AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus PublicationsGöttingen, Germany10.5194/amt-10-2209-2017Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2 measurements with TCCONWunchDebradwunch@atmosp.physics.utoronto.cadwunch@gps.caltech.eduhttps://orcid.org/0000-0002-4924-0377WennbergPaul O.https://orcid.org/0000-0002-6126-3854OstermanGregoryFisherBrendanNaylorBretRoehlColeen M.https://orcid.org/0000-0001-5383-8462O'DellChristopherMandrakeLukasViatteCamilleKielMatthäushttps://orcid.org/0000-0002-9784-962XGriffithDavid W. T.https://orcid.org/0000-0002-7986-1924DeutscherNicholas M.https://orcid.org/0000-0002-2906-2577VelazcoVoltaire A.https://orcid.org/0000-0002-1376-438XNotholtJustusWarnekeThorstenPetriChristofhttps://orcid.org/0000-0002-7010-5532De MaziereMartineShaMahesh K.https://orcid.org/0000-0003-1440-1529SussmannRalfRettingerMarkusPollardDavidhttps://orcid.org/0000-0001-9923-2984RobinsonJohnMorinoIsamuhttps://orcid.org/0000-0003-2720-1569UchinoOsamuHaseFrankBlumenstockThomasFeistDietrich G.https://orcid.org/0000-0002-5890-6687ArnoldSabrina G.StrongKimberlyhttps://orcid.org/0000-0001-9947-1053MendoncaJosephKiviRigelhttps://orcid.org/0000-0001-8828-2759HeikkinenPauliIraciLaurahttps://orcid.org/0000-0002-2859-5259PodolskeJamesHillyardPatrick W.KawakamiShujiDubeyManvendra K.https://orcid.org/0000-0002-3492-790XParkerHarrison A.SepulvedaEliezerGarcíaOmaira E.TeYaoJeseckPascalGunsonMichael R.CrispDavidhttps://orcid.org/0000-0002-4573-9998ElderingAnnmariehttps://orcid.org/0000-0003-1080-9922California Institute of Technology, Pasadena, CA, USAJet Propulsion Laboratory, Pasadena, CA, USAColorado State University, Fort Collins, CO, USAUniversity of Wollongong, Wollongong, AustraliaUniversity of Bremen, Bremen, GermanyRoyal Belgian Institute for Space Aeronomy, Brussels, BelgiumKarlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, GermanyNational Institute of Water and Atmospheric Research, Lauder, New ZealandNational Institute for Environmental Studies (NIES), Tsukuba, JapanKarlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe, GermanyMax Planck Institute for Biogeochemistry, Jena, GermanyUniversity of Toronto, Toronto, CanadaFinnish Meteorological Institute, Sodankylä, FinlandNASA Ames Research Center, Moffett Field, CA, USAJapan Aerospace Exploration Agency (JAXA), Tsukuba, JapanLos Alamos National Laboratory, Los Alamos, NM, USAIzaña Atmospheric Research Center, Meteorological State Agency of Spain (AEMet), Tenerife, SpainLERMA-IPSL, Sorbonne Universités, UPMC Univ Paris 06, CNRS, Observatoire de Paris, PSL Research University, 75005 Paris, FranceBay Area Environmental Research Institute, Petaluma, CA, USADebra Wunch (dwunch@atmosp.physics.utoronto.ca, dwunch@gps.caltech.edu)13June2017106220922386July201629August201612April201730April2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/articles/10/2209/2017/amt-10-2209-2017.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/articles/10/2209/2017/amt-10-2209-2017.pdf
NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon
dioxide column-averaged dry-air mole fraction, XCO2, in the
Earth's atmosphere for over 2 years. In this paper, we describe the
comparisons between the first major release of the OCO-2 retrieval algorithm
(B7r) and XCO2 from OCO-2's primary ground-based validation
network: the Total Carbon Column Observing Network (TCCON). The OCO-2
XCO2 retrievals, after filtering and bias correction, agree well
when aggregated around and coincident with TCCON data in nadir, glint, and
target observation modes, with absolute median differences less than
0.4 ppm and RMS differences less than 1.5 ppm. After bias
correction, residual biases remain. These biases appear to depend on
latitude, surface properties, and scattering by aerosols. It is thus
crucial to continue measurement comparisons with TCCON to monitor and
evaluate the OCO-2 XCO2 data quality throughout its mission.
Introduction
The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first Earth-orbiting
satellite dedicated to observing atmospheric carbon dioxide (CO2) to
better understand the carbon cycle. The mission's main goal is to measure
carbon dioxide with enough precision and accuracy to characterize its sources
and sinks on regional scales and to quantify its seasonal and interannual
variability . OCO-2 was
successfully launched on 2 July 2014 into low-Earth orbit, and its grating
spectrometers measure near-infrared spectra of sunlight reflected off the
Earth's surface in three spectral regions (centered at 0.765, 1.61, and
2.06 µm). Carbon dioxide and oxygen (O2) in the Earth's
atmosphere absorb sunlight at well-known wavelengths in the three spectral
regions. By fitting those absorption features using an optimal estimation
retrieval algorithm described in detail by and
, atmospheric abundances of carbon dioxide and surface
pressure are retrieved along with other atmospheric and surface properties
(e.g., cloud and aerosol optical depth and distribution, water vapor,
temperature, and surface reflectance).
The main product from the retrieved abundances of carbon dioxide and surface
pressure is the column-averaged dry-air mole fraction of CO2, called
XCO2, which is the ratio of CO2 to the dry surface
pressure. The XCO2 quantity is useful for carbon cycle science,
as it is used to directly infer surface fluxes of CO2, and is
relatively insensitive to vertical mixing .
In the remainder of this paper, a “measurement” refers to the entire
process of producing the atmospheric abundances of XCO2.
OCO-2 measures XCO2 with high precision from space
but possesses biases that the OCO-2 team have
attempted to characterize and remove . To validate the
OCO-2 measurements, we use the Total Carbon Column Observing Network
TCCON;, a comprehensive ground-based validation network
that also measures XCO2. The TCCON instruments are solar-viewing
Fourier transform spectrometers, and they measure the same atmospheric
quantity as OCO-2, but their measurements are unaffected by surface
properties and minimally affected by aerosols. TCCON instruments cannot
measure through optically thick clouds.
The OCO-2 satellite has three viewing modes: nadir mode, in which the
instrument points straight down at the surface of the Earth; glint mode, in
which the instrument points just off the glint spot on the surface; and
target mode, in which the observatory is commanded to scan about a particular
point on the ground as it passes overhead. The three modes serve different
purposes: the nadir and glint-mode measurements are normally used for
scientific analyses, and the target mode is used primarily as part of the
OCO-2 bias correction procedure. All three modes must be independently
verified using comparisons with the TCCON data. This paper will describe the
OCO-2 observation modes in Sect. , how the OCO-2 version 7
algorithm target-mode retrievals compare with the TCCON data in
Sect. , and how the glint and nadir mode measurements compare
with TCCON data in Sect. .
OCO-2 observation modes
OCO-2's nadir and glint observation modes are considered the nominal
“science modes” of the OCO-2 measurement scheme. The nadir observations
produce useful measurements only over land and near the sub-solar point over
tropical oceans. The glint data are often separated into glint over land
(“land glint”) and glint over water (“ocean glint”), as the two modes use
different surface reflectance models: Lambertian over land (matching the
surface model of the nadir observations) and Cox–Munk with a Lambertian
component over water. Retrievals are performed over a limited latitude range
in glint due to concerns about biases introduced by aerosol scattering over
the largest optical path lengths; see Fig. . The nadir
mode data can provide more reliable XCO2 measurements over
higher latitudes over land, which is particularly important in the Northern Hemisphere, where the boreal forest, a driver of the CO2 seasonal
cycle, extends north of 70∘ N. Measurements over inland lakes can be
successful in ocean glint mode.
OCO-2 nadir, glint, and target-mode measurement density in
5∘ bins as a function of latitude from the beginning of the mission
through 31 December 2016. These are from the “lite” files applying “warn
level” 11 filters and requiring that the “xco2_quality_flag” is
zero.
OCO-2 has a geographical “near-repeat” after 16 days. During each 16-day
period, the satellite orbits the Earth 233 times, with each orbit along a distinct
“orbital path”. The OCO-2 orbit is sun-synchronous, with an equator
crossing time near local noon 13:36 LT;. The original measurement scheme alternated
between glint and nadir observations on alternate 16-day ground track repeat
cycles. Due to the loss of ocean measurements during nadir mode, and the loss
of high latitude measurements during glint mode, key components of the carbon
cycle (e.g., the springtime draw down of CO2 due to the onset of the
Northern Hemisphere growing season) were poorly sampled. Thus, the observing
strategy was changed to improve the coverage of the oceans and high latitude
land masses on 2 July 2015 to alternate between glint and nadir modes for
each subsequent orbit. The OCO-2 observation scheme was optimized on
12 November 2015, to assign orbits that are almost entirely over ocean to
always measure in glint mode. This change occurred on 72 out of the 233
orbital paths: 15 over the Atlantic and 57 over the Pacific, resulting in
higher data throughput due to the reduction in nadir soundings over ocean.
discuss the measurement strategy in detail.
