We have measured the column-averaged atmospheric CO2 mixing ratio to a
variety of cloud tops by using an airborne pulsed multi-wavelength
integrated-path differential absorption (IPDA) lidar. Airborne measurements
were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days,
and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were
compared to those from an in situ sensor. Analysis of the lidar backscatter
profiles shows the average cloud top reflectance was ∼ 5 % for the
CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower
reflectance. The energies for 1 µs wide laser pulses reflected
from cloud tops were sufficient to allow clear identification of CO2
absorption line shape and then to allow retrievals of atmospheric column
CO2 from the aircraft to cloud tops more than 90 % of the time.
Retrievals from the CO2 measurements to cloud tops had minimal bias but
larger standard deviations when compared to those made to the ground,
depending on cloud top roughness and reflectance. The measurements show this
new capability helps resolve CO2 horizontal and vertical gradients in
the atmosphere. When used with nearby full-column measurements to ground, the
CO2 measurements to cloud tops can be used to estimate the
partial-column CO2 concentration below clouds, which should lead to better
estimates of surface carbon sources and sinks. This additional capability of
the range-resolved CO2 IPDA lidar technique provides a new benefit for
studying the carbon cycle in future airborne and space-based CO2
missions.
Introduction
Precise and accurate atmospheric CO2 measurements with global coverage
and full seasonal sampling are crucial to advance carbon cycle sciences
(Schimel et al., 2016). Passive remote sensing of column-averaged atmospheric
CO2 mixing ratio (XCO2) from space using Earth's surface-reflected
sunlight, e.g., the US Orbiting Carbon Observatory (OCO-2; Crisp et al.,
2004) and the Japanese Greenhouse gases Observation SATellite (GOSAT; Kuze et
al., 2009), is limited to cloud-free pixels, where the photon path length can
be well characterized. However those missions are unable to provide quality
retrievals in the presence of clouds and aerosols due to significant
modification of the photon path length by scattering (e.g., Mao and Kawa,
2004; Houweling et al., 2005; Aben et al., 2007; Butz et al., 2009; Uchino et
al., 2012; Yoshida et al., 2013; Guerlet et al., 2013). Passive
remote-sensing data from space thus are limited in spatial coverage and seasonal
sampling, which may cause large uncertainty in regional and hemispheric
carbon flux estimates (Chevallier et al., 2014; Reuter et al., 2014; Feng et
al., 2009, 2016, 2017).
Active (lidar-based) remote sensing of CO2 from space will carry its
own optical source and so will allow day and night measurements and
global sampling throughout the year. Range-resolved laser measurements allow
accurate determination of the photon path length and thus enable accurate retrievals of
XCO2 to the scattering surface, even in the presence of thin clouds and
aerosols. Because of these benefits the US National Research Council
recommended the NASA Active Sensing of CO2 Emissions over Nights, Days,
and Seasons (ASCENDS) mission in the 2007 report Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond (National Research Council, 2007;
http://www.nap.edu/catalog/11820.html).
The NASA Goddard Space Flight Center (GSFC) has developed a pulsed
multi-wavelength integrated-path differential absorption (IPDA) lidar
called the CO2 Sounder to measure atmospheric CO2 from
space as a candidate for NASA's ASCENDS mission (Abshire et al., 2010, 2013,
2014, 2017). It uses a time-resolved receiver to record the
altitude-resolved laser backscatter profiles at all measurement wavelengths,
which enables accurate ranging to cloud tops and other targets. This allows
retrieval of partial-column XCO2 to cloud tops in addition to those for
the full column to the ground. The difference in absorption line shapes
between the full column and the partial column to cloud tops can be used to
estimate partial-column XCO2 between the ground and cloud tops for
lower-layer atmospheric CO2 (Ramanathan et al., 2015).
A 30 min long vertical cross section (a) and two
individual 1 s vertical profiles (b) of atmospheric backscattering
at offline wavelengths of CO2 line measured by NASA GSFC CO2
Sounder near the West Branch, Iowa, tall-tower site on 11 August 2011. The
backscatter signals were corrected by square of range and averaged by
1 µs vertical running mean (∼ 150 m) and 1 s horizontal
running mean (200 m of ground track). Returns from ground, cumulus and
cirrus clouds, and aerosols are illustrated and labeled.
The GSFC CO2 Sounder has been flown on NASA DC-8 aircraft since 2010
over a variety of sites in the US, along with other ASCENDS airborne lidar
candidates together with accurate in situ CO2 sensors. This paper
describes the retrievals and analyses of partial-column XCO2
measurements made to cloud tops for a variety of cloud types during the
2011, 2013 and 2014 ASCENDS airborne campaigns.
Measurement approach
The airborne CO2 Sounder lidar uses a tunable narrow line width laser to
measure CO2 absorption at 30 wavelengths across the vibration–rotation
line of CO2 centered at 1572.335 nm. The line has a Lorentz half-width
αL≈ 0.07 cm-1 (∼ 17 pm or 2.1 GHz) at
standard atmospheric pressure and temperature. The laser is pulsed in a width
of 1 µs at a rate of 10 kHz (or a step of 100 µs), and
the laser scans across the CO2 line at 30 wavelengths at a 300 Hz rate.
