CARVE: L2 Column Gas and Uncertainty from Airborne FTS, Alaska, 2012-2015

This data set provides total vertical column O2, CO2, CH4, CO, and H2O, as well as dry-air columns of CO2, CH4, CO, and H2O from airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data represent the Level 2 Quick Retrieval (L2QR) data product collected using the CARVE Fourier Transform Spectrometer (FTS). Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.

There are 172 files in NetCDF file format (*.nc) included in this data set. There are also 172 *.zip files included as supporting information. These zip files contain quick-look plots (48 *.png files per zip) corresponding to each netcdf file.

Project: Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE)

The Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) is a NASA Earth Ventures (EV-1) investigation designed to quantify correlations between atmospheric and surface state variables for Alaskan terrestrial ecosystems through intensive seasonal aircraft campaigns, ground-based observations, and analysis sustained over a 5-year mission. CARVE collected detailed measurements of greenhouse gases on local to regional scales in the Alaskan Arctic and demonstrated new remote sensing and improved modeling capabilities to quantify Arctic carbon fluxes and carbon cycle-climate processes. CARVE science fills a critical gap in Earth science knowledge and satisfies high priority objectives across NASA’s Carbon Cycle and Ecosystems, Atmospheric Composition, and Climate Variability & Change focus areas as well as the Air Quality and Ecosystems elements of the Applied Sciences program. CARVE data also complements and enhances the science return from current NASA and non-NASA sensors.

Related Data:

A full list of CARVE data products is available at: https://carve.ornl.gov/dataproducts.html

Spatial Coverage: CARVE flights over the Alaskan and Canadian Arctic 

Spatial Resolution: Point measurements 

Temporal Coverage: 20120523 - 20151112

Temporal Resolution: The instruments were deployed on periodic flights during the growing season (approx. March - November)

Study Area (coordinates in decimal degrees)

Site	Westernmost Longitude	Easternmost Longitude	Northernmost Latitude	Southernmost Latitude
Alaska and Canadian Arctic	-167.646	-131.768	71.4259	58.8879

 

Data File Information

There are 172 files in NetCDF file format (*.nc) included in this data set. There are also 172 *.zip files included as supporting or companion files. These zip files contain quick-look plots (48 *.png per zip) corresponding to each netcdf file.

All science data are stored in NetCDF (*.nc) version 4 file format. Each file provides total vertical column measurements of CO₂, CO, CH₄, H₂O, and O₂ as well as dry air column measurements of CO₂, CO, CH₄, and H₂O acquired during a single flight. Total vertical column is defined as vertical molecular column density integrated between surface and top-of-atmosphere at the location of the aircraft. The data product also includes geolocation information, retrieval diagnostics, and auxiliary data for improved quality control. The reported total and dry-air column values for all gases are still preliminary. They are as yet unvalidated and should be used with extreme caution in science investigations.

Missing values are set to -9.9E30. 

Table 1. CARVE file naming convention. Example file name: carve_FTS_L2QR_b23_20120523_20150410124144.nc

Name element	Example value	Units
Project name	carve
Instrument	FTS
Processing level	L2QR
Build ID	b23
Flight date	20120523	yyyymmdd
Processing date and time	20150410124144	yyyymmddhhmmss

 

Data Variables 

Each file contains 5 variable groups: geolocation, science_products, retrieval_diagnostic, dads, and auxiliary_data. Each variable contains data formatted to fit one of 11 dimensions listed in Table 2. The variables contained within each variable group are described in Tables 3 to 7.

Table 2. Variable dimensions in the NetCDF files

Dimension name	Description
num_times	Number of co-added observations
num_times_1s	Number of 1-second observations
num_coadd	Number of 1s spectra in each co-added observation
num_bands	Number of CARVE FTS bands
num_polarization	Number of polarization observations
num_vertex	Number of vertices in ground-pixel specification
num_instrument	Number of instruments
num_dads	Number of entries in DADS records
num_ch24	Dimension for UTC string time fields ("24")
num_ch08	Dimension for DADS time string ("8")
num_two	Dimension of fitting_window field ("2")

 

