. (2010), Miyamoto et al. (2013),
and Ohyama et al. (2015).
(a) shows the time series of FTS XCO2 and in situ
tower CO2 on monthly mean basis, whereas (b) depicts annual
cycle (2014–2016).
Time series of daily averaged XCO2 retrieval from Anmyeondo
FTS and Saga FTS in the period of February 2014 to November 2017 is
depicted.
For both CO2 and CH4 profiles, we have used in situ surface data
(AMY GAW station) to complement the aircraft profiles close to surface level,
and above the aircraft ceiling, the mole fractions throughout the altitude
range between the uppermost aircraft and the tropopause is assumed to be the
same as at the highest aircraft measurement level because of lack of data.
This extrapolation produces the largest uncertainty in the in situ column
estimate. For this analysis, the tropopause height was derived from NOAA
National Centers for Environmental Prediction/National Center for Atmospheric
Research Reanalysis datasets which are provided in 6 h intervals (00:00,
06:00, 12:00, and 18:00 UTC) with a horizontal resolution of 2.5 by
2.5∘. The measurements of surface pressure were available at the FTS
station, which we have used for calculating XCO2 and XCH4. Above
the tropopause height, GFIT apriori profiles were utilized to extrapolate the
aircraft profile. Eventually, the completed aircraft profiles based on those
assumptions were transformed into a total column XCO2 and XCH4 by
pressure weighting functions. For this comparison, we considered only the FTS
averaged XCO2 and XCH4 retrieval values for the corresponding
aircraft measurement time. Details about the aircraft XCO2 and XCH4
values during ascending and descending aircraft flight duration and the
corresponding FTS averaged XCO2 and XCH4 retrieval values are also
provided in Table 3. Note that the vertically resolved FTS column-averaging
kernels were taken into account for smoothing the aircraft profiles. The
XCO2 and XCH4 for the aircraft in situ profile weighted by the
column averaging kernel a (Rodgers and Connor, 2003) is computed as follows:
Xin-situ=Xa+∑jhjaj(tin-situ-ta)j,
where Xa is the column-averaged dry air mole fraction for the
a priori profile ta (CO2 or CH4), tin-situ
is the aircraft profile and hj is the pressure weighting function.
(a) The time series of XCO2 from the g-b FTS (blue
squares) and OCO-2 (red squares) over the Anmyeondo station from February 2014
to November 2017 are shown. (b) The linear regression curve
between FTS and OCO-2 is shown. All results are given on a daily median
basis.
We estimated the uncertainty of the XCO2 and XCH4 columns derived
from the extended aircraft profiles by assigning uncertainties. Uncertainty
at the surface was assumed to be same as the uncertainty in the lowest
measurements. For the stratosphere, we used the method suggested by Wunch et
al. (2010). This method shifts the stratospheric values up and down by 1 km
to calculate the difference in the total column, which is used as an estimate
of the uncertainty in the location of the tropopause and therefore for the
stratospheric contribution. We estimated the stratospheric errors in aircraft
integrated amount of XCO2 and XCH4 by shifting the apriori profile
by 1 km (Ohyama et al., 2015). For KORUS-AQ, it was found to be 0.42 ppm for
XCO2 and 13.26 ppb for XCH4.
For NASA's DC8 measurements, the in situ profiles covered the altitude range
of approximately 0.17 to 9.0 km, in situ surface data were utilized near the
surface to complement the aircraft profiles and extended the aircraft ceiling
point of measurements to the tropopause which is estimated by NCEP to be at
139.0 hPa. Figure 9 illustrates the results of XCO2 and XCH4
comparisons between the aircraft observation and TCCON site data. In this
plot, blue represents the KORUS-AQ campaign, whereas green indicates the NIMS
campaign. KORUS-AQ data lie on the best line which is derived using TCCON
stations where aircraft profiles are available. This shows that TCCON
Anmyeondo data is consistent with other TCCON stations.