The wavelength of each pulse was increased by 450 MHz or 0.015 cm-1
uniformly for 2011 and 2013 campaigns. The sampling spacing was changed for the
2014 campaign to be 250 MHz near line center and 2 GHz or 0.067 cm-1
on line wings to allow for more online samples. The laser line width is
approximately 15 MHz or 0.0005 cm-1. The laser's spectral resolution
is considerably higher than that of GOSAT (∼ 0.2 cm-1; Kuze et
al., 2009), OCO-2 (∼ 0.3 cm-1; Crisp et al., 2004) and the
ground-based Fourier transform spectrometers of the Total Carbon Column
Observing Network (TCCON; ∼ 0.02 cm-1; Wunch et al., 2011). The narrow
line width allows the measured CO2 line shape to be fully resolved,
including line width and line center position (Ramanathan et al., 2013). The
parameters of the GSFC CO2 Sounder have been summarized in tables of
previous publications (Abshire et al., 2010, 2013, 2014).
The CO2 Sounder is mounted in a fixed nadir-pointed orientation, which
results in vertically directed measurements from the aircraft during normal
horizontal flights. However, when the aircraft tilts, the laser points
off-nadir, and the laser measurement direction is accounted for in the data
processing. The laser photons backscattered from the atmosphere and ground
are collected by a 20 cm receiver telescope, pass through a narrow
(∼ 1 nm) band-pass filter, and then are focused onto the lidar
detector. The bandwidth of receiver is 10 MHz, and it has a response time of
30 ns. The range backscatter profiles are accumulated and recorded after
being averaged for all laser wavelengths at a 10 Hz rate to improve
signal-to-noise ratio (SNR). The lidar measures range to better than 0.25 m
to flat surfaces over a horizontal path from the laboratory (Amediek et al.,
2013).
In the following sections, we briefly describe and illustrate GSFC CO2
Sounder measurements, including backscattering, range, surface roughness and
surface reflectance that enable retrievals of the partial-column XCO2
to cloud tops.
Backscatter measurements
As an example, Fig. 1 shows a 30 min duration of backscatter profiles
measured over Iowa during the 2011 ASCENDS airborne science campaign. The
figure shows height-resolved lidar returns from the ground and from the top
of fair-weather cumulus clouds at the top of the planetary boundary layer
(PBL) near 2 km as well as from the body of high-altitude cirrus clouds.
Some distributed aerosols were present, particularly within the boundary
layer, but the signal was weak. The backscatter profiles at two discrete
times are also shown.
Range measurements and surface roughness
The laser pulse energies from each significant scattering surface can be
processed at each of the 30 transmitted wavelengths to display CO2 line
absorption features in terms of optical depth (OD). An example is shown in
Fig. 2. These samples of the absorption line shape may be used to retrieve
XCO2 from aircraft altitude to each significant scattering surface by
fitting measured ODs to pre-calculated ODs for the same atmospheric state.
The ranging capability of pulsed lidar allows accurate determination of
photon path length for XCO2 retrievals. This is a major advantage of
this lidar approach over passive approaches for remote sensing of greenhouse
gases when the reflecting surface elevation is uncertain (e.g., cloud tops tall trees)
and when the atmosphere has significant scattering (Mao and Kawa, 2004; Aben
et al., 2007).
Backscatter profile (a) and CO2 absorption line
shapes (b) in terms of optical depth for laser returns from ground,
cumulus clouds and cirrus clouds from a flight altitude of 12 km near the West Branch, Iowa, tall-tower site on
10 August 2011. In the left panel, the offline backscatter profile is
plotted in red, and the backscatter profile at line center with peak
absorption is plotted in blue. Both optical depth and differential optical
depth between offline and line center wavelength increase with photon path
length or range between aircraft and the scattering surface. Data are
averaged over 10 s of ground track for both plots. In the right panel the
dots are the lidar measurements and the solid lines are the best-fit line
shapes from the XCO2 retrievals.
Histogram of the variation in sea surface elevation on the 22 August 2014
ASCENDS flight over the Pacific Ocean near the California coast. The green
bars are raw data for every 0.1 s integration time (20 m scale along
track), and the blue bars are averages over 5 s (1 km scale along track).
In order to improve precision, the raw lidar measurements may be aggregated
to a larger scale before being used for XCO2 retrievals. The range to
the scattering surfaces may vary significantly within the aggregated scale,
depending on the roughness of scattering surface and data aggregation time.
In previous measurements (Abshire et al., 2013), the standard deviation of
range measurements from the aircraft to a flat surface, e.g., Railroad Valley,
NV, was about 1 m but increased to 25 m over mountains within a 10 s data
average time, which corresponds to 2 km ground track length. These changes
are caused by changes in surface topography within the averaging time.
In this study, we first calculated surface elevation for ground and/or cloud
tops using lidar range measurements, pointing angle and aircraft altitude.
The measurements showed the relative surface elevation change from one data point to
the next increases with flight distance. During a
flight in the 2014 campaign, one flight was made over the Pacific Ocean near
the California coastline with low winds. The lidar range measurements made at
10 Hz show 0.5 m standard deviation in the relative surface elevation
changes, as shown in Fig. 3. The standard deviation of the relative surface
elevation changes increased to about 1 m after measurements were averaged
over 5 s or 1 km horizontal distance. Although the data aggregation before
retrieval can increase SNR and improve retrieval
precision for flat surfaces, over rougher surfaces like mountains there can
be more variation in the photon path length, which can limit the data
averaging time before retrieval. Since surface roughness and XCO2
variations are smaller over ocean than over land, data can be averaged over
a longer time over oceans before retrieval.
