Sources and Sinks of Atmospheric CO2

1992 ◽  
Vol 40 (5) ◽  
pp. 407 ◽  
Author(s):  
JA Taylor ◽  
J Lloyd
Keyword(s):  
Climate Change ◽  
Biomass Burning ◽  
Transport Model ◽  
Atmospheric Co2 ◽  
Tropical Rainforests ◽  
Co2 Uptake ◽  
Tracer Transport ◽  
Intergovernmental Panel ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

The biosphere plays an important role in determining the sources, sinks, levels and rates of change of atmospheric CO2 concentrations. Significant uncertainties remain in estimates of the fluxes of CO2 from biomass burning and deforestation, and uptake and storage of CO2 by the biosphere arising from increased atmospheric CO2 concentrations. Calculation of probable rates of carbon sequestration for the major ecosystem complexes and global 3-D tracer transport model runs indicate the possibility that a significant net CO2 uptake (> 1 Pg C yr-1), a CO2 'fertilisation effect', may be occurring in tropical rainforests, effectively accounting for much of the 'missing sink'. This sink may currently balance much of the CO2 added to the atmosphere from deforestation and biomass burning. Interestingly, CO2 released from biomass burning may itself be playing an important role in enhanced carbon storage by tropical rainforests. This has important implications for predicting future CO2 concentrations. If tropical rainforest destruction continues then much of the CO2 stored as a result of the CO2 'fertilisation effect' will be rereleased to the atmosphere and much of the 'missing sink' will disappear. These effects have not been considered in the IPCC (Intergovernmental Panel on Climate Change) projections of future atmospheric CO2 concentrations. Predictions which take account of the combined effects of deforestation, the return of carbon previously stored through the CO2 'fertilisation effect' and the loss of a large proportion of the 'missing sink' as a result of deforestation, would result in much higher predicted concentrations and rates of increase of atmospheric CO2 and, as a consequence, accelerated rates of climate change.

scholarly journals Can seasonal and interannual variation in landscape CO<sub>2</sub> fluxes be detected by atmospheric observations of CO<sub>2</sub> concentrations made at a tall tower?

2014 ◽  
Vol 11 (3) ◽  
pp. 735-747 ◽  
Author(s):  
T. L. Smallman ◽  
M. Williams ◽  
J. B. Moncrieff
Keyword(s):  
Interannual Variation ◽  
Atmospheric Transport ◽  
Co2 Exchange ◽  
Atmospheric Co2 ◽  
Co2 Uptake ◽  
Post Harvest ◽  
Co2 Concentrations ◽  
Prevailing Wind Direction ◽  
Atmospheric Co2 Concentrations ◽  
Tall Tower

Abstract. The coupled numerical weather model WRF-SPA (Weather Research and Forecasting model and Soil-Plant-Atmosphere model) has been used to investigate a 3 yr time series of observed atmospheric CO2 concentrations from a tall tower in Scotland, UK. Ecosystem-specific tracers of net CO2 uptake and net CO2 release were used to investigate the contributions to the tower signal of key land covers within its footprint, and how contributions varied at seasonal and interannual timescales. In addition, WRF-SPA simulated atmospheric CO2 concentrations were compared with two coarse global inversion models, CarbonTrackerEurope and the National Oceanic and Atmospheric Administration's CarbonTracker (CTE-CT). WRF-SPA realistically modelled both seasonal (except post harvest) and daily cycles seen in observed atmospheric CO2 at the tall tower (R2 = 0.67, rmse = 3.5 ppm, bias = 0.58 ppm). Atmospheric CO2 concentrations from the tall tower were well simulated by CTE-CT, but the inverse model showed a poorer representation of diurnal variation and simulated a larger bias from observations (up to 1.9 ppm) at seasonal timescales, compared to the forward modelling of WRF-SPA. However, we have highlighted a consistent post-harvest increase in the seasonal bias between WRF-SPA and observations. Ecosystem-specific tracers of CO2 exchange indicate that the increased bias is potentially due to the representation of agricultural processes within SPA and/or biases in land cover maps. The ecosystem-specific tracers also indicate that the majority of seasonal variation in CO2 uptake for Scotland's dominant ecosystems (forests, cropland and managed grassland) is detectable in observations within the footprint of the tall tower; however, the amount of variation explained varies between years. The between years variation in detectability of Scotland's ecosystems is potentially due to seasonal and interannual variation in the simulated prevailing wind direction. This result highlights the importance of accurately representing atmospheric transport used within atmospheric inversion models used to estimate terrestrial source/sink distribution and magnitude.