Target mode is designed to evaluate biases in the OCO-2 XCO2
product. The target locations are mostly selected to be coincident with
ground validation stations, typically at TCCON sites. During a target-mode
maneuver, the OCO-2 satellite rotates from its nominal science mode to point
at a selected ground location. This transition takes approximately 5 min
and rotates the spacecraft's solar panels away from the Sun. The spacecraft
then scans across the site or “nods” as it passes overhead to sweep across
the ground several times (see Fig. ) over a period
of about 4.5 min: these dithered measurements comprise the “target-mode
data”. The spacecraft then transitions out of target mode and back into its
nominal science mode over the next 5 min. In total, the maneuver takes about
14.5 min and, during this time, the spacecraft, traveling at
7.5 kms-1, has traveled over 6500 km.
The zenith angles viewed during an OCO-2 target-mode maneuver over
Lamont on 5 March 2015. The spacecraft “nods” across the ground target as
it rotates overhead. The colors and decreasing size of the points indicate
the time of the measurement. The top inset shows the locations of the
measurements in latitude and longitude. The eight footprints are apparent in the
roughly N–S stripes. There are 3473 soundings with a retrieval zenith angle
of less than 40∘ in this target-mode maneuver, most of which are
obscured in the inset by the later, nearly spatially coincident
soundings.
The strength of target-mode measurements is that thousands of spectra are
obtained in a short period of time over a small region of the world (about
0.2∘ longitude × 0.2∘ latitude for the densest
measurements). For example, in Fig. , there are
3473 soundings in the region around the Lamont TCCON station. As long as the
target location is far from large emissions sources, XCO2 can be
assumed constant spatially and temporally within a target region, because
atmospheric XCO2 is unlikely to change significantly over small
geographic regions within 4.5 min. However, during the maneuver, many other
parameters can change significantly, such as the atmospheric path, the path
length of the measurement (referred to as the “airmass”, where one airmass
corresponds to the optical path length of one vertical column through the
atmosphere), surface reflectivity (albedo), and topography. Any variability
in the retrieved XCO2 in the target-mode data is considered to
be an artifact and can provide insight into biases caused by the algorithm's
treatment of the parameters. With this in mind, the target locations were
carefully chosen to span a wide range of latitudes, longitudes, and surface
types to challenge the OCO-2 retrieval algorithm (B7r) and reveal any biases it
causes.
Available targets. Note that the target location (listed in degrees
latitude, degrees longitude, and altitude above sea level in km) may
not be exactly centered on a TCCON site location. Targets without a
corresponding TCCON station are marked with a star (∗) and are
not discussed in this paper.
There are a limited number of ground locations that can be targeted because
the locations must be preprogrammed into the spacecraft software. For the
1st year after launch, there were 19 possible target locations. In
July 2015, 8 additional targets slots became available, allowing for 27
target locations. At several times, target locations have been changed or
replaced. A list of the ground target locations and dates is provided in
Table , and a map of their locations is in
Fig. . Individual locations can be targeted by OCO-2 only
on specific OCO-2 orbit paths. Only one target location can be assigned to a
given orbit path, and only if the OCO-2 ground track for that path is
sufficiently close to the ground target location. Thus, for each day, there
are between one and seven ground target locations to choose from. The
spacecraft power systems can handle up to three target-mode maneuvers per day
due to the power constraints imposed by rotating the spacecraft solar panels
away from the Sun. We typically select only one target per day.
Map of OCO-2 target locations. Yellow circles show the locations of
the targets that coincide with TCCON stations; orange stars show the
locations of targets that do not have co-located TCCON
stations.
There are several TCCON stations that are located in regions with significant
spatial variability in topography or ground cover. For example, the Lauder
TCCON station is in the midst of rolling hills, the Wollongong TCCON station
is between the ocean and a sharp escarpment, and the Edwards TCCON station is
adjacent to a very bright playa, a land surface property previously
identified from the Greenhouse Gases Observing Satellite GOSAT;
results as challenging for space-borne
XCO2 retrievals . With target-mode
measurements, the impact that local surface variability has on the
XCO2 retrievals becomes apparent.
Other TCCON stations (e.g., Park Falls, Lamont) have relatively uniform
surface properties and are reasonably far from anthropogenic CO2
sources, but the ground cover can vary from season to season. The
Sodankylä and Eureka sites, located at high northern latitudes, challenge
the OCO-2 algorithm at very high solar zenith angles and airmasses and with
snowy scenes. Izaña, Réunion, and Ascension, all lower-latitude sites,
are located on small islands remote from large land masses but with
significant topography. The Izaña TCCON station (28.3∘ N) is at
2.37 km altitude, whereas the Réunion (20.9∘ S,
0.087 km) and Ascension Island (7.9∘ S, 0.032 km) stations are
closer to sea level.
Several TCCON target stations are near or in urban regions with varied
topography and emissions sources: Pasadena (population ∼ 17 million), Tsukuba
(population ∼ 228 000), Paris (population ∼ 2.24 million), and Karlsruhe
(population ∼ 300 000).
There are several target locations that are not TCCON stations
(Fig. , orange stars), and, although data from those
targets will not be analyzed in this paper, the data will help assess the
radiometric calibration of the instrument, its ability to measure large urban
sources of CO2, validate its solar-induced fluorescence observations
, and assess its ability to
measure vertically resolved information about CO2. Railroad Valley is
a heavily instrumented radiometric calibration site , and
Libya has surface properties that are valuable for radiometric calibration.
Shanghai, São Paulo, and Mexico City are geographically well-constrained
urban regions with significant CO2 emissions. Rosemount and
Litchfield have instrumentation that will help verify the OCO-2 solar-induced
fluorescence observations. Boulder has frequent AirCore CO2 profile
measurements . Fairbanks is the location of a future TCCON
station.
The OCO-2 spacecraft must be manually commanded to perform a target maneuver.
The target locations are selected a day or two in advance, based on the
weather forecast, the operational status of the TCCON station (if the target
is a TCCON station), the importance of the projected data loss in nadir or
glint mode from performing the target-mode operation, and the historical
statistics of successful target-mode measurements over that site. The
projected data loss depends primarily on whether the nominal mode for that
orbit was nadir over land, nadir over ocean, glint over land, or glint over
ocean. If the nominal mode is nadir over ocean, little useful data loss
occurs, as nadir measurements over ocean are usually too dark in the
near-infrared for successful retrievals: in this case, the target is almost always
selected given a reasonable weather forecast. This has mostly been the case
for Réunion Island, which has been targeted regularly from OCO-2 nadir
orbits. For the other three cases, there will be some loss of regular science
data to accommodate a target-mode operation. In these cases, the historical
statistics of acquiring good target-mode data and weather forecasts are
weighted more heavily before enabling the target. Often, if the weather
forecast is not ideal, no target-mode measurements will be selected.
As of 31 December 2016, 264 targets have been observed, with 230 of them over
TCCON stations. The TCCON data have been analyzed for 90 % of those
targets. Of the remaining 208 targets, about 59 % (123) were clear enough
to obtain sufficient high-quality OCO-2 data to compare with TCCON data.
Target mode and the OCO-2 bias correction
All current space-based XCO2 measurements have systematic
biases. These biases can be caused by uncertainties in the spectroscopy, by
limitations in the information content of the measurements (i.e., the spectra
do not contain enough information to resolve multiple independent vertical
pieces of information), by uncertainties or oversimplifications in the
optical properties of the atmosphere and surface – particularly from low-lying
cloud, haze, and aerosols – and by uncertainties in the instrument
characterization and calibration e.g.,
. Considerable
effort is dedicated to creating robust “bias correction” procedures, and
these are detailed in regularly updated documentation available online
through the Goddard Data Center and the CO2
portal . The bias correction procedure for the
current B7r dataset is described in .
There are three key types of biases addressed by the OCO-2 bias correction
procedure: footprint-dependent biases; spurious correlations of the retrieved
XCO2 with other retrieval parameters (a “parameter-dependent”
bias); and a multiplicative factor to scale to the World Meteorological
Organization (WMO) trace-gas standard scale , which we will
refer to as a “scaling” bias. The parameter-dependent bias can depend on
retrieval parameters such as the surface pressure retrieval error, signal
level, airmass, surface albedo, or spurious variability in the retrieved
CO2 profile.
Each OCO-2 spectral channel records eight spectra simultaneously, each with a
slightly different atmospheric path, and hence measures sunlight that has
reflected off of a different surface location or “footprint”. The
spectrally dependent radiometric response of each footprint is different and
is calibrated independently. Small (<0.1 %) uncertainties in the
calibration introduce persistent footprint-dependent biases in the retrieved
XCO2 that must be removed as part of the bias correction
process. Footprint-dependent biases are corrected using a subset of OCO-2
data collected over small areas around the world, in which there were at least
100 soundings with low variability, and where all eight footprint
measurements resulted in a successful retrieval . Note
that there are two footprint-dependent corrections applied to the B7r OCO-2
data: one that is applied as part of the standard bias correction algorithm
and one that was discovered after the generation of the bias correction. This
second “residual footprint bias” correction must be applied manually by the
data user . In all subsequent analyses in this paper,
both footprint-dependent biases are removed from the data, unless otherwise
specified. In future versions of the OCO-2 algorithm, there will be no
residual footprint bias correction required.