The elevations of cloud tops can vary significantly. Lidar measurements
showed the standard deviation of marine stratus cloud top heights from the
2014 flights at the California coastline was approximately 5 m for a 0.1 s
averaging time and increased to 18 m for 5 s averages, as shown in Fig. 4,
which is reasonably consistent with estimates from the 2011 flights over the
Pacific Ocean (Abshire et al., 2013). As expected, the range measurements to
puffy popcorn-like cumulus cloud tops made in the 2014 campaign showed more
variation. The standard deviation of the relative cumulus cloud top height
changes from one point to the next was 42 m for 0.1 s averages and 107 m for 5 s
averages, as shown in Fig. 5. Thus, the partial-column XCO2
measurements made to cumulus cloud tops using 10 s averaged data are
expected to be noisier than these over marine stratus clouds.
The same as Fig. 3 but for the 20 August 2014 flight above marine
stratus clouds along the California coastline, showing a 0.1 s standard
deviation of 5.2 m and a 5 s standard deviation of 18 m for cloud top height
changes from one point to the next.
Cloud reflectance
The lidar measurement of backscatter profiles also allows us to estimate the
reflectance of the scattering surfaces. For a pulsed lidar, the reflectance
of a scattering surface is given by
rs=ErEtrR2τsys,
where Er is the signal backscatter pulse energy, Etr is the
laser transmitter energy, R is the range to the surface and τsys
is the lidar system transmission. The lidar signal from an elevated surface
such as an aerosol or a cloud layer only includes the backscattered
component from the laser. For the pulsed CO2 Sounder, only the photons
backscattered by clouds within the 150 m thick atmospheric layer (with the
1 µs laser pulse width) are collected and then used to estimate cloud
reflectance. In contrast for clouds illuminated by sunlight, a passive sensor
viewing the clouds collects all photons including those scattered from
outside of the field of view, as well as photons scattered forward by cloud
particles and then backscattered by lower clouds. Thus, for thick clouds
more sunlight is returned, and the passively measured cloud reflectance is much
higher at these wavelengths.
Figure 1 shows an example of airborne lidar measurements and the relative
strength of pulse echoes reflected from the ground, cumulus clouds and cirrus
clouds. The echoes from the ground show the sharpest vertical profile as
the ground is a solid surface. The vertical extent of backscatter from cirrus
clouds is broader than those from cumulus cloud tops. This is because cirrus
clouds were semi-transparent while cumulus clouds were denser so that only
photons reflected back from the cloud tops are scattered back to the
receiver. For cumulus clouds, the peak pulse return at offline wavelengths
(in red) was about 40 % of the ground return, while for cirrus clouds the
peak return was approximately 25 % of ground return.
The same as Fig. 4 but for the 25 August 2014 flight above cumulus
clouds in Iowa, showing a 0.1 s standard deviation of 42 m and a 5 s
standard deviation of 107 m for cloud top height changes from one point to
the next.
The lidar-measured cloud top reflectance values were calculated for each
flight of these campaigns. Figure 6 shows that for the cumulus clouds over
Iowa in 2014, after being averaged in 150 m vertical layers and over 10 s of
ground track, the median value of cloud top reflectance was approximately
5 %. The averaged reflectance of Pacific marine stratus cloud tops during
the 2011 and 2014 flights was about 4 %. The reflectance of the dense and
tall cumulonimbus clouds during a thunderstorm on a 2014 flight in Iowa was
slightly higher, 6 %, while the ground reflectance was estimated to be
20 %. The range-resolved reflectance of the cirrus clouds was found to be
substantially lower, depending on the physical and spatial structure of the
clouds. As shown in the backscatter vertical profiles in Fig. 1, after lidar
range correction, reflectance of relatively dense and thick cirrus cloud on
the bottom left panel (22:40:04 UTC) was half of cumulus cloud reflectance,
or 2–3 %, while reflectance of the thinner cirrus clouds on
the right panel (23:00:24 UTC) was 1 %. For the range-distributed backscatter
from cirrus clouds, if the vertical signal accumulating layer is increased,
then the integrated pulse echo energy and reflectance would be higher.
(a) shows the cumulus clouds in the PBL from the ASCENDS
sunset flight on 25 August 2014 near the West Branch, Iowa, tall tower.
(b) shows the returned pulse energy in number of photons as a
function of lidar range from aircraft altitude for the cumulus clouds. The
average ground reflectance (in green) is approximately 20 %, while the
average cumulus cloud top reflectance is about 5 % (in blue) and shows
more variability.
Data analysis shows that the pulsed lidar signals from cloud tops were
sufficient to clearly capture the CO2 absorption line shape. The full
line shape from the total of 30 wavelengths across the line is shown in Fig. 2.
