ALBERT

Description: Currently two polar orbiting satellite instruments measure CO2 concentrations in the Earth's atmosphere, while other missions are planned for the coming years. In the future such instruments might become powerful tools for monitoring changes in the atmospheric CO2 abundance and to improve our quantitative understanding of the leading processes controlling this. At the moment, however, we are still in an exploratory phase where first experiences are collected and promising new space-based measurement concepts are investigated. This study assesses the potential of some of these concepts to improve CO2 source and sink estimates obtained from inverse modelling. For this purpose the performance of existing and planned satellite instruments is quantified by synthetic simulations of their ability to reduce the uncertainty of the current source and sink estimates in comparison with the existing ground-based network of sampling sites. Our high resolution inversion of sources and sinks (at 8°x10°) allows us to investigate the variation of instrument performance in space and time and at various temporal and spatial scales. The results of our synthetic tests clearly indicate that the satellite performance increases with increasing sensitivity of the instrument to CO2 near the Earth's surface, favoring the near infra-red technique. Thermal infrared instruments, on the contrary, reach a better global coverage, because the performance in the near infrared is reduced over the oceans owing to a low surface albedo. Near infra-red sounders can compensate for this by measuring in sun-glint, which will allow accurate measurements over the oceans, at the cost, however, of a lower measurement density. Overall, the sun-glint pointing near infrared instrument is the most promising concept of those tested. We show that the ability of satellite instruments to resolve fluxes at smaller temporal and spatial scales is also related to surface sensitivity. All the satellite instruments performed relatively well over the continents resulting mainly from the larger prior flux uncertainties over land than over the oceans. In addition, the surface networks are rather sparse over land increasing the additional benefit of satellite measurements there. Globally, challenging satellite instrument precisions are needed to compete with the current surface network (about 1ppm for weekly and 8°x10° averaged SCIAMACHY columns). Regionally, however, these requirements relax considerably, increasing to 5ppm for SCIAMACHY over tropical continents. This points not only to an interesting research area using SCIAMACHY data, but also to the fact that satellite requirements should not be quantified by only a single number. The applicability of our synthetic results to real satellite instruments is limited by rather crude representations of instrument and data retrieval related uncertainties. This should receive high priority in future work.

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: SCIAMACHY CO2 measurements show a large variability in total column CO2 over the Sahara desert of up to 10%, which is not anticipated from in situ measurements and cannot be explained by results of atmospheric models. Comparisons with colocated aerosol measurements by TOMS and MISR over the Sahara indicate that the seasonal variation of SCIAMACHY-observed CO2 strongly resembles seasonal variations of windblown dust. Correlation coefficients of monthly datasets of colocated MISR aerosol optical depth and SCIAMACHY CO2 vary between 0.6 and 0.8, indicating that about half of the CO2 variance is explained by aerosol optical depth. Radiative transfer model calculations confirm the role of dust and can explain the size of the errors. Sensitivity tests suggest that the remaining variance may largely be explained by variations in the vertical distribution of dust. Further calculations for a few typical aerosol classes and a broad range of atmospheric conditions show that the impact of aerosols on SCIAMACHY retrieved CO2 is by far the largest over the Sahara, but may also reach significant levels elsewhere. Over the continents, aerosols lead mostly to overestimated CO2 columns with the exception of biomass burning plumes and dark coniferous forests. Inverse modelling calculations confirm that aerosol correction of SCIAMACHY CO2 measurements is needed to derive meaningful source and sink estimates. Methods for correcting aerosol-induced errors exist, but so far mainly on the basis of theoretical considerations. As demonstrated by this study, SCIAMACHY may contribute to a verification of such methods using real data.

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: The Bayesian framework of CO2 flux inversions permits estimates of the retrieved flux uncertainties. Here, the reliability of these theoretical estimates is studied through a comparison against the misfits between the inverted fluxes and independent measurements of the CO2 Net Ecosystem Exchange (NEE) made by the eddy covariance technique at local (few hectares) scale. Regional inversions at 0.5° resolution are applied for the western European domain where ~ 50 eddy covariance sites are operated. These inversions are conducted for the period 2002–2007. They use a mesoscale atmospheric transport model, a prior estimate of the NEE from a terrestrial ecosystem model and rely on the variational assimilation of in situ continuous measurements of CO2 atmospheric mole fractions. Averaged over monthly periods and over the whole domain, the misfits are in good agreement with the theoretical uncertainties for prior and inverted NEE, and pass the chi-square test for the variance at the 30% and 5% significance levels respectively, despite the scale mismatch and the independence between the prior (respectively inverted) NEE and the flux measurements. The theoretical uncertainty reduction for the monthly NEE at the measurement sites is 53% while the inversion decreases the standard deviation of the misfits by 38%. These results build confidence in the NEE estimates at the European/monthly scales and in their theoretical uncertainty from the regional inverse modelling system. However, the uncertainties at the monthly (respectively annual) scale remain larger than the amplitude of the inter-annual variability of monthly (respectively annual) fluxes, so that this study does not engender confidence in the inter-annual variations. The uncertainties at the monthly scale are significantly smaller than the seasonal variations. The seasonal cycle of the inverted fluxes is thus reliable. In particular, the CO2 sink period over the European continent likely ends later than represented by the prior ecosystem model.