The relationship between the median value from each OCO-2
target-mode maneuver and the median value of the coincident TCCON data,
typically recorded within 1 h of the maneuver. The top plot (a)
does not have the bias correction applied and the middle
plot (b) is after bias correction but before the scaling is
applied. Plot (c) shows the relationship when the scaling correction
is applied and the recommended residual footprint correction
described in . Note that the best fit line in
plot (c) is much more consistent with the one-to-one line than in
plot (b). The slope and scatter in plot (c) is unaffected
by the residual footprint correction. The one-to-one line is indicated by the
dashed line, and the best fit is marked in the solid line. The error bars
represent the standard deviation about the median.
The time series of the differences between the OCO-2 target-mode
data and the best fit line in Fig. c. The top panel shows
the magnitude of the sum in quadrature of the standard deviation of the OCO-2
data during the target and the standard deviation of the coincident TCCON
data. Those values are plotted as the error bars in the lower
panel.
The parameter-dependent bias correction uses a genetic algorithm to determine
which retrieval parameters account for the largest fraction of the spurious
variability found in the estimated XCO2 on large spatial scales
. The algorithm uses two subsets of the
OCO-2 data for this task: a “Southern Hemisphere approximation” which
exploits the low spatial and temporal variability of XCO2 in
the Southern Hemisphere south of 25∘ S e.g.,
and a “small area analysis” which exploits the low spatial variability of
XCO2 within small regions (0.89∘ latitude on a single
orbit track) and can be applied at all latitudes . A
multivariate regression is performed between spurious XCO2
variability and the parameters. The resulting slopes of the regressions allow
us to then subtract the predicted bias from the XCO2 values. In
the results that follow, the footprint and parameter-dependent biases in the
OCO-2 target-mode data have been removed following ,
allowing us to determine the scaling factor that ties the OCO-2
XCO2 scale to the TCCON scale. Data near coastlines are used to
link the scaling factors between measurement modes. The parameter-dependent
corrections can affect the scaling bias; therefore, they must be removed
before the scaling bias can be computed.
Placing the OCO-2 data on the World Meteorological Organization's
trace-gas standard scale is crucial for obtaining accurate flux estimations
that are consistent with the inversions that assimilate the surface in situ
CO2 measurements that are carefully calibrated to the WMO scale
. The TCCON data are tied to the WMO scale and serve as the
link between the calibrated surface in situ measurements and the OCO-2
measurements.
Filters applied to the target-mode OCO-2 data from the standard
OCO-2 files (i.e., not the “lite” files). The parameter names listed below
are written as they are in the standard L2 files. Parameters for which there
is only one limit are marked with a “–”. The units are listed where
applicable. The parameter “blended_albedo” is defined as
2.4 × albedo_o2_fph - 1.13 × albedo_strong_co2_fph.
The tag “fph” denotes parameters from the full physics algorithm; “abp”
denotes
parameters from the A-band preprocessor algorithm designed for quick cloud
screening; “idp” denotes the IMAP-DOAS preprocessor.
ParameterLower boundUpper boundUnitsDescriptionsurface_pressure_delta_abp-4000583PaSurface pressure difference from the priorretrieval_surface_roughness–26.50Surface roughnessrelative_residual_mean_square_weak_co2–0.00250Spectral residuals in the weak CO2 bandretrieval_zenith–40∘Zenith angle of the retrievaloutcome_flag–2Data quality flagblended_albedo–0.8Described in the table captionh2o_ratio_idp0.71.02The ratio of water retrieved from the two CO2 bandsco2_ratio_idp0.9951.025The ratio of CO2 between the two bandssurface_pressure_delta_fph-510hPaSurface pressure difference from the priordof_co2_profile1.8–Degrees of freedom for signal in the CO2 profileice aod–0.03Ice aerosol optical depth extracted from the aerosol fielddust aod0.0010.3Dust aerosol optical depth extracted from the aerosol fieldco2_grad_del-7070The oscillation of the retrieved profile relative to the priorsulfate aod–0.4Sulfate aerosol optical depth extracted from the aerosol fieldalbedo_weak_co2_fph0.1–Weak CO2 albedoairmass–3.61cos(solarzenith)+1cos(retrievalzenith)surface_typeNot “Coxmunk”Not “Coxmunk”Retain only soundings over land (pure Lambertian surfaces)
The site-to-site differences between the OCO-2 data and the
coincident TCCON data, separated by observation mode. This is a “box plot”:
the bottom and top edges of the box indicate the 25 and 75 percentile limits;
whiskers represent the full range of the data, excluding the outliers
. The outliers and sites for which only one
coincident set of measurements is available are represented by plus
(“+”) symbols. The grey shaded area indicates the ±0.4 ppm
uncertainty in the TCCON values: deviations beyond the shading are more
likely attributable to uncertainties in the OCO-2 data. Filled boxes indicate
sites for which more than 10 coincident measurements were made. Open boxes
have at least three coincident measurements.
Edwards target on 19 April 2015. The background is the MODIS
true-color image of the Edwards area at the time of the target-mode
maneuvers. The white star indicates the location of the Edwards TCCON
station. The left panel shows the elevation model of the surface, and the
right panel shows the difference in OCO-2 XCO2 from the value
recorded by the TCCON instrument. A spatial bias related to the surface
brightness is clearly present in this target-mode measurement. In other
Edwards target-mode measurements, this surface brightness-correlated bias is
not as strong.
To tie the TCCON measurements to the WMO scale, over 30 profiles of in situ
CO2 have been measured directly overhead of 15 TCCON stations with
aircraft carrying carefully calibrated instrumentation
or AirCore . These
profiles, the first of which were collected in 2004, vary in altitude range,
depending on the vehicle, and thus must be combined with estimates of the
CO2 in the highest altitudes of the atmosphere to generate a full
vertical profile. These high-altitude CO2 profile estimates are
provided by the TCCON a priori profiles, which are based on in situ
measurements of the atmosphere from aircraft and high-altitude balloon
platforms . The full vertical profiles are then
integrated, smoothing with the TCCON averaging kernel and a priori profile to
compute the best estimate of the “true” XCO2 value. Integrated
profiles are compared with the retrieved XCO2 from the TCCON
spectra and result in a highly linear relationship which defines a
multiplicative bias between the TCCON XCO2 and the best estimate
of the “truth”. Removing this bias from the TCCON XCO2 ties it
to the WMO scale. The details of this method of tying the TCCON
XCO2 to the WMO scale are described in ,
, , and in
.
We consider TCCON data to be coincident with the OCO-2 target-mode
measurements when they have been recorded within ±30 min of the time at
which the spacecraft is closest to nadir during the maneuver. If there are
fewer than five TCCON data points recorded within that time, the window is
extended to ±120 min, but this is required in only 10 % of cases. We
use the full OCO-2 version B7 retrospective data (i.e., B7r), available from
http://disc.sci.gsfc.nasa.gov/OCO-2, and
manually apply the filters listed in Table .
The analyses of the target-mode data to develop the scaling bias are
completed prior to the generation of “warn levels” and the official
filtering schemes, and this scaling bias is applied as part of the bias
correction procedure required to generate the “lite” files used commonly by
the scientific community. Warn levels determine sets of OCO-2 data with
consistent quality data (as defined by the RMS scatter) within an observation
mode . A significant volume of data is
required to generate warn levels, which is difficult to achieve with the
relatively sparse target-mode data. Furthermore, individual warn levels in
one measurement mode are not necessarily equal in quality to another mode.
The target-mode filters are consistent with the “warn level 15” scheme
described by , except that the filter on the surface
pressure difference from the prior in the A-band preprocessor is loosened,
and we have added an additional outlier filter.
Figure shows the OCO-2 XCO2 target-mode median
data comparisons with coincident TCCON data. The best fit lines were computed
using a method that accounts for uncertainties in the dependent and
independent variables . Panel (a) shows the results prior to
applying the parameter-dependent bias correction and has a correlation
coefficient of R2=0.78. Panel (b) shows the relationship after the
correction has been applied and an improved correlation coefficient
(R2=0.86). This increase in R2 is significant at the 90 % level
(but not the 95 % level; p=0.055) using a standard Fisher's
z-transformation test. The improvement indicates that the
parameter-dependent bias correction is effective at removing spurious
variability in the OCO-2 data with respect to TCCON. The slope in panel (b),
which has a y intercept that is forced through 0, is used to derive the
scaling factor between TCCON and OCO-2 target observations
(m=0.9977±0.04, which represents ∼ 1 ppm) for the time
period spanning 8 September 2014 through 31 December 2016. The y intercept
is forced through 0 because it is assumed that in the absence of atmospheric
CO2, both OCO-2 and TCCON will measure 0 ppm. The scaling
factor derived as part of the bias correction procedure
was produced using the data available at the time, which spanned
November 2014 through May 2015, and resulted in a similar, but not identical,
slope of 0.99694±0.00102. This scaling bias difference results in a
0.3 ppm offset between OCO-2 and TCCON XCO2 at
400 ppm; the standard bias-corrected OCO-2 measurements appear to be
0.3 ppm too high. Panel (c) of Fig. shows the
relationship between the OCO-2 XCO2 after applying the bias
correction, scaling, and the residual footprint correction (m=1.0007±0.04,
R2=0.86). The residual footprint correction does not impact the slope or
R2 value of the relationship. have
shown that the uncertainties computed on this slope are likely to be
significantly overestimated.
