Anthropogenic CO₂ releases to the atmosphere have changed the total inorganic carbon concentration of ocean by no more than 3-4% at any location. Main differences between three approaches [Poisson and Chen, 1987; Gruber et al., 1996; Friis, 2005] are presented that define marine anthropogenic CO₂ (C_T^ant) as deduced from total inorganic carbon. All definitions are based on a back-calculation technique that was independently proposed by Brewer [1978] and Chen and Millero [1979]. The overall importance of this presentation is in the comparability of anthropogenic CO₂ findings from described methods with these derived from global bookkeeping approaches or full carbon model results.

We have employed a Multi-parameter Linear Regression (MLR) analysis procedure to determine the uptake of anthropogenic CO₂ between two east-west hydrographic surveys of the North Pacific that occurred in 1994 and 2004. The results revealed water column integrated uptake rates of anthropogenic CO₂ that ranged from 1.1 to 1.3 mol m^-2 yr^-1 depending on location. The combined effect of the tilted density surfaces and the younger waters with higher anthropogenic CO₂ concentrations leads to higher total column inventories in the western North Pacific.

Atmospheric CO₂ concentrations have been obtained from the Atmospheric Infrared Sounder (AIRS) radiance data within the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system. In a first explorative configuration, a subset of channels from the AIRS instrument has been assimilated providing estimates of tropospheric column-averaged CO₂ mixing ratios representative of a layer between the tropopause and about 700 hPa at observation locations only. Results show considerable geographical and temporal variability with values ranging between 370 and 382 ppmv. The 5-day mean estimated random error is about 1%, which is confirmed by comparisons with flask observations on board flights of Japanese airliners in the west-Pacific region. This study demonstrates the feasibility of global CO₂ estimation using high spectral resolution infrared satellite data in a numerical weather prediction data assimilation system. Currently, the system is being improved to treat CO₂ as a full three-dimensional atmospheric variable included in the forecast model. This allows more flexibility in the constraints on the CO₂ estimation as well as the possibility of assimilating other data sources (e.g., near-infrared satellite data and flasks). The CO₂ fields provided by the data assimilation system have great potential to assist the surface flask network in constraining current top-down carbon flux estimates.

We present preliminary results from hydrogen isotopic measurements in atmospheric methane obtained from the NOAA CCGG Cooperative Air Sampling Network. Recent developments at INSTAAR, University of Colorado have brought on line the capability to measure hydrogen deuterium ratios in methane using continuous flow mass spectrometry coupled with an extraction combustion sample preparation system. Preliminary results show reproducibility of cylinder air samples to less than ± 2 ‰. Data from several months of samples from six network sites are presented, including data from: Barrow and Cold Bay, Alaska, U.S.A; Tutuila American Samoa; Black Sea, Constanta, Romania; Park Falls Wisconsin, U.S.A.; and Baltic Sea, Poland.

A one-dimensional (1d) physical-biological-chemical model was developed and tested by Antoine and Morel [1995, AM95 hereafter], with the aim of assessing upper ocean carbon fluxes. This model was specifically designed to be driven by satellite data, and it was used to evaluate the upper ocean CO₂ fluxes at station P in the NE Pacific. Another validation of this model has been carried out at the DYFAMED station (NW Mediterranean), where time series of biological and physical observations are available. This validation is a first step before the basin-scale application to the Mediterranean Sea, as presented here for the period 1998-2000.

An accurate knowledge of the thermodynamics of the carbonic acid system in seawater is crucial to our understanding of the behavior of carbon dioxide in seawater. In particular, this knowledge is needed whenever a particular property needs to be calculated from measurements of other related properties; e.g., the estimation of the partial pressure of CO2 in air that is in equilibrium with a sample of sea water, p(CO2), from measurements of the total dissolved inorganic carbon, CT, and of the total alkalinity, AT, of a water sample. This calculation is particularly important for ocean models, which transport CT and AT, but which need to calculate p(CO2) at the sea surface so as to represent air-sea exchange processes. Numerous determinations of dissociation constants for carbon dioxide in seawater media have been published over the years. In each case the authors have recommended “best” values for the dissociation constants, and often the constants are represented in these papers by interpolating equations or tables. Furthermore, a number of investigators have attempted to assess the thermodynamic consistency of the various published values for these dissociation constants with analytical measurements made on natural seawater. Despite all this work, the results of these efforts are, as yet, not conclusive. I shall present a review of the situation and will try to provide a clear description of the magnitude of the problems, their possible sources, and their importance to understanding the behavior of CO2 in seawater.

