NASA's Orbiting Carbon Observatory-2 (OCO-2) mission was motivated by the need to diagnose how the increasing concentration of atmospheric carbon dioxide (CO
) is altering the productivity of the ...biosphere and the uptake of CO
by the oceans. Launched on 2 July 2014, OCO-2 provides retrievals of the column-averaged CO
dry-air mole fraction (Formula: see text) as well as the fluorescence from chlorophyll in terrestrial plants. The seasonal pattern of uptake by the terrestrial biosphere is recorded in fluorescence and the drawdown of Formula: see text during summer. Launched just before one of the most intense El Niños of the past century, OCO-2 measurements of Formula: see text and fluorescence record the impact of the large change in ocean temperature and rainfall on uptake and release of CO
by the oceans and biosphere.
The seasonal cycle accounts for a dominant mode of total column CO2 (XCO2) annual variability and is connected to CO2 uptake and release; it thus represents an important quantity to test the accuracy ...of the measurements from space. We quantitatively evaluate the XCO2 seasonal cycle of the Greenhouse Gases Observing Satellite (GOSAT) observations from the Atmospheric CO2 Observations from Space (ACOS) retrieval system and compare average regional seasonal cycle features to those directly measured by the Total Carbon Column Observing Network (TCCON). We analyse the mean seasonal cycle amplitude, dates of maximum and minimum XCO2, as well as the regional growth rates in XCO2 through the fitted trend over several years. We find that GOSAT/ACOS captures the seasonal cycle amplitude within 1.0 ppm accuracy compared to TCCON, except in Europe, where the difference exceeds 1.0 ppm at two sites, and the amplitude captured by GOSAT/ACOS is generally shallower compared to TCCON. This bias over Europe is not as large for the other GOSAT retrieval algorithms (NIES v02.21, RemoTeC v2.35, UoL v5.1, and NIES PPDF-S v.02.11), although they have significant biases at other sites. We find that the ACOS bias correction partially explains the shallow amplitude over Europe. The impact of the co-location method and aerosol changes in the ACOS algorithm were also tested and found to be few tenths of a ppm and mostly non-systematic. We find generally good agreement in the date of minimum XCO2 between ACOS and TCCON, but ACOS generally infers a date of maximum XCO2 2–3 weeks later than TCCON. We further analyse the latitudinal dependence of the seasonal cycle amplitude throughout the Northern Hemisphere and compare the dependence to that predicted by current optimized models that assimilate in situ measurements of CO2. In the zonal averages, models are consistent with the GOSAT amplitude to within 1.4 ppm, depending on the model and latitude. We also show that the seasonal cycle of XCO2 depends on longitude especially at the mid-latitudes: the amplitude of GOSAT XCO2 doubles from western USA to East Asia at 45–50° N, which is only partially shown by the models. In general, we find that model-to-model differences can be larger than GOSAT-to-model differences. These results suggest that GOSAT/ACOS retrievals of the XCO2 seasonal cycle may be sufficiently accurate to evaluate land surface models in regions with significant discrepancies between the models.
The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first satellite designed to measure atmospheric carbon dioxide (CO2) with the precision, resolution, and coverage necessary to quantify regional ...carbon sources and sinks. OCO-2 launched on 2 July 2014, and during the first 2 years of its operation, a major El Niño occurred: the 2015-2016 El Niño, which was one of the strongest events ever recorded.El Niño and its cold counterpart La Niña (collectively known as the El Niño-Southern Oscillation or ENSO) are the dominant modes of tropical climate variability. ENSO originates in the tropical Pacific Ocean but spurs a variety of anomalous weather patterns around the globe. Not surprisingly, it also leaves an imprint on the global carbon cycle. Understanding the magnitude and phasing of the ENSO-CO2 relationship has important implications for improving the predictability of carbon-climate feedbacks.The high-density observations from NASA's OCO-2 mission, coupled with surface ocean CO2 measurements from NOAA buoys, have provided us with a unique data set to track the atmospheric CO2 concentrations and unravel the timing of the response of the ocean and the terrestrial carbon cycle during the 2015-2016 El Niño.During strong El Niño events, there is an overall increase in global atmospheric CO2 concentrations. This increase is predominantly due to the response of the terrestrial carbon cycle to El Niño-induced changes in weather patterns. But along with the terrestrial component, the tropical Pacific Ocean also plays an important role. Typically, the tropical Pacific Ocean is a source of CO2 to the atmosphere due to equatorial upwelling that brings CO2-rich water from the interior ocean to the surface. During El Niño, this equatorial upwelling is suppressed in the eastern and the central Pacific Ocean, reducing the supply of CO2 to the surface. If CO2 fluxes were to remain constant elsewhere, this reduction in ocean-to-atmosphere CO2 fluxes