With the lidar range measurement, this allows quality retrievals of
XCO2 to cloud tops. These retrievals are expected to be noisier than
those to the ground due to the lower reflectance of clouds. During the 2013
and 2014 campaigns in the United States West and Midwest, the ground
reflectance was 15–40 % (listed in Table 1). Meanwhile, the reflectance of
ocean surface at nadir was 10–20 %, depending on wind speed, and quickly
dropped to nearly zero when the aircraft banked and the laser pointed off-nadir.
Snow ice particles have a strong absorption band near 1500 nm, and snow
surfaces have reflectance of 2–10 % at 1572 nm wavelengths, depending on
snow condition, e.g., grain size (Wiscombe and Warren, 1980; Painter and
Dozier, 2004). In the campaign, snow scenes were sometimes mixed with other
more highly reflecting objects, e.g., trees and rocks. Note reflectance of
40 % over desert surfaces is an established standard for estimating
reflectance and is very close to in situ measurements made by the GOSAT
validation team in Railroad Valley at CO2 Sounder measurement
wavelengths (Kuze et al., 2011).
Lidar measurements of surface reflectance during the 2013 and 2014
ASCENDS science flights (SF) over a variety of surface types, including
ocean, snow and clouds. Reflectance of 0.4 over desert was specified as a
standard to quantify reflectance over other surface types.
SurfaceReflectanceFlightMeasurement locationDesert0.42014 SF2Edwards AFB, CA(established2013 SF1Owens Valley, CAstandard)2013 SF2Railroad Valley, NVSemi-desert0.322014 SF2Great Basin Range, NVDesert/cropland0.25-0.352013 SF1Central Valley, CA2014 SF1 & SF4Central Valley, CACropland (winter)0.302013 SF5Great Plains, CO/NE/IAMountain/forests0.25-0.302014 SF3Rocky Mountains, CO2014 SF4Sierras, CACropland (summer)0.202014 SF3 & SF5IowaForests0.15–0.252014 SF1N. California forestsOcean (normal incidence)0.10–0.202014 SF2Pacific OceanOcean (slant incidence)0–0.102014 SF2Pacific OceanSnow (cold)0.05–0.102013 SF4Rockies, COSnow (warm)0.02–0.102013 SF5Midwest, IA/MOClouds0.02–0.102014 SF1, SF2 & SF3West and MidwestCloud identification and data processingCloud identification
Clouds often occur in multiple layers and have variability in density or
opacity and cloud top height. Figure 7 shows the shape of the laser pulses
transmitted and those backscattered from clouds. The cloud-returned pulse
shape varied with cloud type and structure. For the analysis used here, the
data processing of cloud returns is performed in two steps. In the first
step, pulse echoes from significant scattering surfaces are identified from
the lidar backscatter profiles. For hard (ground) or relatively opaque
surfaces (dense cloud tops), as shown in Fig. 7, the echo width is limited
to 150 m, corresponding to the laser's 1 µs pulse width. For signals
backscattered from diffuse clouds, we first subdivided the backscatter
profiles into 500 m atmospheric layers. We then labeled those with
sufficient backscatter as a pulse echo. The range to each echo was then
calculated using the centroid of the backscatter from that layer, as
illustrated in Fig. 2. In the second step, the cloud echoes were grouped and
stratified for every 500 m layer and then aggregated and averaged over 10 s
of ground track. The averaged line shapes were used to retrieve XCO2 to
the averaged centroid cloud height.
The lidar-transmitted pulse shape (a) and the recorded echo pulse shape
returned from a dense cloud top (b). The solid blue lines are for
pulse #15, which is near the CO2 absorption line center, and the
solid red lines are for pulse #30, which is in the line wing. Horizontal black lines are
signal baselines, and vertical dashed lines indicate signal integration
windows. The dashed red lines in the middle are the integration center
position in defining the centroid cloud height. Range unit is meters.
The altitude of a significant scattering surface can usually be determined
using lidar range, the aircraft GPS altitude and pitch and roll angles.
However, during aircraft rolls and turns, distinguishing the altitude of
cloud tops from the ground sometimes required using the simultaneous aircraft
radar data that provided the nadir range to the ground through the clouds. We
also did not data when the aircraft was too close to cloud tops
(< 1 km) and when the aircraft tilted substantially
(> 10∘ off-nadir).
Data processing
The lidar's retrieval process for XCO2 used several steps.
The data from the CO2 Sounder are calibrated before XCO2 is
retrieved by using a line-fitting retrieval algorithm (Abshire et al.,
2014). The calibration utilizes a laser energy vs. wavelength correction
(< 10 %); a correction for the transmissions of the receiver's
optical band-pass filter (< 2 %); and, for these flights, a
detector nonlinearity correction (< 2 %). The laser wavelengths
are benchmarked in the lab and field by using auxiliary equipment and
measurements. The CO2 Sounder pulse energy monitor is calibrated while
the instrument is operating in the field. The outgoing laser pulse energies
are monitored using a beam pick-off, integrating sphere and detector. The
acquisition of outgoing pulse energy uses the same digitizer as the lidar
backscatter. Additional post-flight calibration is made using a flight
segment during the engineering flight with known atmospheric conditions and
a high-resolution CO2 mixing ratio profile measured by an onboard in
situ sensor, where instrument parameters are calibrated against atmospheric radiative
transfer calculations. This allows assessing the corrections for detector
nonlinearity and the receiver's optical band-pass filter. These calibrations
are then applied to all retrievals for the science flights.