scholarly journals Regional Impacts of Climate Change and Atmospheric CO2 on Future Ocean Carbon Uptake: A Multimodel Linear Feedback Analysis

2011 ◽  
Vol 24 (9) ◽  
pp. 2300-2318 ◽  
Author(s):  
Tilla Roy ◽  
Laurent Bopp ◽  
Marion Gehlen ◽  
Birgit Schneider ◽  
Patricia Cadule ◽  
...  
Keyword(s):  
Climate Change ◽  
North Atlantic Ocean ◽  
Climate Change Impacts ◽  
Atmospheric Co2 ◽  
Linear Feedback ◽  
Co2 Uptake ◽  
Co2 Solubility ◽  
Feedback Analysis ◽  
Anthropogenic Co2 ◽  
Atmospheric Co2 Concentrations

Abstract The increase in atmospheric CO2 over this century depends on the evolution of the oceanic air–sea CO2 uptake, which will be driven by the combined response to rising atmospheric CO2 itself and climate change. Here, the future oceanic CO2 uptake is simulated using an ensemble of coupled climate–carbon cycle models. The models are driven by CO2 emissions from historical data and the Special Report on Emissions Scenarios (SRES) A2 high-emission scenario. A linear feedback analysis successfully separates the regional future (2010–2100) oceanic CO2 uptake into a CO2-induced component, due to rising atmospheric CO2 concentrations, and a climate-induced component, due to global warming. The models capture the observation-based magnitude and distribution of anthropogenic CO2 uptake. The distributions of the climate-induced component are broadly consistent between the models, with reduced CO2 uptake in the subpolar Southern Ocean and the equatorial regions, owing to decreased CO2 solubility; and reduced CO2 uptake in the midlatitudes, owing to decreased CO2 solubility and increased vertical stratification. The magnitude of the climate-induced component is sensitive to local warming in the southern extratropics, to large freshwater fluxes in the extratropical North Atlantic Ocean, and to small changes in the CO2 solubility in the equatorial regions. In key anthropogenic CO2 uptake regions, the climate-induced component offsets the CO2-induced component at a constant proportion up until the end of this century. This amounts to approximately 50% in the northern extratropics and 25% in the southern extratropics and equatorial regions. Consequently, the detection of climate change impacts on anthropogenic CO2 uptake may be difficult without monitoring additional tracers, such as oxygen.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2011 ◽  
Vol 4 (3) ◽  
pp. 2047-2080 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e., a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals The ocean carbon sink – impacts, vulnerabilities, and challenges

2014 ◽  
Vol 5 (2) ◽  
pp. 1607-1672
Author(s):  
C. Heinze ◽  
S. Meyer ◽  
N. Goris ◽  
L. Anderson ◽  
R. Steinfeldt ◽  
...  
Keyword(s):  
Carbon Sink ◽  
Mitigation Strategies ◽  
Atmospheric Co2 ◽  
Co2 Uptake ◽  
Spatial And Temporal Scales ◽  
The Past ◽  
Research Fields ◽  
Co2 Concentrations ◽  
Ocean Carbon ◽  
Atmospheric Co2 Concentrations

