5 research outputs found

    Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China

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    Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO₂ concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO₂ dry air mole fraction (XCO₂) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO₂ changes during growing season for 13 years. We derived a relationship between XCO₂ and surface net CO₂ fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO₂ flux enhancement based on satellite observed XCO₂ changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO₂ emissions, we estimated an enhanced XCO₂ drawdown during the GP of −0.070 to −0.084 ppm yr⁻¹. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO₂ to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord

    Multiscale assessment of North American terrestrial carbon balance

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    Comparisons of carbon uptake estimates from bottom-up terrestrial biosphere models (TBMs) to top-down atmospheric inversions help assess how well we understand carbon dioxide (CO2) exchange between the atmosphere and terrestrial biosphere. Previous comparisons have shown varying levels of agreement between bottom-up and top-down approaches, but they have almost exclusively focused on large, aggregated scales (e.g., global or continental), providing limited insights into reasons for the mismatches. Here we explore how consistency, defined as the spread in net ecosystem exchange (NEE) estimates within an ensemble of TBMs or inversions, varies with at finer spatial scales ranging from 1∘×1∘ to the continent of North America. We also evaluate how well consistency informs accuracy in overall NEE estimates by filtering models based on their agreement with the variability, magnitude, and seasonality in observed atmospheric CO2 drawdowns or enhancements. We find that TBMs produce more consistent estimates of NEE for most regions and at most scales relative to inversions. Filtering models using atmospheric CO2 metrics causes ensemble spread to decrease substantially for TBMs, but not for inversions. This suggests that ensemble spread is likely not a reliable measure of the uncertainty associated with the North American carbon balance at any spatial scale. Promisingly, applying atmospheric CO2 metrics leads to a set of models with converging flux estimates across TBMs and inversions. Overall, we show that multiscale assessment of the agreement between bottom-up and top-down NEE estimates, aided by regional-scale observational constraints is a promising path towards identifying fine-scale sources of uncertainty and improving both ensemble consistency and accuracy. These findings help refine our understanding of biospheric carbon balance, particularly at scales relevant for informing regional carbon-climate feedbacks.</p

    Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2)

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    Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes

    Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia

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    There are still large uncertainties in the estimates of net ecosystem exchange of CO2 (NEE) with atmosphere in Asia, particularly in the boreal and eastern part of temperate Asia. To understand these uncertainties, we assessed the CarbonTracker Asia (CTA2017) estimates of the spatial and temporal distributions of NEE through a comparison with FLUXCOM and the global inversion models from the Copernicus Atmospheric Monitoring Service (CAMS), Monitoring Atmospheric Composition and Climate (MACC), and Jena CarboScope in Asia, as well as examining the impact of the nesting approach on the optimized NEE flux during the 2001&ndash;2013 period. The long-term mean carbon uptake is reduced in Asia, which is &minus;0.32 &plusmn; 0.22 PgC yr&minus;1, whereas &minus;0.58 &plusmn; 0.26 PgC yr&minus;1 is shown from CT2017 (CarbonTracker global). The domain aggregated mean carbon uptake from CTA2017 is found to be lower by 23.8%, 44.8%, and 60.5% than CAMS, MACC, and Jena CarboScope, respectively. For example, both CTA2017 and CT2017 models captured the interannual variability (IAV) of the NEE flux with a different magnitude and this leads to divergent annual aggregated results. Differences in the estimated interannual variability of NEE in response to El Ni&ntilde;o&ndash;Southern Oscillation (ENSO) may result from differences in the transport model resolutions. These inverse models&rsquo; results have a substantial difference compared to FLUXCOM, which was found to be &minus;5.54 PgC yr&minus;1. On the one hand, we showed that the large NEE discrepancies between both inversion models and FLUXCOM stem mostly from the tropical forests. On the other hand, CTA2017 exhibits a slightly better correlation with FLUXCOM over grass/shrub, fields/woods/savanna, and mixed forest than CT2017. The land cover inconsistency between CTA2017 and FLUXCOM is therefore one driver of the discrepancy in the NEE estimates. The diurnal averaged NEE flux between CTA2017 and FLUXCOM exhibits better agreement during the carbon uptake period than the carbon release period. Both CTA2017 and CT2017 revealed that the overall spatial patterns of the carbon sink and source are similar, but the magnitude varied with seasons and ecosystem types, which is mainly attributed to differences in the transport model resolutions. Our findings indicate that substantial inconsistencies in the inversions and FLUXCOM mainly emerge during the carbon uptake period and over tropical forests. The main problems are underrepresentation of FLUXCOM NEE estimates by limited eddy covariance flux measurements, the role of CO2 emissions from land use change not accounted for by FLUXCOM, sparseness of surface observations of CO2 concentrations used by the assimilation systems, and land cover inconsistency. This suggested that further scrutiny on the FLUXCOM and inverse estimates is most likely required. Such efforts will reduce inconsistencies across various NEE estimates over Asia, thus mitigating ecosystem-driven errors that propagate the global carbon budget. Moreover, this work also recommends further investigation on how the changes/updates made in CarbonTracker affect the interannual variability of the aggregate and spatial pattern of NEE flux in response to the ENSO effect over the region of interest
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