scholarly journals Data-based estimates of interannual sea–air CO<sub>2</sub> flux variations 1957–2020 and their relation to environmental drivers

2021 ◽  
Author(s):  
Christian Rödenbeck ◽  
Tim DeVries ◽  
Judith Hauck ◽  
Corinne Le Quéré ◽  
Ralph Keeling
Keyword(s):  
Wind Speed ◽  
Linear Regression ◽  
Mixed Layer ◽  
Carbon Sources ◽  
Co2 Flux ◽  
Mapping Method ◽  
Atmospheric Co2 ◽  
Environmental Drivers ◽  
Multi Linear Regression ◽  
Secular Increase

Abstract. This study considers year-to-year and decadal variations as well as secular trends of the sea–air CO2 flux over the 1957–2020 period, as constrained by the pCO2 measurements from the SOCAT data base. In a first step, we relate interannual anomalies in ocean-internal carbon sources and sinks to local interannual anomalies in sea surface temperature (SST), the temporal changes of SST (dSST/dt), and squared wind speed (u2), employing a multi-linear regression. In the tropical Pacific, we find interannual variability to be dominated by dSST/dt, as arising from variations in the upwelling of colder and more carbon-rich waters into the mixed layer. In the eastern upwelling zones as well as in circumpolar bands in the high latitudes of both hemispheres, we find sensitivity to wind speed, compatible with the entrainment of carbon-rich water during wind-driven deepening of the mixed layer and wind-driven upwelling. In the Southern Ocean, the secular increase in wind speed leads to a secular increase in the carbon source into the mixed layer, with an estimated reduction of the sink trend in the range 17 to 42 %. In a second step, we combined the result of the multi-linear regression and an explicitly interannual pCO2-based additive correction into a “hybrid” estimate of the sea–air CO2 flux over the period 1957–2020. As a pCO2 mapping method, it combines (a) the ability of a regression to bridge data gaps and extrapolate into the early decades almost void of pCO2 data based on process-related observables and (b) the ability of an autoregressive interpolation to follow signals even if not represented in the chosen set of explanatory variables. The “hybrid” estimate can be applied as ocean flux prior for atmospheric CO2 inversions covering the whole period of atmospheric CO2 data since 1957.

scholarly journals Forest stand age information improves an inverse North American carbon flux estimate

2013 ◽  
Vol 10 (3) ◽  
pp. 4781-4817 ◽  
Author(s):  
F. Deng ◽  
J. M. Chen ◽  
Y. Pan ◽  
W. Peters ◽  
R. Birdsey ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Age Factors ◽  
Carbon Sources ◽  
Co2 Flux ◽  
Forest Stand ◽  
Atmospheric Co2 ◽  
Stand Age ◽  
Ecosystem Carbon ◽  
Net Ecosystem Carbon Exchange ◽  
Carbon Dioxide Co2

Abstract. Atmospheric inversions have become an important tool in quantifying carbon dioxide (CO2) sinks and sources at a variety of spatiotemporal scales, but associated large uncertainties restrain the inversion research community from reaching agreements on many important subjects. We enhanced an atmospheric inversion of the CO2 flux for North America by introducing spatially-explicit information on forest stand age for US and Canada as an additional constraint, since forest carbon dynamics are closely related to time since disturbance. To use stand age information in the inversion, we converted stand age into an age factor, and included the covariances between sub-continental regions in the inversion based on the similarity of the age factors. Our inversion results show that, considering age factors, regions with recently-disturbed or old forests are often nudged towards carbon sources, while regions with middle-aged productive forests are shifted towards sinks. This conforms to stand age effects observed in flux networks. At the sub-continental level, our inverted carbon fluxes agree well with continuous estimates of net ecosystem carbon exchange (NEE) upscaled from eddy covariance flux data (EC) based on MODIS data. Inverted fluxes with the age constraint exhibit stronger correlation to these upscaled NEE estimates than those inverted without the age constraint. While the carbon flux at the continental and sub-continental scales is predominantly determined by atmospheric CO2 observations, the age constraint is shown to have potential to improve the inversion of the carbon flux distribution among sub-continental regions, especially for regions lacking atmospheric CO2 observations.