In the forward calculations, we used the spectroscopy database HITRAN 2008
(Rothman et al., 2009) and the Line-By-Line Radiative Transfer Model
(LBLRTM; Clough et al., 1992; Clough and Iacono, 1995) V12.1 to calculate
CO2 optical depth and create look-up tables (LUTs) for a vertically
uniform CO2 concentration of 400 ppm. We then use these LUTs to
retrieve the best-fit CO2 concentration by comparing the measured line
shape samples with calculated absorption line shapes. The retrievals used
atmosphere (pressure, temperature and water vapor profiles) from the near
real time forward processing data of the Goddard Earth Observing System
Model, Version 5 (GEOS-5; Rienecker et al., 2011). Data on the full model
grid (0.25∘ latitude × 0.3125∘ longitude×72 vertical layers,
every 3 h) were interpolated to flight ground track position and time
for the atmospheric CO2 absorption calculations. Absorption line
fitting was performed in optical depth with a linear least-squares fitting
approach. The fitting residuals were spectrally weighted by the square of
estimated SNR at each measurement wavelength based on our lidar noise model,
which gives more weighting to measurements on line wings than those on line
center. The retrieval algorithm solves for Doppler shift, baseline offset,
slope, surface reflectance, column-averaged CO2 and H2O (XCO2
and XH2O) simultaneously for the best fitting. Details of forward
calculations and retrieval algorithm were given in Abshire et al. (2014).
(a) Photo of marine stratus cloud deck over the Pacific
Ocean near the California coastline taken on the ASCENDS flight on
2 August 2011. (b) The retrieved values of XCO2 to the cloud
tops at altitudes of 700 m (black dashed line) as a function of flight
altitude. The XCO2 values integrated from the in situ AVOCET gas analyzer
are marked in black squares, and the retrieved values from the CO2
Sounder for 10 s average are marked in red circles. The error bars for the
retrieved XCO2 are for ±1 standard deviation.
There is a weak isotopic water vapor (HDO) line centered at 1572.253 nm on
the shoulder of the 1572.335 nm CO2 line. Depending on atmospheric
water vapor content, this can distort the CO2 line shape and impact the
value of the XCO2 retrieval. The CO2 Sounder's wavelength
assignments place one or two laser wavelengths on the HDO line peak. This allows
the retrievals to also solve for XH2O, which is important because
atmospheric water vapor content is highly variable in space and time.
Passive remote sensing of greenhouse gases, e.g., OCO-2, GOSAT and TCCON, measures O2 absorption for
column dry-air abundance. Measuring column water vapor is an alternative way to
adjust water vapor data from weather forecast models for better estimates of
greenhouse gas mixing ratios. This approach has been recommended in the white
paper report of NASA's ASCENDS mission (Jucks et al., 2015,
http://cce.nasa.gov/ascends_2015/index.html).
XCO2 measurements to cloud tops
During the ASCENDS airborne campaigns in the summers of 2011 and 2014 and
the winter of 2013, the CO2 Sounder made measurements to cloud tops
over the US West and Midwest. Retrievals of partial-column XCO2 were
made over low-level marine stratus clouds, cumulus clouds at the top of the PBL
with cumulonimbus during thunderstorms, mid-level altocumulus and visually thin cirrus clouds.
XCO2 measurements to the tops of marine stratus cloud
Marine stratus clouds exist over a large portion of the ocean adjacent to the west
side of continents where ocean currents are cold and a temperature inversion
layer is formed to condense the upward-moving moist air. Marine stratus
clouds are sheet-like clouds with a nearly horizontally uniform base and top
and shallow in depth. Once formed, they may be advected by the wind over
land areas. The 2011 ASCENDS airborne campaign had one flight over the
Pacific Ocean west of the California coastline on 2 August and flew over marine
stratus cloud decks (shown in the left of Fig. 8) with a cloud top elevation
of approximately 700 m. The campaign also utilized the Atmospheric Vertical
Observation of CO2 in the Earth's Troposphere gas analyzer (AVOCET; Vay et
al., 2011) on board for all flights to measure in situ CO2
concentration every 1 s. During spiral-down maneuvers, the AVOCET
measured the vertical profile of CO2 concentration. These were used to
compare to XCO2 retrievals from the CO2 Sounder lidar. The spiral-down maneuvers typically lasted less than 30 min.
The retrieval results are shown in Fig. 8. The right panel shows that the
partial-column XCO2 retrievals based on a 10 s average have
2–4 ppm standard deviation with biases less than 1 ppm over
all flight altitudes, compared to the in situ data from the AVOCET. The
retrievals with highest precision were from flight altitudes of 8–10 km,
indicating the optimal operating altitude for the lidar. At higher altitudes
there were fewer returned laser photons and noisier signals, while at
lower altitudes the path lengths were shorter and absorption signals
weaker. Overall, the retrievals results are comparable in quality to those
from other 2011 flights under clear conditions (Abshire et al., 2014).
XCO2 measurements to the tops of cumulus cloud
Cumulus clouds form as water vapor condenses in a strong, upward air current
above the Earth's surface. Cumulus clouds are often seen over land in the
afternoon during summertime after the land surface is fully heated by the Sun. Cumulus
clouds usually have flat bases but lumpy tops. Cumulus clouds grow upward
and can develop into a tower-like cumulonimbus, which is a thunderstorm
cloud.