Comparison with OCO-2 measurements
The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first Earth-orbiting
satellite dedicated to greenhouse gas measurement, it was successfully
launched on 2 July 2014 into low-Earth orbit. It is devoted to observing
atmospheric carbon dioxide (CO2) to provide improved insight into the
carbon cycle. The primary mission is to measure carbon dioxide with high
precision and accuracy in order to characterize its sources and sinks at
different spatial and temporal scales (Boland et al., 2009; Crisp, 2008,
2015). The instrument measures the near infrared spectra (NIR) of sunlight
reflected off the Earth's surface. Atmospheric abundances of carbon dioxide
and related atmospheric parameters are retrieved from the spectra in nadir,
sun glint, and target modes. Detailed information about the instrument is
available in, for example, Connor et al., 2008; and O'Dell et al., 2012. In this
work, we used the OCO-2 version 7Br bias corrected data. The comparisons are
discussed in Sect. 3.3.
Annual mean of XCO2, XCO, and XCH4 from Anmyeondo g-b FTS
from February 2014 to November 2017.
Annual mean ± standard deviation
Gases
2014
2015
2016
2017
XCO2 (ppm)
396.91 ± 2.55
399.32 ± 2.96
402.97 ± 2.74
406.04 ± 2.38
XCO (ppb)
99.42 ± 14.71
102.73 ± 14.91
105.39 ± 10.68
100.14 ± 10.3
XCH4 (ppm)
1.837 ± 0.014
1.844 ± 0.015
1.864 ± 0.015
1.859 ± 0.013
Results and discussion
Time series of g-b FTS XCO2, seasonal and annual cycle
The time series of XCO2 along with retrievals of other trace gases such
as XCO and XCH4 from g-b FTS is presented in Fig. 10a–c for
the period from February 2014 to November 2017. In these time series plots,
each marker represents a single retrieval, and the fitting curves of the
retrieved values are also depicted (red solid line). We show the seasonal
cycle of XCO2, XCO, and XCH4 in the time series using a fitting
procedure described by Thoning et al. (1989). Standard deviations of the
differences between the retrieved values and the fitting curves are
1.64 ppm, 11.34 and 10.1 ppb for XCO2, XCO, and XCH4,
respectively. It is evident that all species have a seasonal cycle feature.
Year to year variability of XCO2 is highest in spring and lowest during
the growing season in June to September. Moreover, the behavior of the
seasonal cycle of XCO2 at our site was compared with that of XCO2
at Saga, Japan, which is discussed in a later section. The atmospheric
increase of XCO2 from 2015 to 2016 was 3.65 ppm, which is larger than
the increase from 2014 to 2015. For the case of XCH4, its increase from
2015 to 2016 was 0.02 ppm, which is higher than the increase from 2014 to
2015, whereas in XCO the rate of increment from year to year was found to be
slightly decreased (see Table 4).
The seasonal and annual cycles of XCO2 derived from the g-b FTS were
compared with in situ tower observations of CO2 over the Anmyeondo
station, which are presented in Fig. 11. Regarding in situ data, samples were
collected using flasks and analyzed using non-dispersive infrared (NDIR)
spectroscopy at the altitude of 77 m above sea level (details about in situ
data are available at http://ds.data.jma.go.jp/jmd/wdcgg/). Nearly
97 % of in situ data in Fig. 11 were taken during day time between
04:00–08:40 UTC (13:00–17:40 Korean Standard Time, KST) so that the early
morning and night time enhancements of CO2 were mostly excluded. In situ
CO2 monthly means are generated by first averaging all valid event
measurements with a unique sample date and time. The values are then
extracted at weekly intervals from a smooth curve (Thoning et al., 1989)
fitted to the averaged data and then these weekly values are averaged for
each month. As can be seen in Fig. 10, the overall patterns of seasonal and
annual cycle of FTS XCO2 tend to be similar with those of in situ tower
CO2.