scholarly journals The use of forest stand age information in an atmospheric CO<sub>2</sub> inversion applied to North America

2013 ◽  
Vol 10 (8) ◽  
pp. 5335-5348 ◽  
Author(s):  
F. Deng ◽  
J. M. Chen ◽  
Y. Pan ◽  
W. Peters ◽  
R. Birdsey ◽  
...  
Keyword(s):  
North America ◽  
Carbon Flux ◽  
Age Factors ◽  
Carbon Sources ◽  
Co2 Flux ◽  
Forest Stand ◽  
Atmospheric Co2 ◽  
Stand Age ◽  
Net Ecosystem Carbon Exchange ◽  
Carbon Dioxide Co2

Abstract. Atmospheric inversions have become an important tool in quantifying carbon dioxide (CO2) sinks and sources at a variety of spatiotemporal scales, but associated large uncertainties restrain the inversion research community from reaching agreement on many important subjects. We enhanced an atmospheric inversion of the CO2 flux for North America by introducing spatially explicit information on forest stand age for US and Canada as an additional constraint, since forest carbon dynamics are closely related to time since disturbance. To use stand age information in the inversion, we converted stand age into an age factor, and included the covariances between subcontinental regions in the inversion based on the similarity of the age factors. Our inversion results show that, considering age factors, regions with recently disturbed or old forests are often nudged towards carbon sources, while regions with middle-aged productive forests are shifted towards sinks. This conforms to stand age effects observed in flux networks. At the subcontinental level, our inverted carbon fluxes agree well with continuous estimates of net ecosystem carbon exchange (NEE) upscaled from eddy covariance flux data based on MODIS data. Inverted fluxes with the age constraint exhibit stronger correlation to these upscaled NEE estimates than those inverted without the age constraint. While the carbon flux at the continental and subcontinental scales is predominantly determined by atmospheric CO2 observations, the age constraint is shown to have potential to improve the inversion of the carbon flux distribution among subcontinental regions, especially for regions lacking atmospheric CO2 observations.

scholarly journals Sea-air CO<sub>2</sub> flux estimated from SOCAT surface-ocean CO<sub>2</sub> partial pressure data and atmospheric CO<sub>2</sub> mixing ratio data

2012 ◽  
Vol 9 (3) ◽  
pp. 2273-2326 ◽  
Author(s):  
C. Rödenbeck ◽  
R. F. Keeling ◽  
D. C. E. Bakker ◽  
N. Metzl ◽  
A. Olsen ◽  
...  
Keyword(s):  
Partial Pressure ◽  
Carbon Sources ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Diagnostic Model ◽  
Pressure Data ◽  
Co2 Partial Pressure ◽  
Sources And Sinks ◽  
Surface Ocean ◽  
Spatio Temporal

Abstract. Surface-ocean CO2 partial pressure data have been assimilated into a simple diagnostic model of surface-ocean biogeochemistry to estimate the spatio-temporal CO2 partial pressure field and ultimately the sea-air CO2 fluxes. Results compare well with the widely used monthly climatology by Takahashi et al. (2009) but also contain some short-term and interannual variations. Fitting the same model to atmospheric CO2 data yields less robust but consistent estimates, confirming that using the partial pressure based estimates as ocean prior in atmospheric CO2 inversions may improve land CO2 flux estimates. Estimated seasonality of ocean-internal carbon sources and sinks is discussed in the light of observed nutrient variations.

scholarly journals Does atmospheric CO<sub>2</sub> seasonality play an important role in governing the air-sea flux of CO<sub>2</sub>?