should contribute to a slowdown in the growth of atmospheric CO2. This hypothesis cannot be verified, however, without large-scale CO2 observations over the tropical Pacific Ocean.OCO-2 observations confirm that the tropical Pacific Ocean played an early and important role in the response of atmospheric CO2 concentrations to the 2015-2016 El Niño. By analyzing trends in the time series of atmospheric CO2, we see clear evidence of an initial decrease in atmospheric CO2 concentrations over the tropical Pacific Ocean, specifically during the early stages of the El Niño event (March through July 2015). Atmospheric CO2 concentration anomalies suggest a flux reduction of 26 to 54% that is validated by the NOAA Tropical Atmosphere Ocean (TAO) mooring CO2 data. Both the OCO-2 and TAO data further show that the reduction in ocean-to-atmosphere fluxes is spatially variable and has strong gradients across the tropical Pacific Ocean.During the later stages of the El Niño (August 2015 and later), the OCO-2 observations register a rise in atmospheric CO2 concentrations. We attribute this increase to the response from the terrestrial component of the carbon cycle--a combination of reduction in biospheric uptake of CO2 over pan-tropical regions and an enhancement in biomass burning emissions over Southeast Asia and Indonesia. The net impact of the 2015-2016 El Niño event on the global carbon cycle is an increase in atmospheric CO2 concentrations, which would likely be larger if it were not for the reduction in outgassing from the ocean.The strong El Niño event of 2015-2016 provided us with an opportunity to study how the global carbon cycle responds to a change in the physical climate system. Space-based observations of atmospheric CO2, such as from OCO-2, allow us to observe and monitor the temporal sequence of El Niño-induced changes in CO2 concentrations. Disentangling the timing of the ocean and terrestrial responses is the first step toward interpreting their relative contribution to the global atmospheric CO2 growth rate, and thereby understanding the sensitivity of the carbon cycle to climate forcing on interannual to decadal time scales.The tropical Pacific Ocean, the center of action during an El Niño event, is shown in cross section. Warm ocean surface temperatures are shown in red, cooler waters in blue. The Niño 3.4 region, which scientists use to study the El Niño, is denoted by yellow dashed lines. As a result of OCO-2's global coverage and 16-day repeat cycle, it flies over the entire region every few days, keeping tabs on the changes in atmospheric CO2 concentration. Spaceborne observations of carbon dioxide (CO2) from the Orbiting Carbon Observatory-2 are used to characterize the response of tropical atmospheric CO2 concentrations to the strong El Niño event of 2015-2016. Although correlations between the growth rate of atmospheric CO2 concentrations and the El Niño-Southern Oscillation are well known, the magnitude of the correlation and the timing of the responses of oceanic and terrestrial carbon cycle remain poorly constrained in space and time. We used space-based CO2 observations to confirm that the tropical Pacific Ocean does play an early and important role in modulating the changes in atmospheric CO2 concentrations during El Niño events--a phenomenon inferred but not previously observed because of insufficient high-density, broad-scale CO2 observations over the tropics.
The Orbiting Carbon Observatory-2 (OCO-2), launched on 2 July 2014, is a NASA mission designed to measure the column-averaged CO2 dry air mole fraction, XCO2. Towards that goal, it will collect ...spectra of reflected sunlight in narrow spectral ranges centered at 0.76, 1.6 and 2.0 μm with a resolving power (λ/Δ λ) of 20 000. These spectra will be used in an optimal estimation framework to retrieve XCO2. About 100 000 cloud free soundings of XCO2 each day will allow estimates of net CO2 fluxes on regional to continental scales to be determined. Here, we evaluate the OCO-2 spectrometer performance using pre-launch data acquired during instrument thermal vacuum tests in April 2012. A heliostat and a diffuser plate were used to feed direct sunlight into the OCO-2 instrument and spectra were recorded. These spectra were compared to those collected concurrently from a nearby high-resolution Fourier Transform Spectrometer that was part of the Total Carbon Column Observing Network (TCCON). Using the launch-ready OCO-2 calibration and spectroscopic parameters, we performed total column scaling fits to all spectral bands and compared these to TCCON results. On 20 April, we detected a CO2 plume from the Los Angeles basin at the JPL site with strongly enhanced short-term variability on the order of 1% (3–4 ppm). We also found good (< 0.5 ppm) inter-footprint consistency in retrieved XCO2. The variations in spectral fitting residuals are consistent with signal-to-noise estimates from instrument calibration, while average residuals are systematic and mostly attributable to remaining errors in our knowledge of the CO2 and O2 spectroscopic parameters. A few remaining inconsistencies observed during the tests may be attributable to the specific instrument setup on the ground and will be re-evaluated with in-orbit data.
