ALBERT

Beschreibung: An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.

Beschreibung: 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.

Beschreibung: An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7 funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gases analysis fields to document the dataset and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozone sondes and ACE-FTS data to within ±10% in most situations. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozone sondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area averaged total column ozone agrees with ozone fields from a multi sensor reanalysis data set to within a few percent. NO2 fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO2 maxima over anthropogenic pollution regions and overestimate NO2 in Northern and Southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the Eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.

Beschreibung: To date, North Sea tidal flat sediments have been intensively studied down to a depth of 5 m below sea floor (mbsf). However, little is known about the biogeochemistry, microbial abundance, and activity of sulfate reducers as well of methanogens in deeper layers. For this study, we hypothesized that the imprint of the paleo-environment is reflected in current microbiogeochemical processes. Therefore, 20 m-long cores were retrieved from the tidal-flat area of Spiekeroog Island, NW Germany. Two drill sites were selected with a close distance of only 900 meters, but where sedimentation occurred under different environmental conditions: first, a paleo-channel filled with Holocene sediments and second, a mainly Pleistocene sedimentary succession. In general, the numbers of bacterial 16S rRNA genes are one to two orders of magnitude higher than those of Archaea. The abundances of key genes for sulfate reduction and methanogenesis (dsrA and mcrA) correspond to the sulfate and methane profiles. A co-variance of these key genes at sulfate-methane interfaces and enhanced potential AOM rates suggest that anaerobic oxidation of methane may occur in these layers. Microbial and biogeochemical profiles are vertically stretched relative to 5 m-deep cores from shallower sediments in the same study area. Compared to the deep marine environment, the profiles are transitional between the shallow subsurface and the marine deep biosphere. Our interdisciplinary analysis shows that the microbial abundances and metabolic rates are elevated in the Holocene compared to Pleistocene sediments. However, this is mainly due to present environmental conditions such as pore water flow and organic matter availability. The paleo-environmental imprint is still visible but superimposed by these processes.

Beschreibung: Intact polar lipids (IPLs) are considered biomarkers for living biomass. Their degradation in marine sediments, however, is poorly understood and complicates interpretation of their occurrence in geological samples. To investigate the turnover of IPLs, a degradation experiment with anoxic sandy sediments from the North Sea was conducted. Intact cells of two organisms that do not naturally occur in North Sea sediments were chosen as IPL sources: (i) Saccharomyces cerevisiae, representative for ester-bound acyl lipids that also occur in Bacteria, and (ii) the archaeon Haloferax volcanii, representative for ether-bound isoprenoid lipids. Surprisingly, IPLs with phosphoester-bound head groups showed approximately the same degradation rate as IPLs with glycosidic head groups. Furthermore, the results indicate a relatively fast degradation of S. cerevisiae IPLs with ester-bound moieties (analogs of bacterial membrane lipids) and no significant degradation of archaeal IPLs with ether-bound moieties. Pore water and 16S rRNA-based DGGE analysis showed only a minor influence of the IPL source on microbial metabolism and community profiles. Due to our results, the IPL-based quantification of Archaea and Bacteria should be interpreted with caution.

Beschreibung: A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The goal of this study is to identify the current state of carbon observations and needs for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion (by several orders of magnitude) of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over remote areas such as the southern oceans, tropical forests and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in-situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases inter-operable, and on the calibration of each component of the system to agreed-upon international scales.

Beschreibung: Aerosols affect the atmosphere through the aerosol-radiation and the aerosol-clouds interactions. In this paper we report on a new mechanism whereby the radiative effect of dust aerosol on surface fluxes acts to increase the dust loading of the atmosphere via modification of boundary-layer stability, thereby acting to enhance the radiative aerosol effect. This positive feedback between dust aerosol and boundary layer stability occurred during a series of dust storms in the Sahara and the Eastern Mediterranean in April 2012, which were studied using the Monitoring Atmospheric Composition and Climate – Interim Implementation (MACC-II) system. The radiative fluxes in the shortwave and long-wave spectra were both significantly affected by the prognostic aerosols-radiation interation, which strongly influenced the meteorological simulation. Reduced incoming solar radiation below the aerosol layers caused a decrease in maximum surface temperatures, and consequently a more stable thermal stratification of the lower atmosphere. The increased thermal stability led to decreased surface wind speeds and therefore to smaller amounts of dust aerosol emissions. Larger downwelling long-wave fluxes were associated with the opposite processes: less stable thermal stratification at night, brought mainly by higher minimum temperatures at the surface, caused stronger surface winds. Overall, the impact by the long-wave radiative forcing was more important than the short-wave contribution. This feedback was amplified when taken into account in the aerosol analysis of the MACC-II global system. It lead to a notable improvement in short term forecast of short and long-wave radiative fluxes, of surface temperature but also of the aerosol burden itself. Forecasts of radiative fluxes in the shortwave and long-wave spectrum were also improved. At a longer range the improvement were less important as the forecast error of the aerosol load increased, thereby highlighting the importance of accurate aerosol representation in the study of aerosol-radiation interaction.

Beschreibung: A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

Beschreibung: The Monitoring Atmospheric Composition and Climate Interim Implementation (MACC-II) delayed-mode (DM) system has been producing an atmospheric methane (CH4) analysis 6 months behind real time since June 2009. This analysis used to rely on the assimilation of the CH4 product from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on board Envisat. Recently the extit{Laboratoire de Météorologie Dynamique} (LMD) CH4 products from the Infrared Atmospheric Sounding Interferometer (IASI) and the SRON Netherlands Institute for Space Research CH4 products from the Thermal And Near-infrared Sensor for carbon Observation (TANSO) were added to the DM system. With the loss of Envisat in April 2012, the DM system has to now rely on the assimilation of methane data from TANSO and IASI. This paper documents the impact of this change in the observing system on the methane tropospheric analysis. It is based on four experiments: one free run and three analyses from respectively the assimilation of SCIAMACHY, TANSO and a combination of TANSO and IASI CH4 products in the MACC-II system. The period between December 2010 and April 2012 is studied. This corresponds to a period during which the performance of SCIAMACHY was deteriorating. The SCIAMACHY experiment globally underestimates the tropospheric methane by 35 part per billion (ppb) compared to the HIAPER Pole-to-Pole Observations (HIPPO) data and the methane column by 23 ppb compared the Total Carbon Column Observing Network (TCCON) data, when the global bias of the free run against the same HIPPO and TCCON data is respectively −5 ppb and 4 ppb. The assimilated TANSO product changed in October 2011 from version v.1 to version v.2.0. The analysis of version v.1 globally underestimates the tropospheric methane by 18 ppb compared to the HIPPO data and the column by 11 ppb compared to the TCCON data. In contrast, the analysis of version v.2.0 globally overestimates the column by 10 ppb. When the high density IASI data are added in the tropical region between 30° N and 30° S, the resulting analysis is slightly less biased in the troposphere than the TANSO analysis when compared to the HIPPO data. In the meantime, this IASI plus TANSO analysis presents the worst correlation with the HIPPO data. In terms of column, the addition of the IASI data to the version v.2.0 of the TANSO data has a significant impact, mainly over extratropical regions, reducing the global bias to 6 ppb. The analysis based on the assimilation of the combination of TANSO and IASI products as well as the SCIAMACHY analysis should nevertheless be used with caution when looking at the seasonal cycle or inter-hemispheric gradient because of the unavailability of the measurements over large regions during the local winter period.

Beschreibung: 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.