Table 3. geolocation group variables in the NetCDF files

Variable name	Dimension	Units	Description
year	num_times	n/a	Year of co-added observation
julian_day	num_times	n/a	Julian day of co-added observation
fractional_hour_of_day	num_times	n/a	Average fractional hour of day of co-added observation
flight_altitude	num_times	meters	Average aircraft altitude of co-added observation
center_latitude	num_times	degrees	Average latitude of ground pixel center of co-added observation
center_longitude	num_times	degrees	Average longitude of ground pixel center of co-added observation
solar_zenith_angle	num_times	degrees	Average solar zenith angle of co-added observation
solar_azimuth_angle	num_times	degrees	Average solar azimuth angle of co-added observation
viewing_zenith_angle	num_times	degrees	Average viewing zenith angle of co-added observation
viewing_azimuth_angle	num_times	degrees	Average viewing zenith angle of co-added observation
surface_elevation	num_times	meters	Average terrain height of co-added observation
time_tai93	num_times	seconds	Average TAI93 time of co-added observation
time_utc	num_times*num_ch24	n/a	UTC value of the co-added TAI93 time stamp
year_1s	num_times_1s	yyyy	Year of 1s observation
julian_day_1s	num_times_1s	n/a	Julian day of 1s observation
fractional_hour_of_day_1s	num_times_1s	n/a	Fractional hour of day of 1s observation
flight_altitude_1s	num_times_1s	meters	Aircraft altitude of 1s observation
center_latitude_1s	num_times_1s	degrees	Latitude of ground pixel center of 1s observation
center_longitude_1s	num_times_1s	degrees	Longitude of ground pixel center of 1s observation
solar_zenith_angle_1s	num_times_1s	degrees	Solar zenith angle of 1s observation
solar_azimuth_angle_1s	num_times_1s	degrees	Solar azimuth angle of 1s observation
viewing_zenith_angle_1s	num_times_1s	degrees	Viewing zenith angle of 1s observation
viewing_azimuth_angle_1s	num_times_1s	degrees	Viewing azimuth angle of 1s observation
surface_elevation_1s	num_times_1s	meters	Terrain height of 1s observation
time_tai93_1s	num_times_1s	seconds	TAI93 time of 1s observation
time_utc_1s	num_times_1s*num_ch24	n/a	UTC value of the 1s TAI93 time stamp

 

Table 4. science_products group variables in the NetCDF files

Note: Quality flag variables (qfl_*) indicate whether a value is missing (-1), good (0), suspect (1), or bad (2). See Table 8 for additional information.

Variable name	Dimension	Units	Description
col_o2_abo2	num_times	molec/cm2	O2 total column (Band 1)
err_col_o2_abo2	num_times	molec/cm2	O2 total column uncertainty (Band 1)
qfl_col_o2_abo2	num_times	n/a	O2 total column quality flag (Band 1)
col_co2_wco2	num_times	molec/cm2	CO2 total column (Band 2)
dac_co2_wco2	num_times	ppm	XCO2 column (Band 2)
err_col_co2_wco2	num_times	molec/cm2	CO2 total column uncertainty (Band 2)
err_dac_co2_wco2	num_times	ppm	XCO2 column uncertainty (Band 2)
qfl_col_co2_wco2	num_times	n/a	CO2 total column quality flag (Band 2)
qfl_dac_co2_wco2	num_times	n/a	XCO2 column quality flag (Band 2)
col_ch4_wco2	num_times	molec/cm2	CH4 total column (Band 2)
dac_ch4_wco2	num_times	ppb	XCH4 column (Band 2)
err_col_ch4_wco2	num_times	molec/cm2	CH4 total column uncertainty (Band 2)
err_dac_ch4_wco2	num_times	ppb	XCH4 column uncertainty (Band 2)
qfl_col_ch4_wco2	num_times	n/a	CH4 total column quality flag (Band 2)
qfl_dac_ch4_wco2	num_times	n/a	XCH4 column quality flag (Band 2)
col_h2o_wco2	num_times	molec/cm2	H2O total column (Band 2)
dac_h2o_wco2	num_times	ppm	XH2O column (Band 2)
err_col_h2o_wco2	num_times	molec/cm2	H2O total column uncertainty (Band 2)
err_dac_h2o_wco2	num_times	ppm	XH2O column uncertainty (Band 2)
qfl_col_h2o_wco2	num_times	n/a	H2O total column quality flag (Band 2)
qfl_dac_h2o_wco2	num_times	n/a	XH2O column quality flag (Band 2)
col_co2_sco2	num_times	molec/cm2	CO2 total column (Band 3)
dac_co2_sco2	num_times	ppm	XCO2 column (Band 3)
err_col_co2_sco2	num_times	molec/cm2	CO2 total column uncertainty (Band 3)
err_dac_co2_sco2	num_times	ppm	XCO2 column uncertainty (Band 3)
qfl_col_co2_sco2	num_times	n/a	CO2 total column quality flag (Band 3)
qfl_dac_co2_sco2	num_times	n/a	XCO2 column quality flag (Band 3)
col_ch4_sco2	num_times	molec/cm2	CH4 total column (Band 3)
dac_ch4_sco2	num_times	ppb	XCH4 column (Band 3)
err_col_ch4_sco2	num_times	molec/cm2	CH4 total column uncertainty (Band 3)
err_dac_ch4_sco2	num_times	ppb	XCH4 column uncertainty (Band 3)
qfl_col_ch4_sco2	num_times	n/a	CH4 total column quality flag (Band 3)
qfl_dac_ch4_sco2	num_times	n/a	XCH4 column quality flag (Band 3)
col_h2o_sco2	num_times	molec/cm2	H2O total column (Band 3)
dac_h2o_sco2	num_times	ppm	XH2O column (Band 3)
err_col_h2o_sco2	num_times	molec/cm2	H2O total column uncertainty (Band 3)
err_dac_h2o_sco2	num_times	ppm	XH2O column uncertainty (Band 3)
qfl_col_h2o_sco2	num_times	n/a	H2O total column quality flag (Band 3)
qfl_dac_h2o_sco2	num_times	n/a	XH2O column quality flag (Band 3)
col_co_sco2	num_times	molec/cm2	CO total column (Band 3)
dac_co_sco2	num_times	ppb	XCO column (Band 3)
err_col_co_sco2	num_times	molec/cm2	CO total column uncertainty (Band 3)
err_dac_co_sco2	num_times	ppb	XCO column uncertainty (Band 3)
qfl_col_co_sco2	num_times	n/a	CO total column quality flag (Band 3)
qfl_dac_co_sco2	num_times	n/a	XCO column quality flag (Band 3)