Abstract. Carbon dioxide (CO2) is, next to water vapour, considered to be the most important natural greenhouse gas on Earth. Rapidly rising atmospheric CO2 concentrations caused by human actions such as fossil-fuel burning, land-use change or cement production over the past 250 years have given cause for concern that changes in Earth's climate system may progress at a much faster pace and larger extent than during the past 20 000 years. Investigating global carbon cycle pathways and finding suitable mitigation strategies has, therefore, become of major concern in many research fields. The oceans have a key role in regulating atmospheric CO2 concentrations and currently take up about 25% of annual anthropogenic carbon emissions to the atmosphere. Questions that yet need to be answered are what the carbon uptake kinetics of the oceans will be in the future and how the increase in oceanic carbon load will affect its ecosystems and their services. This requires comprehensive investigations, including high-quality ocean carbon measurements on different spatial and temporal scales, the management of data in sophisticated data bases, the application of state-of-the-art Earth system models to provide future projections for given emission scenarios as well as a global synthesis and outreach to policy makers. In this paper, the current understanding of the ocean as an important carbon sink is reviewed with respect to these topics. Emphasis is placed on the complex interplay of different physical, chemical, and biological processes that yield both positive and negative air–sea flux values for natural and anthropogenic CO2 as well as on increased CO2 (uptake) as the regulating force of the radiative warming of the atmosphere and the gradual acidification of the oceans. Major future ocean carbon challenges in the fields of ocean observations, modelling, and process research as well as the relevance of other biogeochemical cycles and greenhouse gases are discussed.

scholarly journals Evaluation of atmosphere-biosphere exchange estimations with TCCON measurements

2012 ◽  
Vol 12 (5) ◽  
pp. 12759-12800 ◽  
Author(s):  
J. Messerschmidt ◽  
N. Parazoo ◽  
N. M. Deutscher ◽  
C. Roehl ◽  
T. Warneke ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Large Scale ◽  
Growing Season ◽  
Atmospheric Co2 ◽  
Total Carbon ◽  
Co2 Uptake ◽  
Co2 Concentrations ◽  
Time Period ◽  
Atmospheric Co2 Concentrations ◽  
Biosphere Model

Abstract. Three estimates of the atmosphere-biosphere exchange are evaluated using Total Carbon Column Observing Network (TCCON) measurements. We investigate the Carnegie-Ames-Stanford Approach (CASA), the Simple Biosphere (SiB) and the GBiome-BGC models transported by the GEOS-Chem model to simulate atmospheric CO2 concentrations for the time period between 2006 and 2010. The CO2 simulations are highly dependent on the choice of the atmosphere-biosphere model and large-scale errors in the estimates are identified through a comparison with TCCON data. Enhancing the CO2 uptake in the boreal forest by 40% and shifting the onset of the growing season significantly improve the simulated seasonal CO2 cycle using CASA estimates. The SiB model gives the best estimate for the atmosphere-biosphere exchange in the comparison with TCCON measurements.

scholarly journals El Niño-like climate change in a model with increased atmospheric CO2 concentrations

Nature ◽  
1996 ◽  
Vol 382 (6586) ◽  
pp. 56-60 ◽  
Author(s):  
Gerald A. Meehl ◽  
Warren M. Washington
Keyword(s):  
Climate Change ◽  
El Niño ◽  
El Nino ◽  
Atmospheric Co2 ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

scholarly journals A joint data assimilation system (Tan-Tracker) to simultaneously estimate surface CO<sub>2</sub> fluxes and 3-D atmospheric CO<sub>2</sub> concentrations from observations

