Explore the vast range of titles available.

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 2 ) is altering the productivity of the biosphere and the uptake of CO 2 by the oceans. Launched on 2 July 2014, OCO-2 provides retrievals of the column-averaged CO 2 dry-air mole fraction ( X CO 2 ) 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 X CO 2 during summer. Launched just before one of the most intense El Niños of the past century, OCO-2 measurements of X CO 2 and fluorescence record the impact of the large change in ocean temperature and rainfall on uptake and release of CO 2 by the oceans and biosphere.

Quantifying gross primary production (GPP) remains a major challenge in global carbon cycle research. Spaceborne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. Orbiting Carbon Observatory-2 (OCO-2)’s SIF data acquisition and fine spatial resolution permit direct validation against ground and airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations of the robustness of such a relationship across more biomes. Our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.

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.

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO2. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green's function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean pCO2 and air‐sea CO2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO2 uptake occur in subpolar seasonally stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean global ocean CO2 sink (2.47 ± 0.50 Pg C year−1) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies. Plain Language Summary Data‐driven estimates of how much carbon dioxide the ocean is absorbing (the so‐called “ocean carbon sink”) have improved substantially in recent years. However, computational ocean models that include biogeochemistry continue to play a critical role as they allow us to isolate and understand the individual processes that control ocean carbon sequestration. The ideal scenario is a combination of the above two methods, where data are ingested and then used to improve a model's fit to the observed ocean, also known as, data assimilation. While the physical oceanographic community has made great progress in developing data assimilation systems, for example, the Estimating the Circulation and Climate of the Ocean (ECCO) consortium, the biogeochemical community has generally lagged behind. The ECCO‐Darwin model presented in this paper represents an important technological step forward as it is the first global ocean biogeochemistry model that (1) ingests both physical and biogeochemical observations into the model in a realistic manner and (2) considers how the nature of the ocean carbon sink has changed over multiple decades. As the ECCO ocean circulation estimates become more accurate and lengthen in time, ECCO‐Darwin will become an ever more accurate and useful tool for climate‐related ocean carbon cycle and mitigation studies. Key Points ECCO‐Darwin is a global ocean biogeochemistry model that assimilates physical and biogeochemical observations in a conserving manner Air‐sea CO2 fluxes over seasonal to multidecadal timescales (1995–2017) are largely consistent with interpolation‐based products Contrary to interpolation‐based products, ECCO‐Darwin is impervious to sparse and irregularly sampled observations

Protection against Mycobacterium tuberculosis (Mtb) infection requires CD4 T cells to migrate into the lung and interact with infected macrophages. In mice, less-differentiated CXCR3+ CD4 T cells migrate into the lung and suppress growth of Mtb, whereas CX3CR1+ terminally differentiated Th1 cells accumulate in the blood vasculature and do not control pulmonary infection. Here we examine CD4 T-cell differentiation and lung homing during primary Mtb infection of rhesus macaques. Mtb-specific CD4 T cells simultaneously appeared in the airways and blood ∼21–28 days post exposure, indicating that recently primed effectors are quickly recruited into the lungs after entering circulation. Mtb-specific CD4 T cells in granulomas display a tissue-parenchymal CXCR3+CX3CR1−PD-1hiCTLA-4+ phenotype. However, most granuloma CD4 T cells are found within the outer lymphocyte cuff and few localize to the myeloid cell core containing the bacilli. Using the intravascular stain approach, we find essentially all Mtb-specific CD4 T cells in granulomas have extravasated across the vascular endothelium into the parenchyma. Therefore, it is unlikely to be that lung-homing defects introduced by terminal differentiation limit the migration of CD4 T cells into granulomas following primary Mtb infection of macaques. However, intralesional positioning defects within the granuloma may pose a major barrier to T-cell-mediated immunity during tuberculosis.

