Plumbing the Global Carbon Cycle: Integrating Inland Waters into the Terrestrial Carbon Budget

Ecosystems ◽  
2007 ◽  
Vol 10 (1) ◽  
pp. 172-185 ◽  
Author(s):  
J. J. Cole ◽  
Y. T. Prairie ◽  
N. F. Caraco ◽  
W. H. McDowell ◽  
L. J. Tranvik ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Global Carbon Cycle ◽  
Inland Waters ◽  
Terrestrial Carbon ◽  
Global Carbon

scholarly journals Emissions from dry inland waters are a blind spot in the global carbon cycle

2019 ◽  
Vol 188 ◽  
pp. 240-248 ◽  
Author(s):  
Rafael Marcé ◽  
Biel Obrador ◽  
Lluís Gómez-Gener ◽  
Núria Catalán ◽  
Matthias Koschorreck ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Blind Spot ◽  
Inland Waters ◽  
Global Carbon

scholarly journals A global CO<sub>2</sub> flux dataset (2015–2019) inferred from OCO-2 retrievals using the Tan-Tracker inversion system

2021 ◽  
Author(s):  
Zhe Jin ◽  
Xiangjun Tian ◽  
Rui Han ◽  
Yu Fu ◽  
Xin Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Carbon Cycle ◽  
Carbon Flux ◽  
Carbon Budget ◽  
Terrestrial Ecosystem ◽  
Carbon Fluxes ◽  
Global Carbon Cycle ◽  
Ocean Carbon ◽  
Global Carbon ◽  
Regional Fluxes

Abstract. Accurate assessment of the various sources and sinks of carbon dioxide (CO2), especially terrestrial ecosystem and ocean fluxes with high uncertainties, is important for understanding of the global carbon cycle, supporting the formulation of climate policies, and projecting future climate change. Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) are being widely used to improve carbon flux estimation due to their broad spatial coverage. However, there is no consensus on the robust estimates of regional fluxes. In this study, we present a global and regional resolved terrestrial ecosystem carbon flux (NEE) and ocean carbon flux dataset for 2015–2019. The dataset was generated using the Tan-Tracker inversion system by assimilating Observing Carbon Observatory 2 (OCO-2) column CO2 retrievals. The posterior NEE and ocean carbon fluxes were comprehensively validated by comparing posterior simulated CO2 concentrations with OCO-2 independent retrievals and Total Carbon Column Observing Network (TCCON) measurements. The validation showed that posterior carbon fluxes significantly improved the modelling of atmospheric CO2 concentrations, with global mean biases of 0.33 ppm against OCO-2 retrievals and 0.12 ppm against TCCON measurements. We described the characteristics of the dataset at global, regional, and Tibetan Plateau scales in terms of the carbon budget, annual and seasonal variations, and spatial distribution. The posterior 5-year annual mean global atmospheric CO2 growth rate was 5.35 PgC yr−1, which was within the uncertainty of the Global Carbon Budget 2020 estimate (5.49 PgC yr−1). The posterior annual mean NEE and ocean carbon fluxes were −4.07 and −3.33 PgC yr−1, respectively. Regional fluxes were analysed based on TransCom partitioning. All 11 land regions acted as carbon sinks, except for Tropical South America, which was almost neutral. The strongest carbon sinks were located in Boreal Asia, followed by Temperate Asia and North Africa. The entire Tibetan Plateau ecosystem was estimated as a carbon sink, taking up −49.52 TgC yr−1 on average, with the strongest sink occurring in eastern alpine meadows. These results indicate that our dataset captures surface carbon fluxes well and provides insight into the global carbon cycle. The dataset can be accessed at https://doi.org/10.11888/Meteoro.tpdc.271317 (Jin et al., 2021).

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Full Description ◽  
Model Data ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrological, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification 5 of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by model-data fusion or data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation, and systematic and 10 well error-characterized observations relevant to the carbon cycle. Relevant observations for assimilation include various in-situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model 15 benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current 20 observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al. (2005) emphasising the rapid advance in relevant space-based observations.

scholarly journals The study of carbon in inland waters-from isolated ecosystems to players in the global carbon cycle

2018 ◽  
Vol 3 (3) ◽  
pp. 41-48 ◽  
Author(s):  
Lars J. Tranvik ◽  
Jonathan J. Cole ◽  
Yves T. Prairie
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Inland Waters ◽  
Global Carbon

scholarly journals Ignoring detailed fast-changing dynamics of land use overestimates regional terrestrial carbon sequestration

2009 ◽  
Vol 6 (2) ◽  
pp. 3215-3235 ◽  
Author(s):  
S. Zhao ◽  
S. Liu ◽  
Z. Li ◽  
T. L. Sohl
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Land Use Change ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Forest Harvesting ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Sequestration ◽  
Data Frequency ◽  
Global Carbon

Abstract. Land use change is critical in determining the distribution, magnitude and mechanisms of terrestrial carbon budgets at the local to global scales. To date, almost all regional to global carbon cycle studies are driven by a static land use map or land use change statistics with decadal time intervals. The biases in quantifying carbon exchange between the terrestrial ecosystems and the atmosphere caused by using such land use change information have not been investigated. Here, we used the General Ensemble biogeochemical Modeling System (GEMS), along with consistent and spatially explicit land use change scenarios with different intervals (1 yr, 5 yrs, 10 yrs and static, respectively), to evaluate the impacts of land use change data frequency on estimating regional carbon sequestration in the southeastern United States. Our results indicate that ignoring the detailed fast-changing dynamics of land use can lead to a significant overestimation of carbon uptake by the terrestrial ecosystem. Regional carbon sequestration increased from 0.27 to 0.69, 0.80 and 0.97 Mg C ha−1 yr−1 when land use change data frequency shifting from 1 year to 5 years, 10 years interval and static land use information, respectively. Carbon removal by forest harvesting and prolonged cumulative impacts of historical land use change on carbon cycle accounted for the differences in carbon sequestration between static and dynamic land use change scenarios. The results suggest that it is critical to incorporate the detailed dynamics of land use change into local to global carbon cycle studies. Otherwise, it is impossible to accurately quantify the geographic distributions, magnitudes, and mechanisms of terrestrial carbon sequestration at local to global scales.