Comparison of Anmyeondo XCO2 with nearby TCCON station
In Fig. 12, we present the comparison of our FTS XCO2 data with a
similar ground-based high-resolution TCCON FTS observation at Saga station
(33.26∘ N, 130.29∘ E) in Japan, which is the closest TCCON
station to our site. Among nearby TCCON stations, Rikubetsu, Tsukuba, and
Saga are located in Japan (Morino et al., 2011; Ohyama et al., 2009, 2015)
and Hefei is located in China (Wang et al., 2017). To demonstrate the
comparison between them, we have shown the daily averaged XCO2 of two
stations during the period of 2014 to 2017 in Fig. 12. As can be seen,
variations of XCO2 at the Saga station agreed well with Anmyeondo
station. The daily averaged XCO2 revealed the same seasonal cycle as
that of our station. The lowest XCO2 appeared in late summer (August and
September), and the highest value was in spring (April).
Ohyama et al. (2015) studied the time series of XCO2 at Saga, Japan
during the period from July 2011 to December 2014. They showed seasonal and
interannual variations. The peak-to-peak seasonal amplitude of XCO2 was
6.9 ppm over Saga during July 2011 and December 2014, with a seasonal
maximum and minimum in the average seasonal cycle during May and September,
respectively. In recent findings of Wang et al. (2017), the g-b FTS temporal
distributions of XCO2 at Hefei, China were reported. The FTS
observations in 2014 to 2016 had a clear and similar seasonal cycle, i.e.,
XCO2 reaches a minimum in late summer, and then slowly increases to the
highest value in spring. The daily average of XCO2 ranges from
392.33 ± 0.86 to 411.62 ± 0.90 ppm, and the monthly average
value shows a seasonal amplitude of 8.31 and 13.56 ppm from 2014 to 2015 and
from 2015 to 2016, respectively. The seasonal cycle was mainly driven by
large scale (hemispheric) biosphere–atmosphere exchange. Butz et al. (2011)
reported that the observations from GOSAT and the co-located ground-based
measurements agreed well in capturing the seasonal cycle of XCO2 with
the late summer minimum and the spring maximum for four TCCON stations
(Bialystok, Orleans, Park Falls, and Lamont) in the Northern Hemisphere. We
infer that the variation of XCO2 over Anmyeondo station is in harmony
with the variation pattern in mid-latitude Northern Hemisphere.
Comparison of XCO2 between the g-b FTS and OCO-2
In this section, we present a comparison of XCO2 between the g-b FTS and
OCO-2 version 7Br data (bias corrected data) over Anmyeondo station during
the period between 2014 and 2017. For making a direct comparison of the g-b
FTS measurements against OCO-2, we applied the spatial coincidence criteria
for the OCO-2 data within 3∘ latitude/longitude of the FTS station,
as well as setting up a time window of 3 h (maximum 3 h mismatch between
satellite and g-b FTS observations). Based on the coincidence criteria, we
obtained 13 coincident measurements, which were not sufficient to infer a
robust conclusion, but do provide a preliminary result. The comparison of the
time series of XCO2 concentrations derived from the g-b FTS and OCO-2 on
daily median basis is demonstrated during the measurement period between 2014
and 2017, depicted in Fig. 13. As can be seen in the plot, the g-b FTS
measurement exhibits some gaps which occurred due to bad weather conditions,
instrument failures, and absences of an instrument operator. In the present
analysis, the XCO2 concentrations from FTS were considered only when
retrieval error was below 1.50 ppm (not shown), which is the sum of all
error components such as laser sampling error, zero level offsets, ILS error,
smoothing error, atmospheric a-priori temperature, atmospheric a-priori
pressure, surface pressure, and random noise. Wunch et al. (2016) reported
that the comparison of XCO2 derived from the OCO-2 version 7Br data
against co-located ground-based TCCON data that indicates the median
differences between the OCO-2 and TCCON data were less than 0.50 ppm, and
corresponding RMS differences of less than 1.50 ppm. The overall results of
our comparisons were comparable with the report of Wunch et al. (2016). The
OCO-2 product of XCO2 was biased (satellite minus g-b FTS) with respect
to the g-b FTS, which was slightly higher by 0.18 ppm with a standard
deviation of 1.19 ppm, a corresponding RMS difference of 1.16 ppm. This
bias could be attributed to the instrument uncertainty. In addition to that,
we also obtained a strong correlation between the two datasets, which was
quantified as a correlation coefficient of 0.94 (see Table 5 and Fig. 13).
