Reconstructing the recent carbon cycle from atmospheric CO₂, δ¹³C and O₂/N₂ observations*

Abstract

This paper presents an attempt to recover the space-time structure of fluxes of CO 2 to the atmosphere over the period 1980-1995 from atmospheric concentration and isotopic composition measurements. The technique used is Bayesian synthesis inversion in which sources are aggregated into large regions and their strengths adjusted to match observed concentrations. The sources are constrained by prior estimates based on a priori knowledge. The input data are atmospheric CO 2 concentration measurements from the NOAA/CMDL network, 13CO 2 composition and O 2 /N 2 ratios measured at Cape Grim, Tasmania by CSIRO Atmospheric Research. The primary findings are a relatively large long-term mean ocean uptake of CO 2 , and seasonal fluxes over land with similar integrated magnitude, but smaller peak amplitude, compared with those derived by Fung and co-workers. Predicted interannual variability is smaller than reported in previous studies. The largest contributor is the oceanic tropics where fluxes vary on the time scale of the southern oscillation. There is evidence of longer time-scale variation in land uptake. Increases in ocean uptake and northern land uptake in the early 1990s are consistent with a response to the Mt. Pinatubo eruption.

Recent global CO<sub>2</sub> flux inferred from atmospheric CO<sub>2</sub> observations and its regional analyses

“…The inversion problem reduces to minimizing the cost function (Enting et al, 1995;Rayner et al, 1999) …”

“…The model-data mismatch reflects the difference between observations and modeled results, which incorporates errors associated with observations (instrument errors) and errors from the modeling of the observations. Various approaches (Rayner et al, 1999;Rödenbeck et al, 2003;Baker et al, 2006;Michalak et al, 2005;Bruhwiler et al, 2007) have been used to determine the model-data mismatch error. As pointed out by Bruhwiler et al (2007), choosing the appropriate values for the model-data mismatch error is difficult because there are insufficient independent data available for detailed model evaluations at each observation site.…”

“…The Bayesian synthesis inversion (Enting et al, 1995) and its variants have been used extensively in estimating global or regional CO 2 fluxes (e.g., Fan et al, 1998;Rayner et al, 1999;Gurney et al, 2002Gurney et al, , 2003. In recent years, the progress of inversion has been made in two directions : (i) estimating fluxes with finer spatial resolutions (Kaminski et al, 1999;Rödenbeck et al, 2003;Peters et al, , 2007Mueller et al, 2008;Lokupitiya et al, 2008) and (ii) understanding the magnitude and possible mechanisms of interannual variability (e.g., Bousquet et al, 2000;Rödenbeck et al, 2003;Peylin et al, 2005;Patra et al, 2005;Baker et al, 2006;Bruhwiler et al, 2007;Gurney et al, 2008;Rayner et al, 2008;Peters et al, 2010).…”

“…Several atmospheric inversion experiments (e.g., Rödenbeck et al, 2003;Peylin et al, 2005;Baker et al, 2006;Gurney et al, 2008;Rayner et al, 1999Rayner et al, , 2005Rayner et al, , 2008 have shown that the interannual variability of inverted fluxes could be reasonably explained by extreme climate and other events, such as El Niño/La Niña-Southern Oscillation (ENSO), and the eruption of Mt. Pinatubo in 1991.…”

An improved method for estimating forest canopy height using ICESat-GLAS full waveform data over sloping terrain: A case study in Changbai mountains, China

“…They form a very large and dynamic global carbon stock, and can act both as a carbon source, e.g., through deforestation and forest degradation, and as a sink, for instance through growth, afforestation and reforestation. Large uncertainties still remain, however, in estimating forest carbon stock, which need to be studied further (Rayner et al, 1999;Bousquet et al, 2000). Forest carbon stocks and fluxes, and forest biomass are directly related to each other.…”