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: Based on about 20 years of NOAA/CMDL's atmospheric CO2 concentration data and a global atmospheric tracer transport model, we estimate interannual variations and spatial patterns of surface CO2 fluxes in the period 01/1982-12/2000, by using a time-dependent Bayesian inversion technique. To increase the reliability of the estimated temporal features, particular care is exerted towards the selection of data records that are homogeneous in time. Fluxes are estimated on a grid-scale resolution (~8º latitude x 10º longitude), constrained by a-priori spatial correlations, and then integrated over different sets of regions. The transport model is driven by interannually varying re-analyzed meteorological fields. We make consistent use of unsmoothed measurements. In agreement with previous studies, land fluxes are estimated to be the main driver of interannual variations in the global CO2 fluxes, with the pace predominantly being set by the El Niño/La Niña contrast. An exception is a 2-3 year period of increased sink of atmospheric carbon after Mt.  Pinatubo's volcanic eruption in 1991. The largest differences in fluxes between El Niño and La Niña are found in the tropical land regions, the main share being due to the Amazon basin. The flux variations for the Post-Pinatubo period, the 1997/1998 El Niño, and the 1999 La Niña events are exploited to investigate relations between CO2 fluxes and climate forcing. A rough comparison points to anomalies in precipitation as a prominent climate factor for short-term variability of tropical land fluxes, both through their role on NPP and through promoting fire in case of droughts. Some large flux anomalies seem to be directly related to large biomass burning events recorded by satellite observation. Global ocean carbon uptake shows a trend similar to the one expected if ocean uptake scales proportional to the anthropogenic atmospheric CO2 perturbation. In contrast to temporal variations, the longterm spatial flux distribution can be inferred with lesser robustness only. The tentative pattern estimated by the present inversion exhibits a northern hemisphere land sink on the order of 0.4 PgC/yr (for 01/1996-12/1999, non-fossil fuel carbon only) that is mainly confined to North America. Southern hemisphere land regions are carbon neutral, while the tropical land regions are taking up carbon (e.g., at a rate of 0.8 PgC/yr during 01/1996-12/1999). Ocean fluxes show larger uptake in the Northern mid to high latitudes than in the Southern mid latitude regions, in contrast to the estimates by Takahashi et al. (1999) based on in-situ measurements. On a regional basis, results that differ the most from previous estimates are large carbon uptake of 1 to 1.5 PgC/yr by the Southern temperate Pacific ocean region, weak outgassing from the Southern ocean, and a carbon source from eastern Europe.

Description: The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain sites as well as flasks sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation – data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. The main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models through inverse methods are given in the following: 1) Low altitude stations are presently preferable in inverse studies. If high altitude stations are used then the model level that represents the specific sites should be applied, 2) at low altitude sites only the afternoon values of concentrations can be represented sufficiently well by current models and therefore afternoon values are more appropriate for constraining large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robustly in models than surface station records, which emphasize the use of tower data in inverse studies and finally 4) traditional large scale transport models seem not sufficient to resolve fine-scale features associated with fossil fuel emissions, as well as larger-scale features like the concentration distribution above the south-western Europe. It is therefore recommended to use higher resolution models for interpretation of continental data in future studies.

Description: The ratio of CO2 accumulating in the atmosphere to the CO2 flux into the atmosphere due to human activity, the airborne fraction AF, is central to predict changes in earth's surface temperature due to greenhouse gas induced warming. This ratio has remained remarkably constant in the past five decades, but recent studies have reported an apparent increasing trend and interpreted it as an indication for a decrease in the efficiency of the combined sinks by the ocean and terrestrial biosphere. We investigate here whether this interpretation is correct by analyzing the processes that control long-term trends and decadal-scale variations in the AF. To this end, we use simplified linear models for describing the time evolution of an atmospheric CO2 perturbation. We find firstly that the spin-up time of the system for the AF to converge to a constant value is on the order of 200–300 years and differs depending on whether exponentially increasing fossil fuel emissions only or the sum of fossil fuel and land use emissions are used. We find secondly that the primary control on the decadal time-scale variations of the AF is variations in the relative growth rate of the total anthropogenic CO2 emissions. Changes in sink efficiencies tend to leave a smaller imprint. Therefore, before interpreting trends in the AF as an indication of weakening carbon sink efficiency, it is necessary to account for trends and variations in AF stemming from anthropogenic emissions and other extrinsic forcing events, such as volcanic eruptions. Using atmospheric CO2 data and emission estimates for the period 1959 through 2006, and our simple predictive models for the AF, we find that likely omissions in the reported emissions from land use change and extrinsic forcing events are sufficient to explain the observed long-term trend in AF. Therefore, claims for a decreasing long-term trend in the carbon sink efficiency over the last few decades are currently not supported by atmospheric CO2 data and anthropogenic emissions estimates.