The Orbiting Carbon Observatory-3 (OCO-3) is NASA's next instrument dedicated to extending the record of
the dry-air mole fraction of column carbon dioxide (XCO2) and solar-induced fluorescence (SIF) ...measurements from space.
The current schedule calls for a launch from the Kennedy Space Center no earlier than April 2019 via a Space-X Falcon 9 and Dragon capsule.
The instrument will be installed as an external payload on the Japanese Experimental Module Exposed Facility (JEM-EF)
of the International Space Station (ISS) with a nominal mission lifetime of 3 years.
The precessing orbit of the ISS will allow for viewing of the Earth at all latitudes less than approximately 52∘,
with a ground repeat cycle that is much more complicated than the polar-orbiting satellites
that so far have carried all of the instruments capable of measuring carbon dioxide from space. The grating spectrometer at the core of OCO-3 is a direct copy of the OCO-2 spectrometer,
which was launched into a polar orbit in July 2014.
As such, OCO-3 is expected to have similar instrument sensitivity and performance characteristics to OCO-2,
which provides measurements of XCO2 with precision better than 1 ppm
at 3 Hz, with each viewing frame containing eight footprints approximately 1.6 km by 2.2 km in size.
However, the physical configuration of the instrument aboard the ISS, as well as the use of a new pointing mirror assembly (PMA),
will alter some of the characteristics of the OCO-3 data compared to OCO-2.
Specifically, there will be significant differences from day to day in the sampling locations and time of day.
In addition, the flexible PMA system allows for a much more dynamic observation-mode schedule. This paper outlines the science objectives of the OCO-3 mission and, using a simulation of 1 year of global observations,
characterizes the spatial sampling, time-of-day coverage, and anticipated data quality of the simulated L1b.
After application of cloud and aerosol prescreening, the L1b radiances are run through the operational L2 full physics retrieval algorithm,
as well as post-retrieval filtering and bias correction,
to examine the expected coverage and quality of the retrieved XCO2 and to show how the measurement objectives are met.
In addition, results of the SIF from the IMAP–DOAS algorithm are analyzed.
This paper focuses only on the nominal nadir–land and glint–water observation modes,
although on-orbit measurements will also be made in transition and target modes, similar to OCO-2,
as well as the new snapshot area mapping (SAM) mode.
Despite its key role in climate change, large uncertainties persist in our knowledge of the anthropogenic emissions of carbon dioxide (CO2) and no global observing system exists that allows us to ...monitor emissions from localized CO2 sources with sufficient accuracy. The Orbiting Carbon Observatory-2 (OCO-2) satellite allows retrievals of the column-average dry-air mole fractions of CO2 (XCO2). However, regional column-average enhancements of individual point sources are usually small, compared to the background concentration and its natural variability, and often not much larger than the satellite's measurement noise. This makes the unambiguous identification and quantification of anthropogenic emission plume signals challenging. NO2 is co-emitted with CO2 when fossil fuels are combusted at high temperatures. It has a short lifetime on the order of hours so that NO2 columns often greatly exceed background and noise levels of modern satellite sensors near sources, which makes it a suitable tracer of recently emitted CO2. Based on six case studies (Moscow, Russia; Lipetsk, Russia; Baghdad, Iraq; Medupi and Matimba power plants, South Africa; Australian wildfires; and Nanjing, China), we demonstrate the usefulness of simultaneous satellite observations of NO2 and XCO2. For this purpose, we analyze co-located regional enhancements of XCO2 observed by OCO-2 and NO2 from the Sentinel-5 Precursor (S5P) satellite and estimate the CO2 plume's cross-sectional fluxes. We take advantage of the nearly simultaneous NO2 measurements with S5P's wide swath and small measurement noise by identifying the source of the observed XCO2 enhancements, excluding interference with remote upwind sources, allowing us to adjust the wind direction, and by constraining the shape of the CO2 plumes. We compare the inferred cross-sectional fluxes with the Emissions Database for Global Atmospheric Research (EDGAR), the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC), and, in the case of the Australian wildfires, with the Global Fire Emissions Database (GFED). The inferred cross-sectional fluxes range from 31 MtCO2 a−1 to 153 MtCO2 a−1 with uncertainties (1σ) between 23 % and 72 %. For the majority of analyzed emission sources, the estimated cross-sectional fluxes agree, within their uncertainty, with either EDGAR or ODIAC or lie somewhere between them. We assess the contribution of multiple sources of uncertainty and find that the dominating contributions are related to the computation of the effective wind speed normal to the plume's cross section. The flux uncertainties are expected to be reduced by the planned European Copernicus anthropogenic CO2 monitoring mission (CO2M), which will provide not only precise measurements with high spatial resolution but also imaging capabilities with a wider swath of simultaneous XCO2 and NO2 observations. Such a mission, particularly if performed by a constellation of satellites, will deliver CO2 emission estimates from localized sources at an unprecedented frequency and level of accuracy.