 

Tables 5a & 5b. retrieval_diagnostic group sub-groups and variables in the NetCDF files

Table 5a. Sub-groups

Note: Retrieval diagnostics layers are provided for multiple gases and derivation bands. CO₂ and CH₄ are being derived independently from two different bands of the CARVE FTS- Band 2, the weak CO₂ band (wco2) around 1.6 μm, and Band 3, the strong CO₂ band (sco2) around 2.3 μm. For symmetry, data fields related to O₂, which is observed oxygen A band, have been appended with “abo2”.

Sub-group name	Description
o2_abo2	Retrieval parameters for O2 fitting (Band 1)
co2_wco2	Retrieval parameters for CO2 fitting (Band 2)
ch4_wco2	Retrieval parameters for CH4 fitting (Band 2)
h2o_wco2	Retrieval parameters for H2O fitting (Band 2)
co2_sco2	Retrieval parameters for CO2 fitting (Band 3)
ch4_sco2	Retrieval parameters for CH4 fitting (Band 3)
h2o_sco2	Retrieval parameters for H2O fitting (Band 3)
co_sco2	Retrieval parameters for CO fitting (Band 3)

Table 5b. Variables

Note: “<gas>” indicates any gaseous absorber considered during the retrieval. While retrievals in the O₂ A band include only O₂ as an absorber, the other gas retrievals include multiple absorbers for the following list: CO₂, CH₄, H₂O, HDO, and CO. For details consult the variable entries in the particular sub-groups.

Variable name	Dimension	Units	Description
fitting_window	num_two	cm-1	Fitting window limits
baseline_polynomial	scalar	n/a	Order of fitted baseline Legendre polynomial
nit	num_times	n/a	Number of iterations
cl	num_times	native	Continuum level
ct	num_times	n/a	Continuum tilt
cc	num_times	0.075% p/p	Continuum curvature
fs	num_times	mK	Frequency shift
s_m_g	num_times	ppm	“Solar minus gas” shift
zo	num_times	%	Zero-level offset of continuum
zpres	num_times	Km	Surface pressure altitude
rms_o_cl	num_times	n/a	RMS nose / cl
am_<gas>	num_times	n/a	Air mass factor for <gas>
ovc_<gas>	num_times	molec/cm2	Original vertical column for <gas>
vsf_<gas>	num_times	n/a	Vertical scale factor for <gas>
vsf_<gas>_error	num_times	n/a	VSF total error for <gas>