The left panel shows the MODIS true-color image of the Wollongong
region. The orange solid line marks the east coast of Australia; the South
Pacific (Tasman Sea) lies to the east. The sharp Illawarra escarpment is the
dark region inland, mostly contained in the dashed orange box. The dashed
orange box shows the latitude and longitude extent of the images in the right
panel and in Fig. , and the white star indicates the
location of the Wollongong TCCON station. The right panel shows the retrieval
altitudes near the Wollongong TCCON station (indicated by the white star)
compiled from several target maneuvers.
The filtered target-mode measurements over Wollongong. The colors
represent the difference between the OCO-2 measurement and the coincident
TCCON measurement. The OCO-2 data over Wollongong are generally higher
(redder) than the TCCON measurements and significantly high in the July and
August 2015 target-mode maneuvers.
The long-term time dependence of the difference between the OCO-2 target-mode
data and the coincident TCCON data (ΔXCO2), after the
scaling bias is removed, is plotted in Fig. . The
algorithm, calibration, and instrument cause no apparent time-dependent drift
in ΔXCO2 or their errors. Thus, the bias correction is
successful at reducing both the parameter-dependent and scaling biases with
respect to TCCON and our other bias correction datasets described earlier in
this section.
Data from OCO-2 targets over the Lauder TCCON station. The
background is the MODIS true-color image of the Lauder area at the time of
the target-mode maneuvers. The white star indicates the location of the
Lauder TCCON station. The left panel shows the elevation model of the
surface. The middle panel shows the difference in XCO2 from the
value recorded by the TCCON instrument on 27 September 2014. The right panel
shows the difference in XCO2 from the value recorded by the
TCCON instrument on 17 February 2015. A spatial bias is clearly present,
related to the surface elevation, but the sign of the bias changes between
targets prior to 20 November 2014 and after.
However, the target-mode measurements are sensitive enough to point to some
residual biases (i.e., those not corrected by the , bias
correction process) that are currently under investigation by the OCO-2
algorithm, calibration, and validation teams. These residual biases are more
geographically localized in nature and appear to be related to surface
properties or instrument pointing errors and as such might not be expected
to be captured by the standard bias correction, which is designed to minimize
biases that dominate on a more global scale.
OCO-2 biases related to surface properties
Site-dependent differences from the one-to-one plot in
Fig. b are shown in Fig. and reveal
significant location-dependent biases. Any differences with magnitudes less
than 0.4 ppm could be attributable to TCCON station site-to-site
biases , so we focus on the biases that are significantly
larger and thus most likely attributable to the OCO-2 data. Two clear
examples of site-dependent biases are at Edwards, with a median low bias of
∼ 1 ppm, and Wollongong, with a median high bias of
∼ 0.8 ppm. The spatial dependence of the target-mode
measurements reveals that small-scale variability in surface properties
(e.g., albedo, altitude, surface roughness) can cause significant and
spurious variability in the OCO-2 XCO2.
The dependence of the difference between OCO-2 XCO2
coincident with TCCON XCO2 (ΔXCO2) on the
season and OCO-2 observing mode. This is a box plot akin to
Fig. . The filled boxes indicate seasons for which
there are > 10 comparison points between OCO-2 and TCCON; the thin boxes
contain at least 3 comparison points. Any site and season for which there
were fewer than three comparison points were excluded from the plot. The
different colors indicate the different seasons (blue = DJF,
orange = MAM, yellow = JJA, purple = SON). The TCCON stations are
ordered by latitude, where Lauder is 45∘ S and Eureka is
80∘ N. The equator is between Manaus (3∘ S) and Saga
(33∘ N). The high southern latitude ocean glint bias is clear in the
top plot.
The Edwards TCCON station is situated in the bright California high desert on
the edge of a very bright playa with near-infrared albedos reaching 0.6 and
little topographic change (Fig. ). There have been 12
target observations of Edwards, 10 of which had clear skies during the OCO-2
maneuver. On all but one of the clear-sky target maneuvers over Edwards, the
OCO-2 XCO2 appears to include a spurious dependence on surface
brightness, with higher XCO2 retrieved over brighter surfaces.
However, the magnitude of the sensitivity differs from target to target: the
RMS of the target-mode measurements ranges from 0.9 to 1.7 ppm, and
the relationships between surface albedo and XCO2 have different
slopes (ranging from -2.8 to 10.5 ppm per unit albedo with a mean of 4.5 ppm per unit albedo).
The underlying physical reason is currently unknown. All mean target-mode
OCO-2 XCO2 at Edwards is biased lower than the coincident TCCON
XCO2.
Conversely, the Wollongong station, which is situated near the east coast of
Australia, is a dark surface (with near-infrared albedos over land of
≲ 0.3) and lies between the Tasman Sea to the east and the
Illawarra escarpment to the west (Fig. ). The OCO-2
retrievals of XCO2 in target mode are systematically higher than
those from the TCCON, and are particularly high (up to 5 ppm higher
than TCCON) in July and August (Fig. ), due to the
problem discussed below in Sect. . OCO-2 data over
Białystok, located in a dark, forested region, also has a persistent high
bias (on the order of 1 ppm) compared with TCCON.
Even for sites at which OCO-2 XCO2 does not appear to have a
significant bias with respect to TCCON, the retrievals can show spurious
spatially correlated errors. The Lauder TCCON station is situated in a valley
between rolling hills (Fig. ). The surface altitude is
spatially correlated with changes in XCO2 during each
target-mode maneuver. The pattern is apparent in all but one clear-sky
target-mode measurement over Lauder. The biases with respect to TCCON switch
sign after 20 November 2014, when the pointing offsets used by the spacecraft
were updated (Fig. b and c). The average RMS of the
differences in XCO2 before and after 20 November 2014 are 1.2
and 1.1 ppm, respectively. The near-nadir OCO-2 measurements during
the target-mode maneuver (defined by restricting retrieval zenith angles to
≤20∘) show RMS variabilities of 0.9 ppm after 20 November 2014 and 0.8 ppm prior to 20 November 2014.
Land glint OCO-2 one-to-one plot against TCCON. The slope of the
relationship is represented by “m” in the figure, and the coefficient of
determination is represented by “R2”. The number of points on the graph
is indicated by “N” and the root-mean-square value (RMS) of the
differences between OCO-2 and TCCON XCO2 is also shown. Each
point represents a daily median of coincident OCO-2 and TCCON measurements.
Many points are overlaid in this graph, obscuring the density of points along
the best fit line.
Ocean glint OCO-2 one-to-one plot against TCCON. The left panel
shows all the glint-mode data. The right panel removes the Southern Hemisphere wintertime (June through September) glint data that have
a known
high bias. The annotations follow those in
Fig. .
Nadir and glint-mode comparisons to TCCON
In this section, we evaluate the bias-corrected OCO-2 glint and nadir modes
against ground-based TCCON data to reveal other biases that were not
eliminated using the standard version 7 bias correction. We use the version
B7 retrospective OCO-2 “lite” files here, which have had the
footprint-dependent, parameter-dependent, and scaling biases (described in
Sect. ) removed. The residual footprint correction was applied
manually to the data. The “lite” files are available from the CO2
Virtual Science Data Environment
http://co2.jpl.nasa.gov and from
.
We limit ourselves to data for which the warn level is less than or equal
to 11, as recommended by , and for which the
“xco2_quality_flag” is zero. caution against
using warn levels above 12 for nadir and glint modes, because those data can
contain errors significantly in excess of the stated a posteriori
uncertainties on the XCO2 values. For these comparisons, we
choose the following coincidence criteria: a box centered around the TCCON
station that spans 5∘ in latitude and 10∘ in longitude on the
same day as a TCCON measurement, with the exceptions mentioned below. In the
Southern Hemisphere south of 25∘ S, we use a larger box spanning
20∘ in latitude and 120∘ in longitude because the
geographical variance in XCO2 in the Southern Hemisphere is low
e.g.,. The Edwards and Pasadena boxes are constructed
differently because they are geographically very close to each other, but the
Pasadena site is within the polluted, mountain-contained South Coast Air
Basin, and Edwards is in the clean desert north of the mountains. Thus, we
limit the Edwards latitudes to north of Edwards but allow the longitudes to
span 5∘ further west over the Pacific Ocean. The Pasadena coincidence
box is constrained to the South Coast Air Basin, which significantly limits
the number of coincident points (see Appendix
Fig. a–t).