scholarly journals The global carbon budget 1959–2011

2013 ◽  
Vol 5 (1) ◽  
pp. 165-185 ◽  
Author(s):  
C. Le Quéré ◽  
R. J. Andres ◽  
T. Boden ◽  
T. Conway ◽  
R. A. Houghton ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Cycle ◽  
Co2 Emissions ◽  
Carbon Budget ◽  
Co2 Concentration ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Global Carbon Budget ◽  
Atmospheric Co2 Concentration ◽  
Global Carbon

Abstract. Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 &amp;pm; 0.4 PgC yr−1, ELUC 1.0 &amp;pm; 0.5 PgC yr−1, GATM 4.3 &amp;pm; 0.1 PgC yr−1, SOCEAN 2.5 &amp;pm; 0.5 PgC yr−1, and SLAND 2.6 &amp;pm; 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 &amp;pm; 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 &amp;pm; 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 &amp;pm; 0.2 PgC yr−1, SOCEAN was 2.7 &amp;pm; 0.5 PgC yr−1, and SLAND was 4.1 &amp;pm; 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 &amp;pm; 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as &amp;pm;1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2013). Global carbon budget 2013

scholarly journals Increasing Autochthonous Production in Inland Waters as a Contributor to the Missing Carbon Sink

2021 ◽  
Vol 9 ◽  
Author(s):  
Zaihua Liu ◽  
Hao Yan ◽  
Sibo Zeng
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Carbon Sink ◽  
Global Carbon Cycle ◽  
Inland Waters ◽  
Organic Carbon Burial ◽  
Missing Carbon Sink ◽  
Organic Carbon Storage ◽  
Autochthonous Production ◽  
Global Carbon

Accounting for the residual land sink (or missing carbon sink) has become a major budget focus for global carbon cycle modelers. If we are not able to account for the past and current sources and sinks, we cannot make accurate predictions about future storage of fossil fuel combustion emissions of carbon in the terrestrial biosphere. Here, we show that the autochthonous production (AP) in inland waters appears to have been strengthening in response to changes in climate and land use, as evidenced by decreasing CO2 emissions from and increasing dissolved organic carbon storage and/or organic carbon burial in inland waters during recent decades. The increasing AP may be due chiefly to increasing aquatic photosynthesis caused by global warming and intensifying human activities. We estimate that the missing carbon sink associated with the strengthening AP in inland waters may range from 0.38 to 1.8 Gt C yr-1 with large uncertainties. Our study stresses the potential role that AP may play in the further evolution of the global carbon cycle. Quantitative estimates of future freshwater AP effects on the carbon cycle may also help to guide the action needed to reduce carbon emissions, and increase carbon sinks in terrestrial aquatic ecosystems.

Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model

2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Loughran ◽  
Julia Pongratz
Keyword(s):  
Growth Rate ◽  
Carbon Cycle ◽  
Carbon Budget ◽  
Global Carbon Cycle ◽  
System Model ◽  
Earth System ◽  
Global Carbon Budget ◽  
Predictive Skill ◽  
Atmospheric Carbon ◽  
Global Carbon

&lt;p&gt;The global carbon budget including CO&lt;sub&gt;2&lt;/sub&gt; fluxes among different reservoirs and atmospheric carbon growth rate vary substantially in interannual to decadal time-scales. Reconstructing and predicting the variable global carbon cycle is of essential value of tracing the fate of carbon and the corresponding climate and ecosystem changes. For the first time, we extend our prediction system based on the Max Planck Institute Earth system model (MPI-ESM) from concentration-driven to emission-driven taking into account the interactive carbon cycle and hence enabling prognostic atmospheric carbon increment.&amp;#160;&lt;/p&gt;&lt;p&gt;By assimilating atmospheric and oceanic observational data products into MPI-ESM decadal prediction system, we can reproduce the observed variations of the historical global carbon cycle globally. The reconstruction from the fully coupled model enables quantification of global carbon budget within a close Earth system and therefore avoids the budget imbalance term of budgeting the carbon with standalone models. Our reconstructions of carbon budget provide a novel approach for supporting global carbon budget and understanding the dominating processes. Retrospective predictions based on the &amp;#160;emission-driven hindcasts, which are initiated from the reconstructions, show predictive skill in the atmospheric carbon growth rate, air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes, and air-land CO&lt;sub&gt;2&lt;/sub&gt; fluxes. The air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes have higher predictive skill up to 5 years, and the air-land CO&lt;sub&gt;2&lt;/sub&gt; fluxes and atmospheric carbon growth rate show predictive skill of 2 years. Our results also suggest predictions based on Earth system models enable reproducing and further predicting the evolution of atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration changes. The earth system predictions will provide valuable inputs for understanding the global carbon cycle and supporting climate relevant policy development.&amp;#160;&lt;/p&gt;

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Vol 14 (14) ◽  
pp. 3401-3429 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Ecosystem Dynamics ◽  
Full Description ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

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