 

Table 6. dads group variables in the NetCDF files

Variable name	Dimension	Units	Description
gps_alt	num_dads	m	Aircraft GPS altitude
gps_lat	num_dads	deg	Aircraft GPS latitude
gps_lon	num_dads	deg	Aircraft GPS longitude
gps_time	num_dads×num_ch08	n/a	GPS time (8 character UTC time string)
heading	num_dads	deg	Aircraft heading
pitch	num_dads	deg	Aircraft pitch
roll	num_dads	deg	Aircraft roll

 

Table 7. auxiliary_data group variables in NetCDF files

Variable name	Dimension	Units	Description
spectrum_signal	num_times×num_bands	n/a	Spectral signal of co-added data, by band
spectrum_noise	num_times×num_bands	n/a	Spectral noise of co-added data, by band
spectrum_snr	num_times×num_bands	n/a	SNR of co-added data, by band
spectrum_signal_1s	num_times_1s×num_bands	n/a	Spectral signal of 1s data, by band
spectrum_noise_1s	num_times_1s×num_bands	n/a	Spectral noise of 1s data, by band
spectrum_snr_1s	num_times_1s×num_bands	n/a	SNR of 1s data, by band
num_coadded_spectra	num_times	n/a	Number of 1s spectra in each co-added observation
idx_coadded_spectra	num_times×num_coadd	n/a	Index values of the num_coadded_spectra 1s  spectra used in each co-added observation

 

Companion files:

There are 172 *.zip files, with one file corresponding to each netcdf file, included with this data set as supporting information. These zip files follow the same file-naming convention as the netcdf data. The zip files contain quick-look plots (48 *.png per zip) plus a readme file explaining the png data plots. The image in Figure 1 is an example of a quick-look plot for the flight on 20120523.

The carbon budget of Arctic ecosystems is not known with confidence because fundamental elements of this complex system are poorly quantified. The CARVE project was designed to collect detailed measurements of important greenhouse gases on local to regional scales in the Alaskan Arctic and demonstrate new remote sensing and improved modeling capabilities to quantify Arctic carbon fluxes and carbon cycle-climate processes. The CARVE data provide insights into carbon cycling that may be useful in numerous applications. 

Each NetCDF file contains a global attribute MasterQualityFlag that provides a summary indication of the data quality level of the whole file. Its values are set to either good or suspect. Error estimates for total column and dry-air column computations are detailed further in Section 5 below. Global attributes PercentBadObservations, PercentGoodObservations, PercentMissingObservations, and PercentSuspectObservations indicate the percentage of data for which each quality flag is assigned.

In addition, each data product – either total or dry-air column – has a quality flag associated with it. This flag consists of an integer number for each reported observation (Table 8). The assessment of quality status is currently based on instrument signal-to-noise-ratio (SNR), absolute column value, relative fitting uncertainty of the retrieved total columns, and absolute values of the CO₂ and CH₄ dry-air columns:

i. Spectra with low SNR generally produce noisy, i.e., highly uncertain retrievals. Thus, FTS SNR values are used to screen for low-signal values. Any measurement below the minimum threshold - currently set to 20 - is flagged as bad. Since the FTS is not yet radiometrically calibrated, the SNR are used as proxy for scene illumination and overall radiometric information content.

ii. Negative values for total columns are bad. Thresholds for relative fitting uncertainty are listed in Table 9.

iii. Relative fitting uncertainty is used to distinguish suspect from good retrievals. For each product, relative fitting uncertainty is checked against a pre-set maximum. If the threshold is exceeded, the corresponding total column value is flagged suspect. 

iv. For quality assurance purposes, the physically acceptable range of XCO₂ is considered 370-430 ppm, and that of XCH₄ 1700-2200 ppb. Values outside those ranges are considered suspect. Similar assessments are not performed for XCO and XH₂O, due to the highly variable nature of those species.

Dry-air column products inherit the lowest-quality flag from the total column values that go into their computation. If at least one of the total columns is flagged suspect or bad, the resulting dry-air column will be flagged suspect or bad by default. 

