Abstract
Abstract. Atmospheric inversion models have the potential to quantify CO2 fluxes at regional, sub-continental scales by taking advantage of near-surface CO2 mixing ratio observations collected in areas with high flux variability. This study presents results from a series of regional geostatistical inverse models (GIM) over North America for 2004, and uses them as the basis for an inter-comparison to other inversion studies and estimates from biospheric models collected through the North American Carbon Program Regional and Continental Interim Synthesis. Because the GIM approach does not require explicit prior flux estimates and resolves fluxes at fine spatiotemporal scales (i.e. 1° × 1°, 3-hourly in this study), it avoids temporal and spatial aggregation errors and allows for the recovery of realistic spatial patterns from the atmospheric data relative to previous inversion studies. Results from a GIM inversion using only available atmospheric observations and a fine-scale fossil fuel inventory were used to confirm the quality of the inventory and inversion setup. An inversion additionally including auxiliary variables from the North American Regional Reanalysis found inferred relationships with flux consistent with physiological understanding of the biospheric carbon cycle. Comparison of GIM results with bottom-up biospheric models showed stronger agreement during the growing relative to the dormant season, in part because most of the biospheric models do not fully represent agricultural land-management practices and the fate of both residual biomass and harvested products. Comparison to earlier inversion studies pointed to aggregation errors as a likely source of bias in previous sub-continental scale flux estimates, particularly for inversions that adjust fluxes at the coarsest scales and use atmospheric observations averaged over long periods. Finally, whereas the continental CO2 boundary conditions used in the GIM inversions have a minor impact on spatial patterns, they have a substantial impact on the continental carbon budget, with a difference of 0.8 PgC yr−1 in the total continental flux resulting from the use of two plausible sets of boundary CO2 mixing ratios. Overall, this inter-comparison study helps to assess the state of the science in estimating regional-scale CO2 fluxes, while pointing towards the path forward for improvements in future top-down and bottom-up modeling efforts.
Highlights
Carbon cycle scientists are increasingly called upon to provide information in support of efforts to monitor anthropogenic CO2 emissions, and to provide predictions of future changes to the carbon cycle within the context of a changing climate and land-use choices (CCSP, 2007)
An expanding in situ continuous measurement network across the North American and European continents (e.g. NOAA-ESRL, 2011; CGGMN, 2011; CEAD, 2011) is making this possible, but optimally extracting the flux signal from these data is complicated by the combined influence on atmospheric CO2 mixing ratios of the diurnal cycle of the terrestrial biosphere, heterogeneous land cover, point source fossil fuel emissions, and complex atmospheric transport (Bakwin et al, 1998)
The primary goal of this study was to perform an intercomparison of North American CO2 flux estimates for a single year (2004) across inverse modeling studies and biospheric models, using results from a geostatistical inversion approach as a benchmark
Summary
Carbon cycle scientists are increasingly called upon to provide information in support of efforts to monitor anthropogenic CO2 emissions, and to provide predictions of future changes to the carbon cycle within the context of a changing climate and land-use choices (CCSP, 2007). Atmospheric inverse models can contribute towards these goals by taking advantage of the information contained in atmospheric CO2 mixing ratio measurements regarding upwind surface CO2 exchange. Using these measurements, together with an atmospheric transport model and within a robust statistical framework Inversions that can take advantage of spatial and temporal atmospheric CO2 gradients measured in areas with high flux variability provide the potential to resolve sub-continental scale fluxes, thereby informing carbon management efforts and evaluations of mechanistic models of the carbon cycle. Simultaneous improvements in inversion setups (e.g. Law et al, 2002; Schuh et al, 2009; Gourdji et al, 2010) and in the quality of atmospheric transport models (e.g. Geels et al, 2007) have been necessary
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