We quantify how well column-integrated CO2 measurements from the Orbiting Carbon Observatory (OCO) should be able to constrain surface CO2 fluxes, given the presence of various error sources. We use variational data assimilation to optimize weekly fluxes at a 2°×5° resolution (lat/lon) using simulated data averaged across each model grid box overflight (typically every ~33 s). Grid-scale simulations of this sort have been carried out before for OCO using simplified assumptions for the measurement error. Here, we more accurately describe the OCO measurements in two ways. First, we use new estimates of the single-sounding retrieval uncertainty and averaging kernel, both computed as a function of surface type, solar zenith angle, aerosol optical depth, and pointing mode (nadir vs. glint). Second, we collapse the information content of all valid retrievals from each grid box crossing into an equivalent multi-sounding measurement uncertainty, factoring in both time/space error correlations and data rejection due to clouds and thick aerosols. Finally, we examine the impact of three types of systematic errors: measurement biases due to aerosols, transport errors, and mistuning errors caused by assuming incorrect statistics. When only random measurement errors are considered, both nadir- and glint-mode data give error reductions over the land of ~45% for the weekly fluxes, and ~65% for seasonal fluxes. Systematic errors reduce both the magnitude and spatial extent of these improvements by about a factor of two, however. Improvements nearly as large are achieved over the ocean using glint-mode data, but are degraded even more by the systematic errors. Our ability to identify and remove systematic errors in both the column retrievals and atmospheric assimilations will thus be critical for maximizing the usefulness of the OCO data.

Knowledge of carbon exchange between the atmosphere, land and the oceans is important, given that the terrestrial and marine environments are currently absorbing about half of the carbon dioxide that is emitted by fossil-fuel combustion. This carbon uptake is therefore limiting the extent of atmospheric and climatic change, but its long-term nature remains uncertain. Here we provide an overview of the current state of knowledge of global and regional patterns of carbon exchange by terrestrial ecosystems. Atmospheric carbon dioxide and oxygen data confirm that the terrestrial biosphere was largely neutral with respect to net carbon exchange during the 1980s, but became a net carbon sink in the 1990s. This recent sink can be largely attributed to northern extratropical areas, and is roughly split between North America and Eurasia. Tropical land areas, however, were approximately in balance with respect to carbon exchange, implying a carbon sink that offset emissions due to tropical deforestation. The evolution of the terrestrial carbon sink is largely the result of changes in land use over time, such as regrowth on abandoned agricultural land and fire prevention, in addition to responses to environmental changes, such as longer growing seasons, and fertilization by carbon dioxide and nitrogen. Nevertheless, there remain considerable uncertainties as to the magnitude of the sink in different regions and the contribution of different processes.

Measurements of atmospheric carbon dioxide and satellite-derived measurements of temperature and the vegetation index were used to investigate relationships among climate, carbon dioxide, and ecosystems. At the global scale, lagged correlations between temperature and carbon dioxide growth rate were found, indicating modulation by biogeochemical feedbacks. Spatial analysis of the temperature and vegetation index data suggests that the global correlations are a composite of individualistic responses of different ecosystems. The existence of biome-specific time scales of response implies that changes in global ecosystem distributions could indirectly alter the relationships between climate and carbon storage.

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment. Plain Language Summary The iconic CO2 data set initiated by C.D. Keeling at Mauna Loa, Hawaii has been instrumental in our understanding of the global carbon cycle and underpins policy efforts aimed to mitigate carbon emissions and climate change impacts. As our knowledge of the carbon cycle grows, it becomes increasingly critical to acquire information at finer spatial scales to better understand the complexity of carbon movement across the ocean and land. At the same time, policies that seek to mitigate carbon emissions benefit from observations to guide actions at city‐to‐national scales. The scientific community has developed a suite of carbon observations spanning multiple scales, demanding traceability, integration, and global context. Satellite measurements can fill this role but rely on further efforts to link with natural and anthropogenic processes. In this position paper, carbon cycle scientists call for an integrated carbon observing system leveraging near‐surface partial‐column Greenhouse Gas data—capturing the atmosphere closest to forests, cities, and oceans—to better resolve finer spatial scales (<100 km) where key carbon cycle processes and management decisions occur. This system should be anchored by ground observations that are not dependent on any single nation‐state to provide internationally recognized carbon emissions products for policy and planning. Key Points Managing carbon stocks under climate forcing requires a global view of local and regional scale processes Near surface partial column Greenhouse Gas data can improve the ability to resolve carbon fluxes at assessment and management scales (<100 km) A carbon observation system providing actionable information should integrate partial columns with sustained Earth observations and models