We study an ensemble of six multi-year global Bayesian
carbon dioxide (CO2) atmospheric inversions that vary in terms of assimilated
observations (either column retrievals from one of two satellites ...or surface
air sample measurements) and transport model. The time series of inferred
annual fluxes are first compared with each other at various spatial scales.
We then objectively evaluate the small inversion ensemble based on a large
dataset of accurate aircraft measurements in the free troposphere over the
globe, which are independent of all assimilated data. The measured
variables are connected with the inferred fluxes through mass-conserving
transport in the global atmosphere and are part of the inversion results.
Large-scale annual fluxes estimated from the bias-corrected land retrievals
of the second Orbiting Carbon Observatory (OCO-2) differ greatly from the prior
fluxes, but are similar to the fluxes estimated from the surface
network within the uncertainty of these surface-based estimates. The OCO-2-based and surface-based inversions have similar performance when projected in the
space of the aircraft data, but the relative strengths and weaknesses of the two
flux estimates vary within the northern and tropical parts of the
continents. The verification data also suggest that the more complex and
more recent transport model does not improve the inversion skill. In
contrast, the inversion using bias-corrected retrievals from the Greenhouse
Gases Observing Satellite (GOSAT) or, to a larger extent, a non-Bayesian
inversion that simply adjusts a recent bottom-up flux estimate with the
annual growth rate diagnosed from marine surface measurements both estimate much
different fluxes and fit the aircraft data less. Our study highlights a way
to rate global atmospheric inversions. Without any general claim regarding the
usefulness of all OCO-2 retrieval datasets vs. all GOSAT retrieval datasets,
it still suggests that some satellite retrievals can now provide inversion
results that are, despite their uncertainty, comparable with respect to credibility to
traditional inversions using the accurate but sparse surface network and
that are therefore complementary for studies of the global carbon budget.
We assess the large-scale, top-down constraints on regional fossil fuel emissions provided by observations of atmospheric total column CO2, XCO2. Using an atmospheric general circulation model (GCM) ...with underlying fossil emissions, we determine the influence of regional fossil fuel emissions on global XCO2 fields. We quantify the regional contrasts between source and upwind regions and probe the sensitivity of atmospheric XCO2 to changes in fossil fuel emissions. Regional fossil fuel XCO2 contrasts can exceed 0.7 ppm based on 2007 emission estimates, but have large seasonal variations due to biospheric fluxes. Contamination by clouds reduces the discernible fossil signatures. Nevertheless, our simulations show that atmospheric fossil XCO2 can be tied to its source region and that changes in the regional XCO2 contrasts scale linearly with emissions. We test the GCM results against XCO2 data from the GOSAT satellite. Regional XCO2 contrasts in GOSAT data generally scale with the predictions from the GCM, but the comparison is limited by the moderate precision of and relatively few observations from the satellite. We discuss how this approach may be useful as a policy tool to verify national fossil emissions, as it provides an independent, observational constraint.
The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric ...inversion methods combined with column average CO2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques, and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within the ensemble spread, in situ observations, and satellite retrievals constrain a similar global total carbon sink of 3.7±0.5 PgC yr−1, and 1.5±0.6 PgC yr−1 for global land, for the 2015–2016 annual mean. This agreement breaks down in smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015–2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there.
All measurements of XCO2 from space have systematic errors. To reduce a large fraction of these errors, a bias correction is applied toXCO2 retrieved from GOSAT and OCO-2 spectra using the ACOS ...retrieval algorithm. The bias correction uses, among other parameters, the surface pressure difference between the retrieval and the meteorological reanalysis. Relative errors in the surface pressure estimates, however, propagate nearly 1:1 into relative errors in bias-correctedXCO2. For OCO-2, small errors in the knowledge of the pointing of the observatory (up to ∼130 arcsec) introduce a bias inXCO2 in regions with rough topography. Erroneous surface pressure estimates are also caused by a coding error in ACOS version 8, sampling meteorological analyses at wrong times (up to 3 h after the overpass time). Here, we derive new geolocations for OCO-2's eight footprints and show how using improved knowledge of surface pressure estimates in the bias correction reduces errors in OCO-2's v9 XCO2 data.
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