Description: The land and ocean absorb on average over half of the anthropogenic emissions of carbon dioxide (CO2) every year. These CO2 "sinks" are modulated by climate change and variability. Here we use a suite of nine Dynamic Global Vegetation Models (DGVMs) and four Ocean Biogeochemical General Circulation Models (OBGCMs) to quantify the global and regional climate and atmospheric CO2 – driven trends in land and oceanic CO2 exchanges with the atmosphere over the period 1990–2009, attribute these trends to underlying processes, and quantify the uncertainty and level of model agreement. The models were forced with reconstructed climate fields and observed global atmospheric CO2; Land Use and Land Cover Changes are not included for the DGVMs. Over the period 1990–2009, the DGVMs simulate a mean global land carbon sink of −2.4 ± 0.7 Pg C yr−1 with a small significant trend of −0.06 ± 0.03 Pg C yr−2 (increasing sink). Over the more limited period 1990–2004, the ocean models simulate a mean ocean sink of –2.2 ± 0.2 Pg C yr–1 with a trend in the net C uptake that is indistinguishable from zero (−0.01 ± 0.02 Pg C yr−2). The two ocean models that extended the simulations until 2009 suggest a slightly stronger, but still small trend of −0.02 ± 0.01 Pg C yr−2. Trends from land and ocean models compare favourably to the land greenness trends from remote sensing, atmospheric inversion results, and the residual land sink required to close the global carbon budget. Trends in the land sink are driven by increasing net primary production (NPP) whose statistically significant trend of 0.22 ± 0.08 Pg C yr−2 exceeds a significant trend in heterotrophic respiration of 0.16 ± 0.05 Pg C yr−2 – primarily as a consequence of wide-spread CO2 fertilisation of plant production. Most of the land-based trend in simulated net carbon uptake originates from natural ecosystems in the tropics (−0.04 ± 0.01 Pg C yr−2), with almost no trend over the northern land region, where recent warming and reduced rainfall offsets the positive impact of elevated atmospheric CO2 on carbon storage. The small uptake trend in the ocean models emerges because climate variability and change, and in particular increasing sea surface temperatures, tend to counteract the trend in ocean uptake driven by the increase in atmospheric CO2. Large uncertainty remains in the magnitude and sign of modelled carbon trends in several regions, and on the influence of land use and land cover changes on regional trends.

Description: Despite the importance of soil processes for global biogeochemical cycles, our capability for predicting soil evolution over geological timescales is poorly constrained. We attempt to probe our understanding and predictive capability of this evolutionary process by developing a mechanistic soil evolution model, based on an existing model framework, and comparing the predictions with observations from soil chronosequences in Hawaii. Our soil evolution model includes the major processes of pedogenesis: mineral weathering, percolation of rainfall, leaching of solutes, surface erosion, bioturbation and vegetation interactions and can be applied to various bedrock compositions and climates. The specific properties the model simulates over timescales of tens to hundreds of thousand years are, soil depth, vertical profiles of elemental composition, soil solution pH and organic carbon distribution. We demonstrate with this model the significant role that vegetation plays in accelerating the rate of weathering and hence soil profile development. Comparisons with soils that have developed on Hawaiian basalts reveal a remarkably good agreement with Na, Ca and Mg profiles suggesting that the model captures well the key components of soil formation. Nevertheless, differences between modelled and observed K and P are substantial. The fact that these are important plant nutrients suggests that a process likely missing from our model is the active role of vegetation in selectively acquiring nutrients. This study therefore indirectly indicates the valuable role that vegetation can play in accelerating the weathering and thus release of these globally important nutrients into the biosphere.