The median OCO-2 XCO2 within the coincidence box recorded on a
single day is compared with the TCCON daily median for that day. We choose to
compare OCO-2 nadir and glint-mode XCO2 with the TCCON daily
median values because the median reduces the random component of the TCCON
error budget, it is less sensitive to outlier measurements, and it weights
the results to local noon where solar zenith angle changes are slowest, and
the timing is better matched with the overpass time of OCO-2's orbit. The
more complicated dynamical coincidence criteria used to increase the number
of coincident measurements between TCCON and GOSAT in and
are not required for OCO-2, due to OCO-2's much higher
data density.
Nadir OCO-2 one-to-one plot against TCCON. The annotations follow
those in Fig. .
Glint and nadir statistics for data filtered using warn levels ≤11 and the xco2_quality_flag = 0. The median bias
(OCO-2 - TCCON) and its RMS, R2 and number of daily median comparison
points, or “coincidences” (N) are listed below for each TCCON station. If
the number of coincidences is larger than 10, the results are marked in bold
font. The “Total” row is calculated by considering all the coincidences in
the table independently.
Land glint Ocean glint Nadir BiasRMSR2NBiasRMSR2NBiasRMSR2NEureka0.192.000.7463Sodankylä2.382.530.95633.213.291.0002Białystok0.291.750.48540.533.570.17830.961.810.76614Bremen1.982.360.66540.620.810.90542.252.271.0002Karlsruhe0.861.490.812180.931.710.88717Orléans0.292.080.38714-0.322.180.53361.131.800.83919Garmisch0.241.190.873201.612.050.71627Park Falls-0.371.270.903220.351.280.858230.371.560.82329Rikubetsu0.722.330.82550.871.700.8137Lamont-0.301.160.86578-0.031.110.888108Tsukuba1.172.160.76510-0.361.610.772221.343.510.33515Edwards-0.091.250.84245-0.452.160.529400.481.220.84259Pasadena-0.341.050.8677-1.051.490.86550.510.980.92917Saga0.001.110.9157-1.121.510.71620-0.090.550.9386Manaus-0.821.060.7954Ascension Island-0.090.620.89990Réunion Island0.471.060.77550.300.810.87399Darwin-0.160.970.843700.140.840.881860.511.030.82779Wollongong-0.671.320.7332530.201.700.487366-0.121.040.780314Lauder0.090.960.829540.351.180.7822350.631.250.75566Total-0.271.290.7876200.171.410.66410110.221.310.795780
Glint and nadir statistics for data filtered using Warn Levels ≤15 and the xco2_quality_flag = 0. The median bias
(OCO-2 - TCCON) and its RMS, R2 and number of daily median comparison
points, or “coincidences” (N) are listed below for each TCCON station. If
the number of coincidences is larger than 10, the results are marked in bold
font. The “Total” row is calculated by considering all the coincidences in
the table independently. In general, the RMS values are equal to or larger than
those in Table despite the fact that the number of
coincidences is larger.
Land glint Ocean glint Nadir TCCON siteBiasRMSR2NBiasRMSR2NBiasRMSR2NEureka-0.190.880.9733Sodankylä2.242.460.97341.522.850.417102.602.910.76023Białystok1.512.440.54690.601.120.99631.291.890.82022Bremen1.362.260.800101.361.450.90562.042.041.0002Karlsruhe1.692.220.815271.602.280.66141.481.810.91921Orléans0.922.230.601210.091.600.68191.261.940.82622Garmisch1.141.760.83428-0.722.550.44141.521.970.78134Park Falls0.361.620.845420.501.670.798380.541.580.78243Rikubetsu1.372.250.90760.481.570.913120.320.840.9783Lamont0.011.330.827980.180.740.9695-0.071.070.891111Tsukuba1.332.010.81912-0.251.450.782312.314.110.34623Edwards0.181.710.71154-0.181.990.582470.441.240.83459Pasadena-0.223.370.16910-0.861.160.94050.390.900.93218Saga0.461.340.76114-1.031.330.912250.301.420.82714Manaus0.011.540.51211-0.390.511.00020.981.090.9624Ascension Island0.030.670.89392Réunion Island0.471.580.59350.410.810.8931001.511.850.5525Darwin-0.120.880.871810.290.840.890870.571.140.81788Wollongong-0.521.340.6702870.261.650.517367-0.111.040.779318Lauder0.461.910.547840.451.300.7682421.021.620.69084Total0.071.590.7048040.261.420.69410890.361.500.761897
Bias-corrected glint, nadir, and target relationships with TCCON. The
slope and its uncertainty, R2, and number of daily median comparison points
(N) are listed below for each OCO-2 viewing mode. The uncertainties on the
slopes are the standard deviation of the slopes computed through
bootstrapping. The values for ocean glint data with and without the Southern Hemisphere winter data are included on separate rows. Note that the slopes
are computed after the global bias has been removed from the data and the
residual footprint corrections have been applied. The glint and nadir data
are filtered with warn level ≤11 and xco2 quality flag = 0; the
target-mode data are filtered using the filters described in
Table .
Figure shows the differences between coincident OCO-2
XCO2 and that from TCCON, separated by viewing mode and season.
The bottom panel collects the viewing modes together, still separating by
season. The OCO-2 XCO2 appears to have a bias with respect to
TCCON that increases with increasing latitude in the land glint and nadir
data north of 45∘ N (Park Falls). This latitude-dependent bias is
consistent with the target-mode results (Fig. ). A
seasonal bias is not apparent at latitudes for which all four seasons have
sufficient coincident measurements (Lamont, Edwards, Ascension, Réunion,
Wollongong), indicating that the latitudinal bias is not likely caused by an
airmass-dependent bias (in either OCO-2 or TCCON). In general, however, the
number of coincident measurements is low (Table ),
especially in the Northern Hemisphere north of 45∘ N.
In the Southern Hemisphere winter, there is a significant high bias in the
retrieved XCO2 from the OCO-2 ocean glint data. The top panel of
Fig. clearly illustrates this problem by showing the
divergence of the OCO-2 XCO2 measurements in ocean glint mode
over Wollongong and Lauder from the TCCON XCO2 values during
June, July, and August. There were also three target-mode measurements
recorded in the Southern Hemisphere during that time: two points over
Wollongong and a third point over Réunion recorded during late
July and early August 2015 that hint at this residual bias
(Fig. ). Appendix Fig. r and s
also show this problem as a function of time. The bias is also seen in
preliminary comparisons to models (not shown), which also indicate a low bias
of OCO-2 ocean glint XCO2 in the tropical oceans. However, this
latter bias has not been clearly detected in comparisons with TCCON data
(e.g., Fig. p and r). The Southern Hemisphere ocean
glint bias does not impact the overall scaling bias between OCO-2 and TCCON
XCO2 within the uncertainty but does impact the latitudinal
gradients (and hence fluxes) inferred by the OCO-2 data. While the cause of
the bias in the southern winter is currently unclear, there is a promising
hypothesis related to the OCO-2 B7r algorithm's misrepresentation of
stratospheric aerosols, exacerbated by the eruption of Mount Calbuco in Chile
on 22 April 2015 .
The overall comparisons between the OCO-2 data and TCCON data are reported in
Tables and and shown in
Figs. – for data from
land glint mode, ocean glint mode, and nadir mode. The differences between
aggregated, bias-corrected OCO-2 XCO2 data coincident with all
available TCCON daily median measurements are -0.3, 0.2, and 0.2 ppm
for land glint, ocean glint, and nadir, respectively. The RMS values of these
differences are 1.3, 1.4, and 1.3 ppm, respectively. The differences
between the bias-corrected OCO-2 values and the TCCON medians differ from
site to site; sites with more than 10 coincident measurements have
differences in land glint mode ranging from -0.7 ppm (Wollongong)
to 0.9 ppm (Karlsruhe), in ocean glint mode ranging from
-1.1ppm (Saga) to 0.4ppm (Park Falls), and in nadir mode
ranging from -0.1 ppm (Wollongong) to 1.6 ppm (Garmisch).
Table contains the overall nadir and glint
statistics when using warn levels ≤15 instead of the recommended warn
level filter (≤11).
The nadir mode data show the best correlation of the three science modes
(R2=0.81), followed closely by land glint (R2=0.79) and finally ocean
glint (R2=0.63). The low correlation coefficient in the ocean glint data
is partially driven by the high anomalies in the Southern Hemisphere winter,
most obviously in the data over Wollongong (Fig. ). If the
Southern Hemisphere winter data (June–September) are excluded from the ocean
glint correlations, the R2 improves to 0.75. The slopes of all three
regressions are within uncertainty of 1.0. The agreement between the
science-mode OCO-2 data and TCCON is poorer than that for the target-mode
measurements. Halving the spatial coincidence criteria over each site does
not significantly improve the correlation coefficients. This suggests that it is not solely our
definition
of the coincidence criteria that causes the low correlation coefficients and
that perhaps the surface properties within the coincidence boxes contain
sufficient variability to degrade the comparisons. This highlights the
importance of the target-mode data for assessing local, site-to-site, and
overall bias.
Conclusions
Aggregated OCO-2 XCO2 estimates filtered with warn level
≤11 and xco2_quality_flag = 0 generally compare well with
coincident TCCON data at global scales, with absolute median biases less than
0.4 ppm and RMS differences less than 1.5 ppm. While the bias
correction clearly improves the relationship between TCCON and OCO-2
globally, some biases remain. Spurious local XCO2 variability
that is correlated with topography and surface brightness is apparent in the
target-mode measurements, particularly over Edwards, Wollongong, and Lauder.