Description: Spaceborne reflectance measurements from the POLDER instrument are used to study the specific directional signature close to the backscatter direction. The data analysis makes it possible to derive the extinction-to-backscatter ratio (EBR), which is related to the inverse of the scattering phase function for an angle of 180° and is needed for a quantitative interpretation of lidar observations (active measurements). In addition, the multidirectional measurements are used to quantify the scattering phase function variations close to backscatter, which also provide some indication of the aerosol particle size and shape. The spatial distributions of both parameters show consistent patterns that are consistent with the aerosol type distributions. Pollution aerosols have an EBR close to 70, desert dust values are on the order of 50 and EBR of marine aerosols is close to 25. The scattering phase function shows an increase with the scattering angle close to backscatter. The relative increase ∂lnP/∂γ is close to 0.01 for dust and pollution type aerosols and 0.06 for marine type aerosols. These values are consistent with those retrieved from Mie simulations.

Description: This paper suggests a method for improving current inventories of aerosol emissions from biomass burning. The method is based on the hypothesis that, although the total estimates within large regions are correct, the exact spatial and temporal description can be improved. It makes use of open fire detection from the ATSR instrument that is available since 1996. The emissions inventories are re-distributed in space and time according to the occurrence of open fires. Although the method is based on the night-time hot-spot product of the ATSR, other satellite biomass burning proxies (AVHRR, TRMM, GLOBSCAR and GBA2000) show similar distributions. The impact of the method on the emission inventories is assessed using an aerosol transport model, the results of which are compared to sunphotometer and satellite data. The seasonal cycle of aerosol load in the atmosphere is significantly improved in several regions, in particular South America and Australia. Besides, the use of ATSR fire detection may be used to account for interannual events, as is demonstrated on the large Indonesian fires of 1997, a consequence of the 1997-1998 El Niño. Despite these improvements, there are still some large discrepancies between the simulated and observed aerosol optical thicknesses resulting from biomass burning emissions.

Description: In this study, we provide a comprehensive analysis of aerosol interaction with warm boundary layer clouds, over South-East Atlantic. We use MODIS retrievals to derive statistical relationships between aerosol concentration and cloud properties, together with co-located CALIPSO estimates of cloud and aerosol layer altitudes. The latter are used to differentiate between cases of mixed and interacting cloud-aerosol layers from cases where the aerosol is located well-above the cloud top. This strategy allows, to a certain extent, to isolate real aerosol-induced effect from meteorology. Similar to previous studies, statistics clearly show that aerosol affects cloud microphysics, decreasing the Cloud Droplet Radius (CDR). The same data indicate a concomitant strong decrease in cloud Liquid Water Path (LWP), in evident contrast with the hypothesis of aerosol inhibition of precipitation (Albrecht, 1989). Because of this water loss, probably due to the entrainment of dry air at cloud top, Cloud Optical Thickness (COT) is found to be almost insensitive to changes in aerosol concentration. The analysis of MODIS-CALIPSO coincidences also evidenced an aerosol enhancement of low cloud cover. Surprising, the Cloud Fraction (CLF) response to aerosol invigoration is much stronger when (absorbing) particles are located above cloud top, than in cases of physical interaction, This result suggests a relevant aerosol radiative effect on low cloud occurrence. Heating the atmosphere above the inversion, absorbing particles above cloud top may decrease the vertical temperature gradient, increase the low tropospheric stability and provide favorable conditions for low cloud formation. We also focus on the impact of anthropogenic aerosols on precipitation, through the statistical analysis of CDR-COT co-variations. A COT value of 10 is found to be the threshold beyond which precipitation mostly forms, in both clean and polluted environments. For larger COT, polluted clouds showed evidence of precipitation suppression. Results suggest the presence of two competing mechanisms governing LWP response to aerosol invigoration: a drying effect due to aerosol enhanced entrainment of dry air at cloud top (predominant for optically thin clouds) and a moistening effect due to aerosol inhibition of precipitation (predominant for optically thick clouds).