Search

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the models explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and τa as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld – τa relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR – τa relationship show a strong positive correlation between τa and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm−2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrieved Nd – τa regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of −0.4±0.2 Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm−2, with a total estimate of −1.2±0.4 Wm−2.

Sulfur dioxide (SO2) plays a key role in atmospheric chemistry with important implications for air quality and climate forcing. Fossil fuels such as coal and oil contain significant amounts of sulfur. When burned, sulfur is generally converted to SO2. In this study we focus on SO2 emissions from non-ferrous metal smelters in Siberia, Russia and Peru. We have evaluated the SO2 anthropogenic emissions inventories from MOZART and AEROCOM for the year 2003. Total sulfur burden for the year 2003 for each emission inventories are calculated and evaluated. A new emission inventory of SO2 emissions for the year 2003 was developed as a part of the GEMS European project, which includes non-ferrous smelters emissions, especially from Norilsk Siberia and Peru: point sources emissions from these smelters are updated according to available literature values. Simulations have been performed with the MOZART3 chemistry-transport model, using the standard and updated emission inventories for the year 2003.The differential optical absorption spectroscopy (DOAS) technique has been used to retrieve SO2 column amounts from the observations performed by the SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric ChartographY) satellite-based instrument. The SCIAMACHY observations will be compared with the model results, particularly over the smelter regions.

A weekly cycle in aerosol pollution and meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloud-radiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol cycles and cloud microphysics. It is found that the simulated weekly cycles in sulfur dioxide, sulfate, and aerosol optical depth in both models agree reasonably well with the observed ones indicating model skill in simulating the aerosol cycle. A distinct weekly cycle in cloud droplet number concentration is demonstrated in both observations and models. For other variables, such as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation fluxes, precipitation, and surface temperature, large variability and contradictory results between observations, model simulations, and model control simulations without a weekly cycle in emissions prevent us from reaching any firm conclusions about the potential aerosol impact on meteorology or the realism of the modeled second aerosol indirect effects.

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and τa as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–τa relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR–τa relationship show a strong positive correlation between τa and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrieved Nd–τa regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2 Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm−2, with a total estimate of −1.2±0.4 Wm−2.

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) from AERONET and Ozone Monitoring Instrument (OMI) retrievals and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retreivals, the models are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.6 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50 N, the average model is a factor of 10 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC is 0.6 and underestimates the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes suggests that most models are underestimating BC absorption and should improve estimates for refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models.

The main uncertainty in anthropogenic forcing of the Earth’s climate stems from pollution aerosols, particularly their ‘‘indirect effect’’ whereby aerosols modify cloud properties. We develop a new methodology to derive a measurement-based estimate using almost exclusively information from an Earth radiation budget instrument (CERES) and a radiometer (MODIS). We derive a statistical relationship between planetary albedo and cloud properties, and, further, between the cloud properties and column aerosol concentration. Combining these relationships with a data set of satellite-derived anthropogenic aerosol fraction, we estimate an anthropogenic radiative forcing of -0.9 ± 0.4 Wm-2 for the aerosol direct effect and of -0.2 ± 0.1 Wm-2 for the cloud albedo effect. Because of uncertainties in both satellite data and the method, the uncertainty of this result is likely larger than the values given here which correspond only to the quantifiable error estimates. The results nevertheless indicate that current global climate models may overestimate the cloud albedo effect.

Inventories for global aerosol and aerosol precursor emissions, and auxiliary information, have been collected, assessed and prepared for the year 2000 (present-day conditions) and for the year 1750 (pre-industrial conditions). These global datasets establish a reference for input in global modeling, when simulating the aerosol impact on climate with state-of-the-art aerosol component modules. These modules stratify aerosol by type, distinguishing among dust, seasalt, sulfate, organic matter and soot. The datasets are also intented to serve as systematic constraints in sensitivity studies of the AeroCom initiative, which aims to evaluate uncertainties in aerosol global modeling. The datasets comprise daily size-resolved emissions of sea-salt and dust and monthly-to-yearly emissions for all other currently known emissions of natural and anthropogenic aerosol (precursors). The emissions are a reference dataset for aerosol modeling in the coming years and benchmark the emissions according to our knowledge in the year 2004.

The AeroCom exercise diagnoses multi-component aerosol modules in global modeling. In an initial assessment simulated global distributions for mass and mid-visible aerosol optical thickness (aot) were compared among 20 different modules. Model diversity was also explored in the context of previous comparisons. For the component combined aot general agreement has improved for the annual global mean. At 0.11 to 0.14, simulated aot values are at the lower end of global averages suggested by remote sensing from ground (AERONET ca. 0.135) and space (satellite composite ca. 0.15). More detailed comparisons, however, reveal that larger differences in regional distribution and significant differences in compositional mixture remain. Of particular concern are large model diversities for contributions by dust and carbonaceous aerosol, because they lead to significant uncertainty in aerosol absorption (aab). Since aot and aab, both, influence the aerosol impact on the radiative energy-balance, the aerosol (direct) forcing uncertainty in modeling is larger than differences in aot might suggest. New diagnostic approaches are proposed to trace model differences in terms of aerosol processing and transport: These include the prescription of common input (e.g. amount, size and injection of aerosol component emissions) and the use of observational capabilities from ground (e.g. measurements networks) or space (e.g. correlations between aerosol and clouds).