Ocean glint measurements from OCO-2 at southern high latitudes during the
Southern Hemisphere winter are biased high, possibly due to stratospheric
aerosol interference. In all observation modes, there is an apparent
latitude-dependent bias, with the largest north of 45∘ N. Remedying these
residual biases is the current focus of the OCO-2 algorithm development and
validation teams, and we anticipate that the next version of the OCO-2 data
will represent a significant improvement. It is imperative to continue
measurement comparisons with TCCON in all modes (target, glint, and nadir) to
monitor and evaluate the OCO-2 data quality throughout its entire mission.
Unfiltered, uncorrected OCO-2 data are available from the
Goddard Data Center . The filtered and bias-corrected
data are contained in “lite” files, which are available both from JPL's
CO2 portal
https://co2.jpl.nasa.gov/, and the
Goddard Data Center. TCCON data are available from the TCCON data archive,
hosted by CDIAC: http://tccon.ornl.gov. Each TCCON dataset used in this
paper is cited independently in Table or in the captions of
Fig. .
Site plots
The ocean glint, land glint, and nadir mode plots for each TCCON station are
shown in Fig. . In each plot, there are four panels.
The top left panel shows the time series of the TCCON daily median data
(black circles) and the OCO-2 data (triangles colored differently for each
mode). The bottom left panel shows the difference between OCO-2 and TCCON
measurements (OCO-2 - TCCON). The top right panel shows the correlations
between the TCCON data and the OCO-2 data. The bottom right panel shows the
coincidence area for the OCO-2 measurements. Note that the gap in the OCO-2
data over Lauder in winter is caused by near-direct sun glint, during which
time the spacecraft is not permitted to measure (i.e., no data were recorded
at that latitude during that time).
The top left panel of each plot (a–t) shows the time
series of the TCCON daily medians (black circles) and the daily medians of
the OCO-2 glint mode (gold triangles), split into land glint (blue triangles)
and ocean glint (red triangles), and OCO-2 nadir mode (purple triangle). The
bottom left panel shows the difference between the OCO-2 data and TCCON data
as a function of time. The top right panel shows the one-to-one
correspondence between the OCO-2 XCO2 values and the TCCON
values, and the best fit lines in the colors corresponding to the symbols.
The one-to-one line is marked in black. The lower right panel shows the
location of the TCCON station (black circle) and the locations of the OCO-2
data, showing glint-mode data in gold and nadir-mode data in purple. The
lower right panel is intended to give a sense of the spatial coincidence
criteria applied to the OCO-2 data for each TCCON
station.
Debra Wunch wrote the manuscript and produced the main analysis and
results with significant input from Gregory Osterman, Camille Viatte, and
Paul O. Wennberg. Debra Wunch, Gregory Osterman, Brendan Fisher, Matthäus Kiel, Bret Naylor,
Coleen M. Roehl, Christopher O'Dell, Annmarie Eldering, Lukas Mandrake,
Camille Viatte, Michael R. Gunson, David Crisp, and Paul O. Wennberg
contributed to the experiment design and analysis of data.
David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco,
Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere,
Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson,
Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock,
Matthäus Kiel, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong,
Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske,
Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker,
Eliezer Sepulveda, Omaira E. García, Yao Te, and Pascal Jeseck provided
TCCON data. All authors read and provided comments on the
manuscript.
The authors declare that they have no conflict of
interest.
Acknowledgements
Part of this work was performed at the Jet Propulsion Laboratory, California
Institute of Technology, under contract with NASA. The operation of the Ascension
Island site was funded by the Max Planck Society. The Bremen, Białystok,
and Orléans TCCON sites are funded by the EU projects InGOS and
ICOS-INWIRE as well as by the Senate of Bremen. The Darwin and Wollongong TCCON
sites are funded by NASA grants NAG512247 and NNG05GD07G and by Australian
Research Council grants DP140101552, DP110103118, DP0879468, LE0668470, and
LP0562346. We are grateful to the DOE ARM program for technical support at
the Darwin TCCON site. Nicholas M. Deutscher
was supported by an Australian Research Council fellowship, DE140100178. The
TCCON site at Réunion Island is operated by the Royal Belgian
Institute for Space Aeronomy with financial support in 2014, 2015, and 2016
under the EU project ICOS-Inwire and the ministerial decree for ICOS
(FR/35/IC2) and local activities supported by LACy/UMR8105 – Université
de La Réunion. TCCON is funded by NASA grants NNX14AI60G, NNX11AG01G,
NAG5-12247, NNG05-GD07G, and NASA's Orbiting Carbon Observatory Program. We
are grateful to the DOE ARM program for technical support in Lamont and
Jeff Ayers for technical support in Park Falls. From 2004 to 2011 the Lauder
TCCON program was funded by the New Zealand Foundation of Research Science
and Technology contracts CO1X0204, CO1X0703, and CO1X0406. Since 2011 the
program has been funded by NIWA's Atmosphere Research Programme 3 (2011/13
Statement of Corporate Intent). The TCCON measurements at Eureka are made by
the Canadian Network for the Detection of Atmospheric Change (CANDAC), led by
James R. Drummond, and in part by the Canadian Arctic ACE Validation
Campaigns, led by Kaley A. Walker. They are supported by the Atlantic
Innovation Fund/Nova Scotia Research Innovation Trust, Canada Foundation for
Innovation, Canadian Foundation for Climate and Atmospheric Sciences,
Canadian Space Agency, Environment Canada, Government of Canada International
Polar Year funding, Natural Sciences and Engineering Research Council,
Northern Scientific Training Program, Ontario Innovation Trust, and Ontario
Research Fund and Polar Continental Shelf Program. We thank PEARL site
manager Pierre Fogal, the staff at the Eureka weather station, and the CANDAC
operators for the logistical and on-site support provided at Eureka.
Manvendra K. Dubey thanks DOE OBER's TES and NGEE-Tropics program for funding
and ARM for logistical support of the TCCON deployment during the GoAmazon
campaign. Edited by: H. Worden
Reviewed by: A. Jacobson and one anonymous referee
ReferencesBlumenstock, T., Hase, F., Schneider, M., Garcia, O. E., and Sepulveda, E.:
TCCON data from Izana (ES), Release GGG2014R0, TCCON data archive, CDIAC, 10.14291/tccon.ggg2014.izana01.R0/1149295, 2014.Boland, S., Brown, L. R., Burrows, J. P., Ciais, P., Connor, B. J., Crisp, D.,
Denning, A. S., Doney, S. C., Engelen, R., Fung, I. Y., Griffith, P., Jacob,
D. J., Johnson, B., Martin-Torres, J., Michalak, A. M., Miller, C. E.,
Polonsky, I., Potter, C., Randerson, J. T., Rayner, P. J., Salawitch, R. J.,
Santee, M., Tans, P. P., Wennberg, P. O., Wunch, D., Wofsy, S. C., and Yung,
Y. L.: The Need for Atmospheric Carbon Dioxide Measurements from Space:
Contributions from a Rapid Reflight of the Orbiting Carbon Observatory,
Tech. rep., available at: https://www.nasa.gov/pdf/363474main_OCO_Reflight.pdf (last access: 5 November 2011), 2009.Connor, B. J., Boesch, H., Toon, G. C., Sen, B., Miller, C. E., and Crisp, D.:
Orbiting Carbon Observatory: Inverse method and prospective error analysis,
