Global monthly averaged CO₂ fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements

Abstract

[1] This study presents monthly CO 2 fluxes from 1997 to 2001 at a 3.75°latitude  5°l ongitude resolution, inferred using a geostatistical inverse modeling approach. The approach focuses on quantifying the information content of measurements from the NOAA-ESRL cooperative air sampling network with regard to the global CO 2 budget at different spatial and temporal scales. The geostatistical approach avoids the use of explicit prior flux estimates that have formed the basis of previous synthesis Bayesian inversions and does not prescribe spatial patterns of flux for large, aggregated regions. Instead, the method relies strongly on the atmospheric measurements and the inferred spatial autocorrelation of the fluxes to estimate sources and sinks and their associated uncertainties at the resolution of the atmospheric transport model. Results show that gridscale estimates exhibit high uncertainty and relatively little small-scale variability, but generally reflect reasonable fluxes in areas that are relatively well constrained by measurements. The aggregated continental-scale fluxes are better constrained, and estimates are consistent with results from previous synthesis Bayesian inversion studies for many regions. Observed differences at the continental scale are primarily attributable to the choice of a priori assumptions in the current work relative to those in other synthesis Bayesian studies. Overall, the results indicate that the geostatistical inverse modeling approach is able to estimate global fluxes using the limited atmospheric measurement network without relying on assumptions about a priori estimates of the flux distribution. As such, the method provides a means of isolating the information content of the atmospheric measurements, and thus serves as a valuable tool for reconciling top-down and bottom-up estimates of CO 2 flux variability.Citation: Mueller, K. L., S. M. Gourdji, and A. M. Michalak (2008), Global monthly averaged CO 2 fluxes recovered using a geostatistical inverse modeling approach: 1. Results using atmospheric measurements,

A systematic approach for comparing modeled biospheric carbon fluxes across regional scales

“…Geostatistical approaches have been applied to many fields in the Earth and environmental sciences, including geology, ecology, and hydrology to study spatial phenomena (e.g., Chiles and Delfiner, 1999;Webster and Oliver, 2007). In studying land-atmosphere carbon dynamics, geostatistical inversion modeling has been used to estimate the spatial distribution of carbon sources and sinks both globally, and regionally over North America (e.g., Michalak et al, 2004;Gourdji et al, , 2010Mueller et al, 2008). Geostatistical regression approaches, such as the one described here, have been used regionally to evaluate the relationship between environmental variables (e.g., Erickson et al, 2005), and have recently been applied to evaluate the potential controls on carbon uptake and release at flux tower sites in North America (NA) (e.g., Mueller et al, 2010;Yadav et al, 2010).…”

“…2) are frequently used as prior estimates in inverse modeling studies (e.g., Gurney et al, 2004;Peters et al, 2007;Wang et al, 2007). There is growing awareness of the strong influence of prior estimates in inversion results (Rödenbeck et al, 2003;Michalak et al, 2004;Mueller et al, 2008). Therefore, understanding how forward model estimates of NEE, GPP, and R E vary spatially and what drives this variability is of great importance, not only for forward model intercomparisons, but also for atmospheric inversion studies.…”

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

“…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). Although different inversions generally agree on flux estimates at the hemisphere scale, large discrepancies still exist at the regional scale because of the limitations in observations used, models employed, and other setups of these inversions.…”

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

“…Recent inverse modeling studies include for instance efforts to derive the net carbon exchange across the globe or at smaller scales from mixing ratio observations of CO 2 (e.g. Bousquet et al, 2000;Gurney et al, 2003;Rödenbeck et al, 2003;Mueller et al, 2008;Lauvaux et al, 2009;Ciais et al, 2010;Göckede et al, 2010) or attempts to constrain biophysical parameters from eddycovariance methods (Papale and Valentini, 2003;Carvalhais et al, 2008).…”