2014 ◽  
Vol 14 (23) ◽  
pp. 13281-13293 ◽  
Author(s):  
X. Tian ◽  
Z. Xie ◽  
Y. Liu ◽  
Z. Cai ◽  
Y. Fu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Simultaneous Estimation ◽  
Co2 Fluxes ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We have developed a novel framework ("Tan-Tracker") for assimilating observations of atmospheric CO2 concentrations, based on the POD-based (proper orthogonal decomposition) ensemble four-dimensional variational data assimilation method (PODEn4DVar). The high flexibility and the high computational efficiency of the PODEn4DVar approach allow us to include both the atmospheric CO2 concentrations and the surface CO2 fluxes as part of the large state vector to be simultaneously estimated from assimilation of atmospheric CO2 observations. Compared to most modern top-down flux inversion approaches, where only surface fluxes are considered as control variables, one major advantage of our joint data assimilation system is that, in principle, no assumption on perfect transport models is needed. In addition, the possibility for Tan-Tracker to use a complete dynamic model to consistently describe the time evolution of CO2 surface fluxes (CFs) and the atmospheric CO2 concentrations represents a better use of observation information for recycling the analyses at each assimilation step in order to improve the forecasts for the following assimilations. An experimental Tan-Tracker system has been built based on a complete augmented dynamical model, where (1) the surface atmosphere CO2 exchanges are prescribed by using a persistent forecasting model for the scaling factors of the first-guess net CO2 surface fluxes and (2) the atmospheric CO2 transport is simulated by using the GEOS-Chem three-dimensional global chemistry transport model. Observing system simulation experiments (OSSEs) for assimilating synthetic in situ observations of surface CO2 concentrations are carefully designed to evaluate the effectiveness of the Tan-Tracker system. In particular, detailed comparisons are made with its simplified version (referred to as TT-S) with only CFs taken as the prognostic variables. It is found that our Tan-Tracker system is capable of outperforming TT-S with higher assimilation precision for both CO2 concentrations and CO2 fluxes, mainly due to the simultaneous estimation of CO2 concentrations and CFs in our Tan-Tracker data assimilation system. A experiment for assimilating the real dry-air column CO2 retrievals (XCO2) from the Japanese Greenhouse Gases Observation Satellite (GOSAT) further demonstrates its potential wide applications.

scholarly journals A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations

2012 ◽  
Vol 5 (1) ◽  
pp. 231-243 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  
Keyword(s):  
High Resolution ◽  
High Frequency ◽  
Transport Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Atmospheric Co2 ◽  
Lagrangian Model ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.

scholarly journals No way out? The double-bind in seeking global prosperity along with mitigated climate change

2011 ◽  
Vol 2 (1) ◽  
pp. 315-354 ◽  
Author(s):  
T. J. Garrett
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Atmospheric Co2 ◽  
Double Bind ◽  
Greenhouse Warming ◽  
Emission Rates ◽  
Co2 Concentrations ◽  
Co2 Levels ◽  
Atmospheric Co2 Concentrations ◽  
Ipcc Sres

Abstract. In a prior study (Garrett, 2011), I introduced a simple thermodynamics-based economic growth model. By treating civilization as a whole, it was found that the global economy's current rate of energy consumption can be tied through a constant to its current accumulation of wealth. The value of the constant is λ = 9.7 ± 0.3 milliwatts per 1990 US dollar. Here, this model is coupled to a linear formulation for the evolution of atmospheric CO2 concentrations. Despite the model's extreme simplicity, multi-decadal hindcasts of trajectories in gross world product (GWP) and CO2 agree closely with recent observations. Extending the model to the future, the model implies that the well-known IPCC SRES scenarios substantially underestimate how much CO2 levels will rise for a given level of future economic prosperity. Instead, what is shown is that, like a long-term natural disaster, future greenhouse warming should be expected to retard the real growth of wealth through inflationary pressures. Because wealth is tied to rates of energy consumption through the constant λ, it follows that dangerous climate change should be a negative feedback on CO2 emission rates, and therefore the ultimate extent of greenhouse warming. Nonetheless, if atmospheric CO2 concentrations are to remain below a "dangerous" level of 450 ppmv (Hansen et al., 2007), there will have to be some combination of an unrealistically rapid rate of energy decarbonization and a near immediate collapse of civilization wealth. Effectively, civilization is in a double-bind. If civilization does not collapse quickly this century, then CO2 levels will likely end up exceeding 1000 ppmv; but, if CO2 levels rise by this much, then the danger is that civilization will gradually tend towards collapse.

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