J. Geophys. Res., 113, 1–14, 10.1029/2006JD008336,
2008.Crisp, D.: Measuring atmospheric carbon dioxide from space with the Orbiting
Carbon Observatory-2 (OCO-2), SPIE, 9607, 960702-1,
10.1117/12.2187291, 2015.Crisp, D., Miller, C. E., and DeCola, P. L.: NASA Orbiting Carbon Observatory:
measuring the column averaged carbon dioxide mole fraction from space,
J. Appl. Remote Sens., 2, 23508, 10.1117/1.2898457, 2008.Crisp, D., Pollock, H. R., Rosenberg, R., Chapsky, L., Lee, R. A. M.,
Oyafuso, F. A., Frankenberg, C., O'Dell, C. W., Bruegge, C. J., Doran, G. B.,
Eldering, A., Fisher, B. M., Fu, D., Gunson, M. R., Mandrake, L., Osterman,
G. B., Schwandner, F. M., Sun, K., Taylor, T. E., Wennberg, P. O., and Wunch,
D.: The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2)
instrument and its radiometrically calibrated products, Atmos. Meas. Tech.,
10, 59–81, 10.5194/amt-10-59-2017, 2017.De Mazière, M., Sha, M. K., Desmet, F., Hermans, C., Scolas, F., Kumps,
N., Metzger, J.-M., Duflot, V., and Cammas, J.-P.: TCCON data from Reunion
Island (RE), Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.reunion01.R0/1149288, 2014.Deutscher, N. M., Notholt, J., Messerschmidt, J., Weinzierl, C., Warneke, T.,
Petri, C., Grupe, P., and Katrynski, K.: TCCON data from Bialystok (PL),
Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.bialystok01.R0/1149277, 2014.Dubey, M., Henderson, B., Green, D., Butterfield, Z., Keppel-Aleks, G., Allen,
N., Blavier, J.-F., Roehl, C., Wunch, D., and Lindenmaier, R.: TCCON data
from Manaus (BR), Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.manaus01.R0/1149274, 2014.Eldering, A., O'Dell, C. W., Wennberg, P. O., Crisp, D., Gunson, M. R.,
Viatte, C., Avis, C., Braverman, A., Castano, R., Chang, A., Chapsky, L.,
Cheng, C., Connor, B., Dang, L., Doran, G., Fisher, B., Frankenberg, C., Fu,
D., Granat, R., Hobbs, J., Lee, R. A. M., Mandrake, L., McDuffie, J., Miller,
C. E., Myers, V., Natraj, V., O'Brien, D., Osterman, G. B., Oyafuso, F.,
Payne, V. H., Pollock, H. R., Polonsky, I., Roehl, C. M., Rosenberg, R.,
Schwandner, F., Smyth, M., Tang, V., Taylor, T. E., To, C., Wunch, D., and
Yoshimizu, J.: The Orbiting Carbon Observatory-2: first 18 months of science
data products, Atmos. Meas. Tech., 10, 549–563, 10.5194/amt-10-549-2017,
2017.Feist, D. G., Arnold, S. G., John, N., and Geibel, M. C.: TCCON data from
Ascension Island (SH), Release GGG2014R0, TCCON data archive,
CDIAC, 10.14291/tccon.ggg2014.ascension01.R0/1149285, 2014.Frankenberg, C., O'Dell, C. W., Berry, J., Guanter, L., Joiner, J.,
Köhler, P., Pollock, R., and Taylor, T. E.: Prospects for chlorophyll
fluorescence remote sensing from the Orbiting Carbon Observatory-2, Remote
Sens. Environ., 147, 1–12, 10.1016/j.rse.2014.02.007, 2014.GES-DISC: Goddard Earth Sciences Data and Information Services Center OCO-2
Data Holdings, available at: http://disc.sci.gsfc.nasa.gov/OCO-2 (last access: 15 March 2017),
2016.Griffith, D. W., Deutscher, N. M., Velazco, V. A., Wennberg, P. O., Yavin, Y.,
Aleks, G. K., Washenfelder, R. a., Toon, G. C., Blavier, J.-F., Murphy, C.,
Jones, N., Kettlewell, G., Connor, B. J., Macatangay, R., Roehl, C., Ryczek,
M., Glowacki, J., Culgan, T., and Bryant, G.: TCCON data from Darwin (AU),
Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.darwin01.R0/1149290, 2014a.Griffith, D. W., Velazco, V. A., Deutscher, N. M., Murphy, C., Jones, N.,
Wilson, S., Macatangay, R., Kettlewell, G., Buchholz, R. R., and Riggenbach,
M.: TCCON data from Wollongong (AU), Release GGG2014R0, TCCON data archive,
CDIAC, 10.14291/tccon.ggg2014.wollongong01.R0/1149291,
2014b.Guerlet, S., Butz, A., Schepers, D., Basu, S., Hasekamp, O. P., Kuze, A.,
Yokota, T., Blavier, J.-F. L., Deutscher, N. M., Griffith, D. W., Hase, F.,
Kyro, E., Morino, I., Sherlock, V., Sussmann, R., Galli, A., and Aben, I.:
Impact of aerosol and thin cirrus on retrieving and validating XCO2 from
GOSAT shortwave infrared measurements, J. Geophys. Res.-Atmos., 118, 4887–4905, 10.1002/jgrd.50332, 2013.Hase, F., Blumenstock, T., Dohe, S., Gross, J., and Kiel, M.: TCCON data from
Karlsruhe (DE), Release GGG2014R1, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.karlsruhe01.R1/1182416, 2014.Iraci, L. T., Podolske, J., Hillyard, P. W., Roehl, C., Wennberg, P. O.,
Blavier, J.-F., Allen, N., Wunch, D., Osterman, G., and Albertson, R.: TCCON
data from Edwards (US), Release GGG2014R1, TCCON data archive,
CDIAC, 10.14291/tccon.ggg2014.edwards01.R1/1255068, 2016.JPL-Caltech: CO2 Virtual Science Data Environment, available at:
http://co2.jpl.nasa.gov (last access: 15 March 2017), 2016.Karion, A., Sweeney, C., Tans, P. P., and Newberger, T.: AirCore: An
Innovative Atmospheric Sampling System, J. Atmos. Ocean.
Tech., 27, 1839–1853, 10.1175/2010JTECHA1448.1,
2010.Kawakami, S., Ohyama, H., Arai, K., Okumura, H., Taura, C., Fukamachi, T., and
Sakashita, M.: TCCON data from Saga (JP), Release GGG2014R0, TCCON data
archive, CDIAC, 10.14291/tccon.ggg2014.saga01.R0/1149283,
2014.Keppel-Aleks, G., Wennberg, P. O., and Schneider, T.: Sources of variations
in total column carbon dioxide, Atmos. Chem. Phys., 11, 3581–3593,
10.5194/acp-11-3581-2011, 2011.Kivi, R., Heikkinen, P., and Kyrö, E.: TCCON data from Sodankyla (FI),
Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.sodankyla01.R0/1149280, 2014.Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near infrared
sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring.,
Appl. Optics, 48, 6716–6733, 10.1364/AO.48.006716, 2009.Kuze, A., O'Brien, D. M., Taylor, T. E., Day, J. O., O'Dell, C. W., Kataoka,
F., Yoshida, M., Mitomi, Y., Bruegge, C. J., Pollock, H., Basilio, R.,
Helmlinger, M., Matsunaga, T., Kawakami, S., Shiomi, K., Urabe, T., and Suto,
H.: Vicarious Calibration of the GOSAT Sensors Using the Railroad Valley
Desert Playa, IEEE T. Geosci. Remote Sens., 49,
1781–1795, 10.1109/TGRS.2010.2089527, 2011.Kuze, A., Suto, H., Shiomi, K., Kawakami, S., Tanaka, M., Ueda, Y., Deguchi,
A., Yoshida, J., Yamamoto, Y., Kataoka, F., Taylor, T. E., and Buijs, H. L.:
Update on GOSAT TANSO-FTS performance, operations, and data products after
more than 6 years in space, Atmos. Meas. Tech., 9, 2445–2461,
10.5194/amt-9-2445-2016, 2016.Mandrake, L., Frankenberg, C., O'Dell, C. W., Osterman, G., Wennberg, P., and
Wunch, D.: Semi-autonomous sounding selection for OCO-2, Atmos. Meas. Tech.,
6, 2851–2864, 10.5194/amt-6-2851-2013, 2013.Mandrake, L., O'Dell, C. W., Wunch, D., Wennberg, P. O., Fisher, B., Osterman,
G. B., and Eldering, A.: Orbiting Carbon Observatory-2 (OCO-2) Warn Level,
Bias Correction, and Lite File Product Description, Tech. rep., Jet
Propulsion Laboratory, California Institute of Technology, Pasasdena,
available at:
http://disc.sci.gsfc.nasa.gov/OCO-2/documentation/oco-2-v7/OCO2_XCO2_Lite_Files_and_Bias_Correction_0915_sm.pdf (last access: 16 October 2015),
2015.McGill, R., Tukey, J. W., and Larsen, W. A.: Variations of Box Plots,
Am. Stat., 32, 12–16, 10.2307/2683468, 1978.Messerschmidt, J., Geibel, M. C., Blumenstock, T., Chen, H., Deutscher, N.
M., Engel, A., Feist, D. G., Gerbig, C., Gisi, M., Hase, F., Katrynski, K.,
Kolle, O., Lavric, J. V., Notholt, J., Palm, M., Ramonet, M., Rettinger, M.,
Schmidt, M., Sussmann, R., Toon, G. C., Truong, F., Warneke, T., Wennberg, P.
O., Wunch, D., and Xueref-Remy, I.: Calibration of TCCON column-averaged
CO2: the first aircraft campaign over European TCCON sites, Atmos. Chem.