Table 8. Summary of quality assessment and product quality flags

QC Flag	Flag Meaning	Description
-1	missing	No column values have been computed; entries are missing
0	good	Total or dry-air column value present and passes all quality checks
1	suspect	Caution advised because one or more of the following conditions are present: Total columns: Relative fitting uncertainties are above threshold specified in Table 9. Dry-air column: At least one of the total column values is suspect XCH4 only: value lies outside the range of 1700 – 2200 ppb XCO2 only: value lies outside the range of 370 – 430 ppm
2	bad	Avoid using data because one or more of the following conditions are present: SNR observation < 20 Total column value < 0 Dry-air columns only: at least one of the constituting total column values are bad

 

Table 9. Relative fitting uncertainties for total column products

Product	O2 (Band 1)	CO2 (Band 2)	CH4 (Band 2)	H2O (Band 2)	CO2 (Band 3)	CH4 (Band 3)	H2O (Band 3)	CO (Band 3)
Threshold	6%	2%	2%	2%	5%	5%	5%	30%

 

CARVE Flights

These data represent one part of the data collected by the Carbon in Arctic Reservoirs Vulnerability Experiment. A C-23 Sherpa aircraft made frequent flights out of Fairbanks, Alaska between March and November over multiple years, observing the spring thaw, summer draw-down, and fall refreeze of the Arctic growing season. Flights concentrate observations on three study domains: the North Slope, the interior, and the Yukon River valley. North Slope flights cover regions of tundra and continuous permafrost and were anchored by flux towers in Barrow, Atqasuk, and Ivotuk. Flights to Prudhoe Bay characterize the CO₂ and CH₄ emissions from oil and natural gas processing plants. Flights over interior Alaska sample discontinuous permafrost, boreal forests, and wetlands. A complete list of CARVE flights can be found at: https://carve.ornl.gov/flights.html. Flight paths and atmospheric gas concentrations for CARVE surveys can be visualized through the CARVE Flight Data Visualization Tool (http://carve.ornl.gov/visualize) and are illustrated in Figure 2.

 

Figure 2. CARVE flights during 2012-2015 delivered measurements over continuous and discontinuous permafrost regimes.

 

The CARVE aircraft carried a remote sensing and atmospheric sampling payload consisting of the following instruments: a Fourier transform spectrometer (FTS), and an in situ gas analyzer suite (ISGA) with a gas analyzer and PFP sampling system (see https://carve.ornl.gov/documentation.html). All instruments were controlled by a master computer system (Data Acquisition and Distribution System, DADS). Data were logged and UTC time stamped at 1 second intervals. DADS also recorded GPS data (Lat, Lon, elevation), aircraft pitch, roll, and yaw, as well as basic meteorological data from onboard instruments.

Fourier Transform Spectrometer

The CARVE Fourier Transform Spectrometer (FTS; Figure 2) consists of three near-IR channels with spectral ranges of 12,920 – 13,180 cm^-1 (Band 1), 5,820 – 6,380 cm^-1 (Band 2), and 4,200 – 4,322 cm^-1 (Band 3). Each band has a spectral resolution of 0.2 cm^-1. The instrument can be operated in polarization mode, where each band records the S- and P-polarization components separately, or un-polarized. During 2012, the first year of operations, the FTS observed in polarization mode. In 2013, prompted by the challenging observation conditions in the Alaskan Arctic, the instrument configuration was changed to un-polarized in order to improve signal-to-noise ratios.

The FTS Level 2 products are derived from all three bands: Band 1 provides the O₂ observations that are used in the computation of dry-air columns, as well as fluorescence (not part of the current release); Band 2 is used for retrievals of CO₂, CH₄, and H₂O; and Band 3 is used for observations of CO, as well as a second set of products for CO₂ and CH₄.

 

Figure 3. CARVE-FTS system: (a) instrument, (b) control electronic boxes, (c) power supply, and (d) interface control computer. Figure from Dupont et al., 2012.

The CARVE aircraft takes FTS nadir measurements in 1-second intervals along the flight track, corresponding roughly to a displacement of 100 m on the ground. For the retrievals, up to 100 of these 1-second observations are co-added to a single spectrum, corresponding to roughly 10 km along flight track. Pre-retrieval co-adding improves signal-to-noise ratio (SNR) of the observations and provides greatly improved uncertainties in the retrieved column values. Not necessarily all 100 spectra (per FTS band) with the 100-second co-adding interval are being used in the final, co-added spectrum. Rather, the selection is based on whether the specific set of three spectra – one from each of the three FTS bands – improves overall SNRs across the bands. If one or more of the three spectra significantly degrades the over SNR, the whole set is rejected. This ensures that (a) low SNR observations are discarded, and that (b) exactly the same set of 1-second observations is used in the 100-second co-added spectra for each band. The latter is important because dry-air columns are derived from ratios of retrievals performed in different bands, using different sets of 1 second spectra in each band for the same co-added observation would introduce a random source of error.