Measurements of CO₂ concentration are carried out on a weekly basis since 1992 on the island of Lampedusa (35.5°N, 12.6°E), in the Mediterranean. Measurements are based at the Station for Climate Observations, which rests on a rocky plateau (45 m asl) on the North-Eastern coast of the island, and are made with a NDIR analyzer. World Meteorological Organization (WMO) reference standards are used for calibrations.  Continuous measurements were started in 1998; they were interrupted in early 2003, and activated again in 2005. The continuous observations show evidence of a small daily cycle (amplitude < ±1 ppm) only during the months of June, July, and August. Mean annual cycles derived from weekly flask measurements show a dependency on the wind origin: the annual cycle and the annual CO₂ mean are smaller for winds originating from the Southern sectors, than for winds from Northern sectors. The continuous measurements were combined with daily backward airmass trajectories to identify the dependency of the CO₂ amount on the airmass origin. Trajectories provided by National Oceanic and Atmospheric Administration / Air Resources Laboratory (Hysplit) are used. During winter, low CO₂ is generally connected to Southern/South-Eastern airmasses. In summer airmasses from North often display lower CO₂ content, due to the influence of the European sink.

CO₂ and methane are important greenhouse gases, both contributing in increasing amounts towards positive radiative forcing. It is hence important to gain maximum understanding of the carbon cycle in the atmosphere, and the scale of carbon trace gas sources and sinks, not only globally but also on a more regional level. The Orbiting Carbon Observatory (OCO) satellite, scheduled for launch in 2008, is designed for dedicated global mapping of CO₂. In order to investigate the usefulness of a variety of methods, including retrievals from satellite mapping, some preliminary inverse modelling using a Bayesian synthesis technique is performed using pseudodata generated to represent possible future measurement regimes. This study will focus on the ability of in-situ measurements within Australia to reduce the uncertainties in Australian continental CO₂ flux estimates. The specific measurements investigated include a Ghan railway transect between Adelaide (34.9°S, 138.6°E) and Darwin (12.5°S, 130.9°E), and a number of continuous permanent sites. The reduction in flux uncertainties from additional measurements compared to a background inversion is examined, from which it is concluded that measuring on the Ghan railway is potentially worthwhile for reducing uncertainties associated with flux estimates.

We have developed a carbon flux inversion method for using a mesoscale meteorological model (CSU-RAMS) within a Maximum Likelihood Ensemble Filter (MLEF, Zupanski 2005; Zupanski and Zupanski 2005). The MLEF is a variant of the Ensemble Kalman Filter, and is used to optimize model state variables and parameters based on continuous observations of CO₂ mixing ratio. The method does not require the development of a model adjoint, but rather relies on transformation of variables to efficiently obtain estimates of fluxes with uncertainties and dynamical model error from an ensemble of forward model simulations. We demonstrate this method using a mesoscale simulation of weather, transport, and the surface carbon budget over the continental USA during the summer. The estimation procedure decomposes the total surface flux into photosynthesis and respiration (which are assumed to be modeled correctly to first order), plus an unknown but time-invariant fractional error in each.  These residuals are estimated for each model grid cell over a moving window in time, allowing atmospheric observations to be integrated over sufficient time to obtain constraint. Model error can also be estimated by this procedure, and the method can be extended to larger domains and longer integrations.

An inverse modeling system has been developed based on the Bayesian principle for estimating the carbon fluxes of the 48 regions globally and 28 regions over North America in monthly steps for 2003 using CO₂ concentration measurements at 95 atmospheric baseline stations and with regularization using remote sensing-based surface flux field. Preliminary inversion results of global carbon flux and a carbon flux field over North America have been obtained.