The 10 August 2011 flight of the ASCENDS airborne campaign flew to Iowa near
the West Branch, Iowa, (WBI) tall tower. The flight passed over many isolated
cumulus clouds in the area with cloud tops ranging from 1950 to 2200 m near
the top of the PBL. Analysis of pulse echoes from both the cloud tops and the
ground within the 100 s data averaging time allows solving for the
partial-column XCO2 in the PBL by using the differential absorption line shape. The
results showed a strong seasonal drawdown over a cornfield in the area and were
consistent with the in situ AVOCET data (Ramanathan et al., 2015).
The XCO2 retrievals for lidar measurements to the tops of
broken cumulus clouds (a) and to the ground (b) on the
10 August 2011 ASCENDS flight over Iowa. The XCO2 values from the in situ
AVOCET gas analyzer are marked in black squares, and the values of XCO2
retrievals from CO2 Sounder measurements averaged over 10 s are marked
in red circles with error bars of ±1 standard deviation. The average
altitude of cloud tops (∼ 2 km) is plotted in the dashed line.
Summary plot of altitude-resolved lidar measurements for the sunset
ASCENDS flight to Iowa on 25 August 2014. The aircraft altitude is plotted as
the dotted black line, the ground elevation is plotted as the solid black
line, the altitudes of boundary layer cloud tops are plotted as the red
squares and the altitudes of mid-altitude clouds tops are plotted as the blue
triangles. Green boxes “A” and “B” are two segments selected for further
data analysis.
For this work, we performed XCO2 retrievals to the puffy cloud tops for
the same flight but use 10 s averaged data as shown in Fig. 2. Retrievals
made to the cumulus cloud tops near the spiral-down segment at the West
Branch tall tower had standard deviations of 3–6 ppm with average biases
less than 1 ppm (Fig. 9, left panel), except for the lowest altitude, where
the cloud tops were closer and data became noisier. These statistics are based on
retrievals within the spiral-down flight segment with limited sample size,
depending on cloud conditions.
Retrievals of XCO2 to the ground in the same segment showed results with
standard deviations of 2–4 ppm and with similar biases, shown in the right
panel of Fig. 9. A significant decrease in XCO2 was evident at lower
flight altitudes, caused by the large CO2 drawdown in the boundary layer
above the cornfield. In this region, the cumulus clouds act as a divider to
separate free-tropospheric CO2 from the boundary layer CO2, which are
involved in different physical processes. The difference between the two
XCO2 amounts allows for better estimates of surface sources and sinks
(Ramanathan et al., 2015).
During the ASCENDS sunset flight from California to Iowa and back on
25 August 2014, there were many cumulus clouds as shown in Fig. 6. Figure 10
illustrates the detected boundary layer clouds with cloud tops below 2 km
and the mid-level clouds with cloud tops around 4 km above ground. In the
middle of the flight, a cold front moved through the area, and cumulonimbus
clouds developed vertically and a thunderstorm was formed in the
region. The cloud top heights ranged from 2 km for PBL cumulus to as high as
3.5 km for cumulonimbus clouds, and the standard deviation of cloud top
height was more than 100 m as shown in Fig. 5. The measurement analysis
showed the average cloud reflectance was about 6 %, which is sufficient to
clearly show the gas absorption features across the measurement line and
enable quality retrievals of partial-column XCO2 to the cloud tops.
We show two segments during the flight to illustrate how XCO2
retrievals to cloud tops may be used to help resolve horizontal and vertical
gradients of atmospheric CO2 concentration. Both segments have longer
than 5 min continuous cloud covers and have more than 30 retrievals to
cloud tops for statistics. Segment A, marked in Fig. 10, is a 7 min long
segment (23:42–23:49 UTC) near the WBI tall tower during level flight at an
altitude of 5 km, while segment B is a 30 min long segment (02:30–03:00 UTC)
at a similar altitude on the way back to California after three
flights in a square pattern around the WBI tall tower. Most of the clouds in
segment A were PBL cumulus clouds that had cloud tops around 2 km above
ground. Some were higher cumulonimbus with cloud tops as high as 3.5 km. In
segment B most clouds were cumulus with slightly lower tops around 1.5 km,
and some were patchy altocumulus clouds with tops around 4 km, which can be
clearly seen in Fig. 11. These cloud covers and types can be also identified
from photos taken by a digital camera on board.
Over the 7 min segment A with a total of 40 retrievals the lidar
measurements of XCO2 to PBL cumulus cloud tops over a 10 s average had
a small bias of 0.2 ppm (395.2 ppm vs. 395.4 ppm of AVOCET) and a standard
deviation of 1.94 ppm. The XCO2 retrievals to the PBL cumulus cloud tops
from the lidar measurements in the 30 min long segment B had a standard
deviation of 1.85 ppm from a total of 114 retrievals and a mean value of 393 ppm,
which is 2.2 ppm lower than those in segment A.
Vertical cross sections of range-corrected backscattered pulse
energy for segment A and B marked in Fig. 10. The lidar returns from the
ground are at the bottom, and cloud returns are at a variety of altitudes from
1 to 4 km. The red lines on the top of plots indicate aircraft flight
altitudes.