The CARVE FTS has a 10 degree field of view, which makes across-track coverage dependent on flight altitude. The current release of the FTS Level 2 data products do not contain information on ground footprint. A data field with this information will be added to future releases.

Both CO₂ and CH₄ are being derived independently from two different bands of the CARVE FTS – Band 2, also referred to as the weak CO₂ band (wco2) around 1.6 μm, and Band 3, the strong CO₂ band (sco2) around 2.3 μm. The field names in the data file have been appended with “wco2” and “sco2” in order to distinguish the same molecule product derived from bands 2 and 3. This has been done even in the cases of CO and H₂O, where no ambiguity exists. For symmetry, data fields related to O₂, which is observed in the oxygen A band, have been appended with “abo2”.

Several fields in the geolocation and auxiliary_data groups come in two sets, one of which contains “1s” at the end of the field names. These are the 1-second interval data mentioned above. They have been included in the data product for diagnostic purposes. Particularly the information on surface elevation at 1s temporal resolution (in geolocation), together with the list of 1s observations that went into each co-added retrieval (idx_coadded_spectra in the auxiliary_data group) may be helpful for enhanced quality assessment. The dads group contains latitude, longitude, and flight altitude information for the entire time the CARVE computer system on-board the aircraft was switched on. This includes the taxiing periods prior to take-off and after touch-down. While the variables in the geolocation group only provide information for periods when the FTS was in operation, the dads variables cover the full extent of the flight.

Retrieval and Total Column/Dry-Air Column Computations

Column retrievals are based on the TCCON GGG/GFit algorithm (TCCON, CalTech). GFit was developed to evaluate ground-based FTS direct sun observations. The algorithm was modified to include the atmospheric column below the aircraft in order to work with the CARVE flight measurements. GFIT uses a single atmospheric vertical profile scaled to match the absorbed radiances for each target gas. The algorithm returns a scaling factor as well as its error estimate for each trace gas profile included in the retrieval, plus values for spectral shift, continuum offset and curvature, and other auxiliary parameters fitted to the observed radiances.

Total column computation

Total column values for each gas are the product of the original column value reported by GFit and the retrieved scaling factor. Total column uncertainties are the product of the total column value and the algorithm error estimate. 

Dry-air column computation

The computation of dry-air columns (XCO₂, XCH₄, XCO, XH₂O) makes use of the constant volume mixing ratio of O₂ throughout most of the atmosphere. The dry-air column for gas G (XG) is computed from the observed total columns of the gas (TG) and that of O₂ (TO₂) as follows:

XG = ( TG / TO2 ) * 0.2095

which is then scaled by an additional factor depending on whether XG is reported in ppm or ppb.

The uncertainty of the dry-air columns dXG is computed from the relative root-sum-square total column errors of TG and TO₂:

dXG = XG * [ ( dTG / TG )² + ( dTO₂ / TO₂ )² ]^1/2

Note: Error estimates reported in the product for total and dry air columns are solely based on the algorithm retrieval error. They underestimate the true error, since error sources like scene inhomogeneity and line spectroscopy have not been considered.

Dupont, F., F. Tanguay, M. Li, G. Perron, C.E. Miller, S.J. Dinardo, and T.P. Kurosu (2012). CARVE-FTS Observations of Arctic CO2, CH4, and CO - Overview of the Instrument, Proc. Of SPIE, 8532, 853204. http:dx.doi.org/10.1117/12.979826

TCCON, Caltech. TCCON GGG/GFit algorithm. https://tccon-wiki.caltech.edu/Software/GGG. An account and password is required to access the information on the TCCON Wiki. Please consult the Wiki home page for contact information: https://tccon-wiki.caltech.edu/

Wunch, D., G.C. Toon, V. Sherlock, N.M. Deutscher, X. Liu, D.G. Feist, and P.O. Wennberg. The Total Carbon Column Observing Network's GGG2014 Data Version. 2015. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. http://dx.doi.org/10.14291/tccon.ggg2014.documentation.R0/1221662