Measurements of atmospheric CO₂ began in 1957-1958 at a wide range of locations, including at fixed stations, on ice floes, on oceanic expeditions, and on aircraft flights, with logistical and financial support provided by the International Geophysical Year (IGY) program. Although the measurement effort was reduced in scope immediately following the IGY, today, measurements are made at more than 100 locations.  Over this same time interval, emissions of CO₂ from fossil fuel combustion increased from 2.3 thousand million metric tons per year (GtC/yr) in 1958 to 7.1 GtC/yr in 2003 [Marland et al., 2005, and personal communication].  More than 90% of this CO₂ was released into the northern hemisphere where it lingered before mixing fully world-wide.  The atmospheric CO₂ concentration, in response, rose faster in the northern hemisphere than in the southern, the interhemispheric difference increasing from near zero during the IGY to about 3 parts per million (ppm) in 2003. For all northern hemisphere stations where our program has measured CO₂, the gradient changes relative to the South Pole are generally proportional to the rate of fossil fuel CO₂ emissions, disregarding seasonal and short term interannual variability in the CO₂ data.  Here, we use this fact to diagnose how the carbon cycle has evolved over the past half century.

Current predictions of future CO₂ sink strength vary widely as a result of different model representations of the carbon cycle. A sound characterization of these prediction uncertainties is crucial for the design of economically efficient carbon management strategies. We use a mechanistically sound and statistically tractable model of the global carbon cycle to (1) assimilate historical observations of atmospheric CO₂ concentrations and oceanic CO₂ fluxes, (ii) derive probabilistic predictions of future CO₂ concentrations and fluxes, and (iii) compare the utility of terrestrial and oceanic observations to constrain predictive uncertainties. We found that terrestrial and oceanic flux observations have nearly equal ability to constrain these uncertainties, if terrestrial observations include both net primary productivity (NPP) and respiration. Model predictions are dependent on the choice of historical land use emissions dataset. The probability density function (PDFs) of model parameter estimates are not normally distributed, and neglecting autocorrelation in the CO₂ concentration signal during model calibration causes overconfident results.

In order to facilitate future decision-making regarding regional carbon fluxes, it is essential to better quantify uncertainty in inverse carbon flux models. At Colorado State University, research is being performed in order to better quantify sources and sinks and associated uncertainties on a mesoscale level, through a coupled atmospheric (RAMS and PCTM) and terrestrial carbon flux (SiB3) model (Denning, 2003).  Carbon-dioxide flux and mixing ratio data were collected from a ring of towers (WLEF tall tower and nearby smaller towers) in northern Wisconsin over the summer of 2004.  The fully coupled terrestrial-atmospheric model, SiB/RAMS, will be forced with 2004 reanalysis data to predict fine scale weather in the vicinity of these towers for the summer of 2004. Relevant portions of this simulated weather, including wind fields and pertinent turbulence components, are extracted and used to create backward-in-time Lagrangian Particle Dispersion Modeled (LPDM) influence functions.  Pseudo spatial carbon-dioxide mixing ratio and flux data created by SiB/Rams is then used as input to several different estimation routines in order to try and predict pseudo tower data at different heights.  Different temporal and spatial aggregation lengths are considered as means of data reduction. Particular attention will be paid to Ensemble Kalman Filter (EnKF) techniques as well as geo-statistical methods as a means of estimation.

For the purpose of exploiting upcoming measurements of atmospheric CO₂ vertical profiles by aircrafts and continuous CO₂ data recorded along tall towers as part of the North American Carbon Plan (NACP), a direct carbon budgeting approach is being developed.

A major challenge in reaching a better understanding of global change is the integration of global carbon observations at different scales, made in the atmosphere, ocean and terrestrial domains.  This is essential to optimize efforts supporting national, regional and international policy related to the global carbon cycle.  The partners of the Integrated Global Observing Strategy (IGOS-P) representing all players in carbon cycle research and monitoring recognised this and produced, with the help of an international panels of experts, published theme reports on the Carbon Cycle (IGCO) and on Atmospheric Chemistry (IGACO).  These themes contain recommendations on how to more effectively coordinate and fill gaps in global Earth observations. 

The primary aim of the Centre for Observation of Air-sea Interactions and Fluxes (CASIX) is to estimate accurately the air-sea fluxes of CO₂. Under CASIX, a high resolution ocean general circulation model, coupled to an ocean biogeochemistry model, has been used to provide estimates of surface ocean pCO₂ and air-sea fluxes of CO₂ for the year 2003. An initial global simulation was run at 1 degree horizontal resolution, providing boundary conditions for a limited area North Atlantic model at 1/3 degree resolution. Observed temperature and salinity data were assimilated into the model. Temporal variability in the resulting pCO₂ fields are compared to observations, and the primary production and pCO₂ results of the two different resolution runs are compared.

We are establishing a continuous CO₂ observing network in the Rocky Mountains, building on technological and modeling advances made during the Carbon in the Mountains Experiment (CME), to improve our understanding of regional carbon fluxes and to fill key gaps in the North American Carbon Program (NACP). We will present a description of the Rocky RACCOON network and early results from the first three sites.

Atmospheric observations obtained during intensive field experiments are used to characterize regional sources and test data assimilation techniques. In this study, the STEM-2K1 (Sulfur Transport Eulerian Model, version 2K1) and its adjoint model are applied to the analysis of observations from aircraft platforms made during the summer 2004 ICARTT (International Consortium for Atmospheric Research on Transport) experiment. Observed ratios between CO₂ and tracers and model derived airmass markers are used to identify emission signatures, indicating the influence of different sources. Model derived influence functions along with assimilated transport model results of anthropogenic tracers are used to characterize the anthropogenic CO₂ emissions in the Midwest during the summer 2004 period. This analysis gives an initial look at the Midwest domain which is the focus of the expansion of NOAA Climate Monitoring and Diagnostic Laboratory’s tall tower observation network and the upcoming Mid-Continent NACP Intensive Campaign.