Inventories for global aerosol and aerosol precursor emissions have been collected (based on published inventories and published simulations), assessed and prepared for the year 2000 (present-day conditions) and for the year 1750 (pre-industrial conditions). These global datasets establish a comprehensive source for emission input to global modeling, when simulating the aerosol impact on climate with state-of-the-art aerosol component modules. As these modules stratify aerosol into dust, sea-salt, sulfate, organic matter and soot, for all these aerosol types global fields on emission strength and recommendations for injection altitude and particulate size are provided. Temporal resolution varies between daily (dust and sea-salt), monthly (wild-land fires) and annual (all other emissions). These datasets benchmark aerosol emissions according to the knowledge in the year 2004. They are intended to serve as systematic constraints in sensitivity studies of the AeroCom initiative, which seeks to quantify (actual) uncertainties in aerosol global modeling.

The AeroCom exercise diagnoses multi-component aerosol modules in global modeling. In an initial assessment simulated global distributions for mass and mid-visible aerosol optical thickness (aot) were compared among 20 different modules. Model diversity was also explored in the context of previous comparisons. For the component combined aot general agreement has improved for the annual global mean. At 0.11 to 0.14, simulated aot values are at the lower end of global averages suggested by remote sensing from ground (AERONET ca. 0.135) and space (satellite composite ca. 0.15). More detailed comparisons, however, reveal that larger differences in regional distribution and significant differences in compositional mixture remain. Of particular concern are large model diversities for contributions by dust and carbonaceous aerosol, because they lead to significant uncertainty in aerosol absorption (aab). Since aot and aab, both, influence the aerosol impact on the radiative energy-balance, the aerosol (direct) forcing uncertainty in modeling is larger than differences in aot might suggest. New diagnostic approaches are proposed to trace model differences in terms of aerosol processing and transport: These include the prescription of common input (e.g. amount, size and injection of aerosol component emissions) and the use of observational capabilities from ground (e.g. measurements networks) or space (e.g. correlations between aerosol and clouds)., Atmospheric Chemistry and Physics, 6 (7), ISSN:1680-7375, ISSN:1680-7367

[ 1] Climatological mean estimates of forest burning and crop waste burning based on broad assumptions of the amounts burned have so far been used for India in global inventories. Here we estimate open biomass burning representative of 1995 - 2000 from forests using burned area and biomass density specific for Indian ecosystems and crop waste burning as a balance between generation and known uses as fuel and fodder. High-resolution satellite data of active fires and land cover classification from MODIS, both on a scale of 1 km x 1 km, were used to capture the seasonal variability of forest and crop waste burning and in conjunction with field reporting. Correspondence in satellite-detected fire cycles with harvest season was used to identify types crop waste burned in different regions. The fire season in forest areas was from February to May, and that in croplands varied with geographical location, with peaks in April and October, corresponding to the two major harvest seasons. Spatial variability in amount of forest biomass burned differed from corresponding forest fire counts with biomass burned being largest in central India but fire frequency being highest in the east-northeast. Unutilized crop waste and MODIS cropland fires were predominant in the western Indo-Gangetic plain. However, the amounts of unutilized crop waste in the four regions were not strictly proportional to the fire counts. Fraction crop waste burned in fields ranged from 18 to 30% on an all-India basis and had a strong regional variation. Open burning contributes importantly ( about 25%) to black carbon, organic matter, and carbon monoxide emissions, a smaller amount ( 9 - 13%) to PM2.5 ( particulate mass in particles smaller than 2.5 micron diameter) and CO2 emissions, and negligibly to SO2 emissions (1%). However, it cannot explain a large "missing source'' of BC or CO from India.

A hearing was organized by the European Commission (DG Environment and DG Joint Research Centre) on behalf of the European Union Climate Change Expert Group on Science, with the aim to update non-expert policy-makers on the role of aerosols in the climate system. The focus was on new knowledge that came available since the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC TAR, 2001). The present report does not pretend to provide information with the status of the IPCC. The experts anyway agreed that the following statements are robust, hence that they are not likely to change as scientific uncertainties are further reduced: • the increase of the atmospheric aerosol concentration since pre-industrial times (1750) has resulted globally in a cooling, which magnitude is significant when compared with the warming due to greenhouse gases (GHG). • the probability that the climate sensitivity is in the upper part of the range proposed by the IPCC TAR, i.e. larger than 2.5 °C for a doubling of the atmospheric CO2 concentration, is therefore higher. • reductions of black carbon and organic matter emissions from fossil fuel combustion (diesel in particular) would be beneficial for human health and would very likely counter-act partially the warming expected from ongoing reductions in sulfate and nitrate aerosols. • in order to stabilize CO2 equivalent concentrations there is an urgent need to reduce CO2 emissions, however the potential of reducing non-CO2 greenhouse gases, in particular CH4 and tropospheric ozone, should be explored as well.

The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24-48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24-48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.

We estimate aerosol absorption over the clear-sky oceans using aerosol geophysical products from POLDER-1 space measurements and absorption properties from ground-based AERONET measurements. Our best estimate is 2.5 Wm-2 averaged over the 8-month lifetime of POLDER-1. Low and high absorption estimates are 2.2 and 3.1 Wm-2 based on the variability in aerosol single scattering albedo observed by AERONET. Main sources of uncertainties are the discrimation of the aerosol type from satellite measurements, and potential clear-sky bias induced\ud by the cloud-screening procedure.