The central location of segment B is about 250 km west of segment A.
Unfortunately there were no in situ vertical profile data with which to validate this
significant gradient. In this situation, CO2 concentration simulations
from the Parameterized Chemical Transport Model (PCTM; Kawa et al., 2004,
2010) were used for intercomparison. PCTM CO2 concentration simulation
is driven by meteorological data from the Modern-Era Retrospective analysis
for Research and Applications (MERRA) (Bosilovich, 2013), which is a NASA
reanalysis using GEOS-5. The vertical mixing profile in PCTM is
parameterized for both turbulence diffusion in the boundary layer and
convection. PCTM in this case is run at 1.25∘
longitude × 1.0∘ latitude with 56 hybrid vertical levels and outputs hourly, which should be
sufficient to resolve the gradient between these two locations, which are
2.4∘ longitude away, and measurements are 3 h apart.
Figure 12 shows the vertical profile of model CO2 for both segments.
Segment A had high CO2 concentration in the lower atmosphere. We infer
this was likely due to the mixing during the thunderstorm and subsequent
surface emission in the evening. The vertical profile in segment B shows a
typical summer nighttime vertical structure of CO2 concentration in the
area with overall low value in the lower atmosphere after daytime uptake by
growing vegetation but high values near the surface when surface uptake
stops and respiration starts. The difference in lidar measurements of
XCO2 to cloud tops by the lidar between segment A and B reflects these
two different processes and is consistent with PCTM model simulations. Our
XCO2 retrievals to mid-level cloud tops in the middle of segment B
(02:38–02:48 UTC) were back to a high value of 395.8 ppm, on average from 39
retrievals, which excludes the lower CO2 concentration below clouds.
During the same 10 min portion of the segment, our lidar measurements of
XCO2 to PBL cumulus cloud tops stayed at 393 ppm, averaged over 28
retrievals. We had 32 clear-sky full-column XCO2 retrievals to the
ground between the popcorn clouds during the 30 min segment. The average
value of full-column XCO2 was 389 ppm, which is about 4 ppm lower than
XCO2 to cumulus cloud tops and 7 ppm lower than that to the mid-level
cloud tops, as illustrated in Fig. 12. The XCO2 measurements to the
land surface had a standard deviation of 1.61 ppm, which, as expected, was
less than those to the cloud tops. In this case, the lidar measurements of
XCO2 to cloud tops allow us to distinguish both horizontal and vertical
gradients of atmospheric CO2 concentration.
Vertical profiles of CO2 mixing ratio on 25 August 2014 for the
central location of segment A at 41.1∘ N, 92.3∘ W in
black and of segment B at 41.3∘ N, 94.7∘ W in red from
the NASA Parameterized Chemical Transport Model. The XCO2 measurements
to ground, PBL cumulus clouds and mid-altitude altocumulus clouds from the
CO2 Sounder lidar for segment B are labeled. Flight
altitudes were around 5.5 km above sea level for both segments, shown as a red
dashed line.
A CO2 absorption line shape measured on 7 March 2013 to
cirrus cloud tops at 10.5 km altitude (a). The lidar measurements
are the blue circles, and the fitted line shape is the solid black line.
AVOCET in situ vertical profile of CO2 concentration is plotted in (b). The aircraft flight altitude was 12.1 km, and the lidar
range to cirrus cloud tops was 1.6 km.
XCO2 measurements to cirrus clouds
Cirrus clouds are thin and semi-transparent clouds, and are globally
widespread in the upper troposphere. Cirrus cloud height decreases with
latitude, following the tropopause height, and can be as low as
6–8 km at high latitudes and as high as 16–18 km in the tropics
(Sassen et al., 2008). The occurrence frequency of
cirrus clouds is about 17 % (Sassen et al., 2008) on a global average, but
it can be as high as 70 % (Nazaryan et al., 2008) in the equatorial
west-central Pacific Ocean, associated with deep convections at the
Intertropical Convergence Zone (ITCZ) and seasonal monsoon circulations.
Cirrus clouds are composed of ice crystals and strongly absorptive in our
CO2 measurement line (Wiscombe and Warren, 1980; Warren, 1984; Gosse et
al., 1995). Therefore, the laser backscatter from cirrus clouds is expected
to be substantially lower than from clouds composed of water droplets. The
reflectance of cirrus clouds varies with cloud physical and spatial
structure.
Some cirrus clouds encountered during the ASCENDS airborne campaigns were
dense and thick and had sufficient echo pulse energy to show clear CO2
absorption line shape. However, for most cases, the energy values were lower,
and the absorption line shapes are not sufficiently clear to allow quality
retrievals. Figure 13 shows an example of XCO2 retrievals to cirrus cloud
tops near the spiral-down flight segment in Iowa on 7 March 2013. The data
are averaged over 100 s and show a clear CO2 absorption line shape. The
aircraft altitude was 12.1 km, and the averaged cirrus cloud top height was
10.5 km. The lidar measurements show a retrieval of XCO2 of 392.8 ppm
to the cirrus cloud tops, which is lower than the full-column XCO2 to
the ground of 398 ppm. The lidar retrieval is consistent with in situ AVOCET
data of 392.4 ppm for the same layer average in the stratosphere.