Summary of the statistics of XCO2 comparisons between OCO-2 and
the g-b FTS from 2014 to 2017. N – coincident number of data,
R – Pearson correlation coefficient, RMS – root mean squares differences.
N
Mean absolute
Mean relative
R
RMS
diff. (ppm)
diff (%)
(ppm)
13
0.18 ± 1.19
0.04 ± 0.29
0.94
1.16
Seasonal mean and standard deviations of XCO2 from the g-b FTS
and OCO-2 in the period between 2014 and 2016 are given below.
Season
g-b FTS XCO2
OCO-2 XCO2
mean ± SD (ppm)
mean ± SD (ppm)
Winter
401.52 ± 0.85
402.67 ± 2.67
Spring
402.72 ± 2.79
403.96 ± 2.77
Summer
396.92 ± 3.28
399.68 ± 3.77
Autumn
398.01 ± 2.83
398.48 ± 2.41
Both measurements capture the seasonal variability of XCO2. As can be
seen clearly from the temporal distribution of FTS XCO2, the maximum and
minimum values are discernible in spring and late summer seasons,
respectively. The mean values in spring and summer were 402.72 and
396.92 ppm, respectively (see Table 6). This is because the seasonal
variation of XCO2 is most likely to be controlled by the imbalance of
the terrestrial ecosystem exchange, and this could explain the larger
XCO2 values in the northern hemisphere in late April (Schneising et al.,
2008, and references therein). The minimum value of XCO2 occurs in
August, which is most likely due to uptake of carbon into the biosphere
associated with the period of plant growth. Furthermore, both instruments
showed high standard deviations during summer, about 3.28 ppm in FTS and
3.77 ppm in OCO-2, and this suggests that the variability reflects strong
sources and sink signals.
Conclusions
Monitoring of greenhouse gases is an essential issue in the context of
global climate change. Accurate and precise continuous long-term
measurements of greenhouse gases (GHGs) are substantial for investigating
their sources and sinks. Today, several remote sensing instruments operated
on different platforms are dedicated for measuring GHGs. Total column
measurements of greenhouse gases such as XCO2, XCH4, XH2O,
XN2O have been made using the g-b FTS at the Anmyeondo station since
2013. In this work, we focused on the measurements taken during the period
of February 2014 to November 2017. The instrument has been operated in a
semi-automated mode since then. The FTS instrument has been stable during
the whole measurement period. Regular instrument alignment checks using the
HCl cell measurements are performed. The TCCON standard GGG2014 retrieval
software was used to retrieve XCO2, XCO, and others GHG gases from the
g-b FTS spectra.
In this work, the g-b FTS retrieval of XCO2 and XCH4 were compared
with aircraft measurements that were conducted over Anmyeondo station on
22 May 2016, 29 October and 12 November 2017. The mean absolute difference
between FTS and aircraft XCO2 were found to be
-1.109 ± 0.802 ppm, corresponding to a mean relative difference of
-0.273 ± 0.198 % for XCO2, while the mean absolute
difference for XCH4 is 0.007 ± 0.0096 ppm, corresponding to a
mean relative difference of 0.377 ± 0.518 %. These differences
appeared in both species and were consistent with the combined instrument
errors. The preliminary comparison results of XCO2 between FTS and OCO-2
were also presented over the Anmyeondo station. The mean absolute difference
of XCO2 between FTS and OCO-2 was calculated on daily median basis and
it was estimated to be 0.18 ppm with a standard deviation of 0.19 with
respect to the g-b FTS. This bias could be attributed to instrument
uncertainty. Based on the seasonal cycle comparison, both the g-b FTS and
OCO-2 showed a consistent pattern in capturing the seasonal variability of
XCO2, with maximum in spring and minimum in summer.