Evaluation of various observing systems for the global monitoring of CO<sub>2</sub> surface fluxes

Abstract

Abstract. In the context of rising greenhouse gas concentrations, and the potential feedbacks between climate and the carbon cycle, there is an urgent need to monitor the exchanges of carbon between the atmosphere and both the ocean and the land surfaces. In the so-called top-down approach, the surface fluxes of CO 2 are inverted from the observed spatial and temporal concentration gradients. The concentrations of CO 2 are measured in-situ at a number of surface stations unevenly distributed over the Earth while several satellite missions may be used to provide a dense and better-distributed set of observations to complement this network. In this paper, we compare the ability of different CO 2 concentration observing systems to constrain surface fluxes. The various systems are based on realistic scenarios of sampling and precision for satellite and in-situ measurements.It is shown that satellite measurements based on the differential absorption technique (such as those of SCIAMACHY, GOSAT or OCO) provide more information than the thermal infrared observations (such as those of AIRS or IASI). The OCO observations will provide significantly better information than those of GOSAT. A CO 2 monitoring mission based on an active (lidar) technique could potentially proCorrespondence to: K. Hungershoefer (katja.hungershoefer@dwd.de) vide an even better constraint. This constraint can also be realized with the very dense surface network that could be built with the same funding as that of the active satellite mission. Despite the large uncertainty reductions on the surface fluxes that may be expected from these various observing systems, these reductions are still insufficient to reach the highly demanding requirements for the monitoring of anthropogenic emissions of CO 2 or the oceanic fluxes at a spatial scale smaller than that of oceanic basins. The scientific objective of these observing system should therefore focus on the fluxes linked to vegetation and land ecosystem dynamics.

Surface observations for monitoring urban fossil fuel CO2 emissions: Minimum site location requirements for the Los Angeles megacity

“…Because the framework is analytic and the calculations rapid, many different observing systems can be quantitatively assessed and compared for their ability to constrain urban CO 2 emissions. This same analytical technique has been exploited to study global observing systems [Hungershoefer et al, 2010].…”

“…However, to extract information on anthropogenic emissions from atmospheric observations, the role of transport and biospheric fluxes must be untangled. Current global assimilation frameworks are incapable of disentangling these components to the level required for monitoring of anthropogenic CO 2 at 300 km spatial scales [Hungershoefer et al, 2010]. By developing a framework specifically focused on small area, large magnitude anthropogenic sources, we can potentially overcome transport and biospheric obfuscation.…”

“…These studies suggest that attribution and trend detection with atmospheric observations are possible. However, although optimal global monitoring network design has been studied [Gloor et al, 2000;Suntharalingam et al, 2003;Hungershoefer et al, 2010], optimal strategies for monitoring urban emissions have yet to be determined.…”

Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit

“…The sources and sinks of greenhouse gases are then inferred through flux inversions (e.g., Baker et al, 2010;Nassar et al, 2011). However, the low spatiotemporal measurement densities of the current Earth observing system in LEO result in a lack of information about emissions on smaller spatiotemporal scales (Chevallier et al, 2005;Hungershoefer et al, 2010;Wecht et al, 2014). For example, localized emissions from forest fires and megacities vary over days or even hours.…”

Diagnostic methods for atmospheric inversions of long-lived greenhouse gases

“…Pseudo-observation sites and types of data (for example, mixing ratios, profiles, column averages, or isotopic signatures from flask samples) can be added or taken away from the inversion to determine how the density and distribution of observations affect the precision and accuracy of the posterior flux field (Villani et al, 2010;Miyazaki et al, 2011;Hungershoefer et al, 2010;Shiga et al, 2013;Basu et al, 2016;Bloom et al, 2016). In addition, the ability of existing monitoring network sites to detect specific types of fluxes or flux patterns can be explored, as well as the impact of various sources of uncertainty on detection (e.g., Shiga et al, 2014;Fang et al, 2014;Miller et al, 2016a).…”