Unfortunately, there were not enough cases with suitable cirrus cloud tops
during these three campaigns to allow calculation of statistics.
Discussion and conclusion
The pulsed multi-wavelength IPDA lidar approach allows accurate
determination of the photon path lengths and accurate retrieval of XCO2 to cloud tops.
Measurements to cloud tops and ground were made with the CO2 Sounder
lidar during the 2011, 2013 and 2014 ASCENDS airborne campaigns. These
measurements were used to study the XCO2 retrievals made to a variety
of cloud tops and to demonstrate the value of these retrievals in resolving
both horizontal and vertical gradients of atmospheric CO2. Measurements
were made over a variety of clouds, including cumulus and marine stratus at
the top of the boundary layer, mid-level altocumulus and cirrus. For all
clouds except cirrus, the data processing rate was greater than 90 %,
excluding cases when the aircraft was too close to cloud tops and when the aircraft
tilted substantially.
Analysis of the airborne campaign measurements showed that the laser pulse
energies from the tops of boundary layer clouds such as stratus and cumulus
were usually sufficient to allow clear identification of CO2 absorption
line shape and good retrievals of partial-column XCO2 to cloud tops. On
average, the reflectance of the boundary layer cloud tops was 5 %. In most
cases, the boundary layer clouds are too thick for laser pulse to penetrate
and allow ground echoes to return simultaneously. However, over broken
clouds, after averaging over 10 s of ground track or longer, both cloud and
ground returns were available. If clouds are patchy or broken, retrievals
of both XCO2 to the ground and to cloud tops simultaneously and the
difference between the two could be then used to estimate the residual
XCO2 in the boundary layer, whose value is the most sensitive to
surface carbon sources and sinks.
For passive remote-sensing approaches, cirrus clouds can significantly
modify the photon path length and cause a significant error in XCO2
retrievals. In contrast, the lidar measurements showed range-resolved pulse
echoes from semi-transparent cirrus clouds and the ground. In some cases those
could be used to retrieve full-column XCO2 to the ground and
partial-column XCO2 to cirrus and then to estimate tropospheric column
XCO2. However, in most cases during the campaigns, the backscattered
pulse energies from cirrus clouds were low, compared to other clouds such as
stratus and cumulus clouds. Only dense and thick (> 1.0 km)
cirrus clouds allowed detection of clear CO2 absorption line shapes and
thus yield good XCO2 retrievals. One limitation for these initial
airborne measurements was that cirrus clouds were at high altitude
(∼ 10 km) so that the column path length from aircraft
altitudes to the cloud tops was short and the CO2 absorption signal
was weak. For future space-based missions, the path length of pulse echoes
from cirrus clouds will be longer and the CO2 absorption will be
stronger, improving retrievals.
The quality of the CO2 Sounder retrievals is being improved with advancing
technologies for the laser and detector, toward the measurement goals of ASCENDS. Our results show that
XCO2 retrievals to the flat marine stratus cloud tops have the same
quality as those to the sea surface. That is probably because the higher
homogeneity of cloud reflectivity compensates well for the lower cloud
reflectivity at the measurement wavelengths and makes the SNRs for
returns from both the clouds and the surface almost identical (Amediek et al., 2017).
Meanwhile, when compared to in situ data with sufficient samples
(> 30), the XCO2 retrievals to the puffy cumulus cloud
tops near the West Branch tall tower in Iowa showed low bias
(∼ 0.2 ppm) and standard deviation of 1.9 ppm. In this case,
the standard deviation of XCO2 retrievals to the cumulus cloud tops
were increased by 20 %, compared to the standard deviation of 1.6 ppm for
the retrievals to the ground, mainly due to the larger cloud top roughness
as well as the lower cloud reflectivity at the measurement wavelengths.
Previous ASCENDS observing system simulation experiments (OSSEs) with
clear-sky measurements (Kawa et al., 2010; Hammerling et al., 2015) have
shown that lidar approaches have greater spatial and temporal coverage
than passive approaches and hence a higher potential to reduce uncertainties
in carbon budget estimates. Retrievals to all-level cloud tops with
corresponding measurement precision are planned to be included in future
OSSE studies to assess their impact on atmospheric transport modeling and
surface flux estimates.
Partial-column XCO2 retrievals to different cloud tops and to the
ground allow us to distinguish horizontal and vertical gradients of atmospheric
CO2. This measurement capability for the future space carbon missions
will be particularly valuable for the regions with persistent cloud covers.
These include tropical ITCZ, west coasts of continents with marine layer
clouds, and the Southern Ocean with the highest occurrence of low-level clouds, where
underneath carbon cycles are active but where measurements from passive
satellite-based spectrometers are limited. Lidar-based measurements to cloud
tops will fill these significant gaps, provide a more complete picture of
the CO2 distribution and benefit atmospheric transport modeling as
well as global and regional carbon budget estimates.
Data availability
All of the data used in this work are available from the primary author.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
This work was supported by the NASA ESTO IIP program and the NASA ASCENDS
mission pre-formulation activity. We gratefully acknowledge the work of the DC-8 team
at NASA Armstrong Flight Center for helping plan and conduct the flight
campaigns. We also would like to thank two anonymous reviewers for their
careful reviews and recommendations. Edited by: Gerhard Ehret
Reviewed by: two anonymous referees
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