Phys., 11, 10765–10777, 10.5194/acp-11-10765-2011, 2011.Morino, I., Matsuzaki, T., and Shishime, A.: TCCON data from Tsukuba (JP),
125HR, Release GGG2014R1, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.tsukuba02.R1/1241486, 2014a.Morino, I., Yokozeki, N., Matzuzaki, T., and Horikawa, M.: TCCON data from
Rikubetsu (JP), Release GGG2014R1, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.rikubetsu01.R1/1242265, 2014b.Nguyen, H., Osterman, G., Wunch, D., O'Dell, C., Mandrake, L., Wennberg, P.,
Fisher, B., and Castano, R.: A method for colocating satellite
XCO2 data to ground-based data and its application to ACOS-GOSAT
and TCCON, Atmos. Meas. Tech., 7, 2631–2644, 10.5194/amt-7-2631-2014,
2014.Notholt, J., Petri, C., Warneke, T., Deutscher, N. M., Buschmann, M.,
Weinzierl, C., Macatangay, R., and Grupe, P.: TCCON data from Bremen (DE),
Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.bremen01.R0/1149275, 2014.O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C.,
Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J.,
Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T.,
Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval
algorithm – Part 1: Description and validation against synthetic
observations, Atmos. Meas. Tech., 5, 99–121, 10.5194/amt-5-99-2012,
2012.Pan, L. L., Bowman, K. P., Atlas, E. L., Wofsy, S. C., Zhang, F., Bresch,
J. F., Ridley, B. A., Pittman, J. V., Homeyer, C. R., Romashkin, P. A., and
Cooper, W. A.: The Stratosphere–Troposphere Analyses of Regional Transport
2008 Experiment, B. Am. Meteorol. Soc., 91,
327–342, 10.1175/2009BAMS2865.1,
2010.Romero, J. E., Morgavi, D., Arzilli, F., Daga, R., Caselli, A., Reckziegel, F.,
Viramonte, J., Díaz-Alvarado, J., Polacci, M., Burton, M., and
Perugini, D.: Eruption dynamics of the 22–23 April 2015 Calbuco Volcano
(Southern Chile): Analyses of tephra fall deposits, J. Volcanol.
Geoth. Res., 317, 15–29, 10.1016/j.jvolgeores.2016.02.027, 2016.Schneising, O., Bergamaschi, P., Bovensmann, H., Buchwitz, M., Burrows, J.
P., Deutscher, N. M., Griffith, D. W. T., Heymann, J., Macatangay, R.,
Messerschmidt, J., Notholt, J., Rettinger, M., Reuter, M., Sussmann, R.,
Velazco, V. A., Warneke, T., Wennberg, P. O., and Wunch, D.: Atmospheric
greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS
measurements and model results, Atmos. Chem. Phys., 12, 1527–1540,
10.5194/acp-12-1527-2012, 2012.Sherlock, V., Connor, B. J., Robinson, J., Shiona, H., Smale, D., and Pollard,
D.: TCCON data from Lauder (NZ), 125HR, Release GGG2014R0, TCCON data
archive, CDIAC, 10.14291/tccon.ggg2014.lauder02.R0/1149298,
2014.Singh, H. B., Brune, W. H., Crawford, J. H., Jacob, D. J., and Russell, P. B.:
Overview of the summer 2004 Intercontinental Chemical Transport
Experiment-North America (INTEX-A), J. Geophys. Res.-Atmos., 111, D24S01, 10.1029/2006JD007905, 2006.Strong, K., Mendonca, J., Weaver, D., Fogal, P., Drummond, J., Batchelor, R.,
and Lindenmaier, R.: TCCON data from Eureka (CA), Release GGG2014R0, TCCON
data archive, CDIAC,
10.14291/tccon.ggg2014.eureka01.R0/1149271, 2014.Sussmann, R. and Rettinger, M.: TCCON data from Garmisch (DE), Release
GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.garmisch01.R0/1149299, 2014.Te, Y., Jeseck, P., and Janssen, C.: TCCON data from Paris (FR), Release
GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.paris01.R0/1149279, 2014.Warneke, T., Messerschmidt, J., Notholt, J., Weinzierl, C., Deutscher, N. M.,
Petri, C., Grupe, P., Vuillemin, C., Truong, F., Schmidt, M., Ramonet, M.,
and Parmentier, E.: TCCON data from Orléans (FR),
Release GGG2014R0, TCCON data archive, CDIAC,
10.14291/tccon.ggg2014.orleans01.R0/1149276, 2014.Washenfelder, R. A., Toon, G. C., Blavier, J.-F. L., Yang, Z., Allen, N. T.,
Wennberg, P. O., Vay, S. A., Matross, D. M., and Daube, B. C.: Carbon
dioxide column abundances at the Wisconsin Tall Tower site, J.
Geophys. Res., 111, 1–11, 10.1029/2006JD007154,
2006.Wennberg, P. O., Roehl, C., Wunch, D., Toon, G. C., Blavier, J.-F.,
Washenfelder, R. a., Keppel-Aleks, G., Allen, N., and Ayers, J.: TCCON data
from Park Falls (US), Release GGG2014R0, TCCON data archive,
CDIAC, 10.14291/tccon.ggg2014.parkfalls01.R0/1149161,
2014a.Wennberg, P. O., Wunch, D., Roehl, C., Blavier, J.-F., Toon, G. C., and Allen,
N.: TCCON data from Caltech (US), Release GGG2014R1, TCCON data archive,
CDIAC, 10.14291/tccon.ggg2014.pasadena01.R1/1182415,
2014b.Wennberg, P. O., Wunch, D., Roehl, C., Blavier, J.-F., Toon, G. C., Allen, N.,
Dowell, P., Teske, K., Martin, C., and Martin., J.: TCCON data from Lamont
(US), Release GGG2014R1, TCCON data archive, hosted by CDIAC,
10.14291/tccon.ggg2014.lamont01.R1/1255070, 2016.Wofsy, S. C.: HIAPER Pole-to-Pole Observations (HIPPO): fine-grained,
global-scale measurements of climatically important atmospheric gases and
aerosols, Philos. T. R. Soc. A, 369, 2073–86,
10.1098/rsta.2010.0313, 2011.Wunch, D., Toon, G. C., Wennberg, P. O., Wofsy, S. C., Stephens, B. B.,
Fischer, M. L., Uchino, O., Abshire, J. B., Bernath, P., Biraud, S. C.,
Blavier, J.-F. L., Boone, C., Bowman, K. P., Browell, E. V., Campos, T.,
Connor, B. J., Daube, B. C., Deutscher, N. M., Diao, M., Elkins, J. W.,
Gerbig, C., Gottlieb, E., Griffith, D. W. T., Hurst, D. F., Jiménez, R.,
Keppel-Aleks, G., Kort, E. A., Macatangay, R., Machida, T., Matsueda, H.,
Moore, F., Morino, I., Park, S., Robinson, J., Roehl, C. M., Sawa, Y.,
Sherlock, V., Sweeney, C., Tanaka, T., and Zondlo, M. A.: Calibration of the
Total Carbon Column Observing Network using aircraft profile data, Atmos.
Meas. Tech., 3, 1351–1362, 10.5194/amt-3-1351-2010, 2010.Wunch, D., Toon, G. C., Blavier, J.-F. L., Washenfelder, R. A., Notholt, J.,
Connor, B. J., Griffith, D. W., Sherlock, V., and Wennberg, P. O.: The total
carbon column observing network, Philos. T. R. Soc. A, 369, 2087–2112,
10.1098/rsta.2010.0240, 2011a.Wunch, D., Wennberg, P. O., Toon, G. C., Connor, B. J., Fisher, B., Osterman,
G. B., Frankenberg, C., Mandrake, L., O'Dell, C., Ahonen, P., Biraud, S. C.,
Castano, R., Cressie, N., Crisp, D., Deutscher, N. M., Eldering, A., Fisher,
M. L., Griffith, D. W. T., Gunson, M., Heikkinen, P., Keppel-Aleks, G.,
Kyrö, E., Lindenmaier, R., Macatangay, R., Mendonca, J., Messerschmidt,
J., Miller, C. E., Morino, I., Notholt, J., Oyafuso, F. A., Rettinger, M.,
Robinson, J., Roehl, C. M., Salawitch, R. J., Sherlock, V., Strong, K.,
Sussmann, R., Tanaka, T., Thompson, D. R., Uchino, O., Warneke, T., and
Wofsy, S. C.: A method for evaluating bias in global measurements of CO2
total columns from space, Atmos. Chem. Phys., 11, 12317–12337,
10.5194/acp-11-12317-2011, 2011b.
Wunch, D., Toon, G. C., Sherlock, V., Deutscher, N. M., Liu, C., Feist, D. G.,
and Wennberg, P. O.: The Total Carbon Column Observing Network's GGG2014
Data Version, Tech. rep., California Institute of Technology, Carbon Dioxide
Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge,
Tennessee, USA, https://doi.org/10.14291/tccon.ggg2014.documentation.R0/1221662,
2015.Yang, Z., Washenfelder, R. a., Keppel-Aleks, G., Krakauer, N. Y., Randerson,
J. T., Tans, P. P., Sweeney, C., and Wennberg, P. O.: New constraints on
Northern Hemisphere growing season net flux, Geophys. Res. Lett.,
34, L12807, 10.1029/2007GL029742,
2007.York, D., Evensen, N. M., Martinez, M. L., and De Basabe Delgado, J.: Unified
equations for the slope, intercept, and standard errors of the best straight
line, Am. J. Phys., 72, 367, 10.1119/1.1632486, 2004.Zhang, B., Cressie, N., and Wunch, D.: Statistical properties of atmospheric
greenhouse gas measurements: Looking down from space and looking up from the
ground, Chemometr. Intell. Lab., 162, 214–222,
10.1016/j.chemolab.2016.11.014, 2017.Zhao, C. L. and Tans, P. P.: Estimating uncertainty of the WMO mole fraction
scale for carbon dioxide in air, J. Geophys. Res., 111,
1–10, 10.1029/2005JD006003,
2006.