ALBERT

Description: 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 CO2 are inverted from the observed spatial and temporal concentration gradients. The concentrations of CO2 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 CO2 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 CO2 monitoring mission based on an active (lidar) technique could potentially provide 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 CO2 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.

Description: This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

Description: In the context of raising 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 CO2 are inverted from the observed spatial and temporal concentration gradients. The concentrations of CO2 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 CO2 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 CO2 monitoring mission based on an active (lidar) technique could potentially provide 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 CO2 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.

Description: This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common CO2 fluxes and initial concentrations. Simulated column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over sea. A variable, but overall quite encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 Pg C/yr per 106 km2 over land and 0.03 Pg C/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 Pg C/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Further development of these models should receive high priority.