2012 ◽  
Vol 9 (6) ◽  
pp. 2311-2323 ◽  
Author(s):  
P. R. Halloran
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Seasonal Cycle ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Seasonal Cycles ◽  
Earth System ◽  
Model Simulations ◽  
Anthropogenic Co2 ◽  
The Impact

Abstract. The amplitude, phase, and form of the seasonal cycle of atmospheric CO2 concentrations varies on many time and space scales (Peters et al., 2007). Intra-annual CO2 variation is primarily driven by seasonal uptake and release of CO2 by the terrestrial biosphere (Machta et al., 1977; Buchwitz et al., 2007), with a small (Cadule et al., 2010; Heimann et al., 1998), but potentially changing (Gorgues et al., 2010) contribution from the ocean. Variability in the magnitude, spatial distribution, and seasonal drivers of terrestrial net primary productivity (NPP) will be induced by, amongst other factors, anthropogenic CO2 release (Keeling et al., 1996), land-use change (Zimov et al., 1999) and planetary orbital variability, and will lead to changes in CO2atm seasonality. Despite CO2atm seasonality being a dynamic and prominent feature of the Earth System, its potential to drive changes in the air-sea flux of CO2 has not previously (to the best of my knowledge) been explored. It is important that we investigate the impact of CO2atm seasonality change, and the potential for carbon-cycle feedbacks to operate through the modification of the CO2atm seasonal cycle, because the decision had been made to prescribe CO2atm concentrations (rather than emissions) within model simulations for the fifth IPCC climate assessment (Taylor et al., 2009). In this study I undertake ocean-model simulations within which different magnitude CO2atm seasonal cycles are prescribed. These simulations allow me to examine the effect of a change in CO2atm seasonal cycle magnitude on the air-sea CO2 flux. I then use an off-line model to isolate the drivers of the identified air-sea CO2 flux change, and propose mechanisms by which this change may come about. Three mechanisms are identified by which co-variability of the seasonal cycles in atmospheric CO2 concentration, and seasonality in sea-ice extent, wind-speed and ocean temperature, could potentially lead to changes in the air-sea flux of CO2 at mid-to-high latitudes. The sea-ice driven mechanism responds to an increase in CO2atm seasonality by pumping CO2 into the ocean, the wind-speed and solubility-driven mechanisms, by releasing CO2 from the ocean (in a relative sense). The relative importance of the mechanisms will be determined by, amongst other variables, the seasonal extent of sea-ice. To capture the described feedbacks within earth system models, CO2atm concentrations must be allowed to evolve freely, forced only by anthropogenic emissions rather than prescribed CO2atm concentrations; however, time-integrated ocean simulations imply that the cumulative net air-sea flux could be at most equivalent to a few ppm CO2atm. The findings presented here suggest that, at least under pre-industrial conditions, the prescription of CO2atm concentrations rather than emissions within simulations will have little impact on the marine anthropogenic CO2 sink.

scholarly journals CO<sub>2</sub> flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

2007 ◽  
Vol 4 (6) ◽  
pp. 1005-1025 ◽  
Author(s):  
L. Kutzbach ◽  
J. Schneider ◽  
T. Sachs ◽  
M. Giebels ◽  
H. Nykänen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Nonlinear Regression ◽  
Co2 Flux ◽  
Exponential Model ◽  
Co2 Uptake ◽  
Co2 Fluxes ◽  
Closed Chamber ◽  
Exponential Regression ◽  
Closure Time ◽  
Over Time

Abstract. Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

scholarly journals Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO<sub>2</sub> mole fractions in the US Midwest

2018 ◽  
Vol 18 (20) ◽  
pp. 14813-14835 ◽  
Author(s):  
Liza I. Díaz-Isaac ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Boundary Conditions ◽  
Planetary Boundary Layer ◽  
Initial Conditions ◽  
Atmospheric Transport ◽  
Atmospheric Co2 ◽  
The Us ◽  
Physics Parameterizations ◽  
Physical Parameterizations

Abstract. Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates. In this study, we determine the leading causes of transport errors over the US upper Midwest with a large set of simulations generated with the Weather Research and Forecasting (WRF) mesoscale model. The various WRF simulations are performed using different meteorological driver datasets and physical parameterizations including planetary boundary layer (PBL) schemes, land surface models (LSMs), cumulus parameterizations and microphysics parameterizations. All the different model configurations were coupled to CO2 fluxes and lateral boundary conditions from the CarbonTracker inversion system to simulate atmospheric CO2 mole fractions. PBL height, wind speed, wind direction, and atmospheric CO2 mole fractions are compared to observations during a month in the summer of 2008, and statistical analyses were performed to evaluate the impact of both physics parameterizations and meteorological datasets on these variables. All of the physical parameterizations and the meteorological initial and boundary conditions contribute 3 to 4 ppm to the model-to-model variability in daytime PBL CO2 except for the microphysics parameterization which has a smaller contribution. PBL height varies across ensemble members by 300 to 400 m, and this variability is controlled by the same physics parameterizations. Daily PBL CO2 mole fraction errors are correlated with errors in the PBL height. We show that specific model configurations systematically overestimate or underestimate the PBL height averaged across the region with biases closely correlated with the choice of LSM, PBL scheme, and cumulus parameterization (CP). Domain average PBL wind speed is overestimated in nearly every model configuration. Both planetary boundary layer height (PBLH) and PBL wind speed biases show coherent spatial variations across the Midwest, with PBLH overestimated averaged across configurations by 300–400 m in the west, and PBL winds overestimated by about 1 m s−1 on average in the east. We find model configurations with lower biases averaged across the domain, but no single configuration is optimal across the entire region and for all meteorological variables. We conclude that model ensembles that include multiple physics parameterizations and meteorological initial conditions are likely to be necessary to encompass the atmospheric conditions most important to the transport of CO2 in the PBL, but that construction of such an ensemble will be challenging due to ensemble biases that vary across the region.

scholarly journals Global surface-ocean <i>p</i><sup>CO<sub>2</sub></sup> and sea–air CO<sub>2</sub> flux variability from an observation-driven ocean mixed-layer scheme

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 193-216 ◽  
Author(s):  
C. Rödenbeck ◽  
R. F. Keeling ◽  
D. C. E. Bakker ◽  
N. Metzl ◽  
A. Olsen ◽  
...  
Keyword(s):  
Partial Pressure ◽  
Mixed Layer ◽  
Co2 Flux ◽  
Companion Paper ◽  
Diagnostic Model ◽  
Ocean Mixed Layer ◽  
Co2 Partial Pressure ◽  
Surface Ocean ◽  
Flux Variability ◽  
Global Surface

Abstract. A temporally and spatially resolved estimate of the global surface-ocean CO2 partial pressure field and the sea–air CO2 flux is presented, obtained by fitting a simple data-driven diagnostic model of ocean mixed-layer biogeochemistry to surface-ocean CO2 partial pressure data from the SOCAT v1.5 database. Results include seasonal, interannual, and short-term (daily) variations. In most regions, estimated seasonality is well constrained from the data, and compares well to the widely used monthly climatology by Takahashi et al. (2009). Comparison to independent data tentatively supports the slightly higher seasonal variations in our estimates in some areas. We also fitted the diagnostic model to atmospheric CO2 data. The results of this are less robust, but in those areas where atmospheric signals are not strongly influenced by land flux variability, their seasonality is nevertheless consistent with the results based on surface-ocean data. From a comparison with an independent seasonal climatology of surface-ocean nutrient concentration, the diagnostic model is shown to capture relevant surface-ocean biogeochemical processes reasonably well. Estimated interannual variations will be presented and discussed in a companion paper.

scholarly journals CO2 flux behavior in the maritorium of San Andres Islands on 2019

Respuestas ◽  
2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Juan Guillermo Popayán-Hernández ◽  
Orlando Zúñiga-Escobar
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Images ◽  
Co2 Flux ◽  
Sea Surface ◽  
Remote Sensors ◽  
Partial Pressures ◽  
Thermodynamic Relationship ◽  
San Andres

This document estimated the behavior of the CO2 flux in the San Andrés Islas maritime for the first half of 2019. This behavior was established based on the thermodynamic relationship between the sea surface temperature, the partial pressures of CO2 in the atmosphere and the water column, this from data derived from remote sensors. The satellite data were derived from the MODIS aqua sensors and the MERRA model for sea surface temperature and wind speed respectively. Satellite images were obtained from NASA databases, subsequently processed and specialized in ArcGis 10.1. Finally, the behavior of the CO2 flux is shown for the San Andrés Islas maritime, finding that it does not have a tendency to capture CO2, so acidification processes are discarded for the selected study period.

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