Aerosols act as cloud condensation nuclei (CCN) for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE). Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion) to AIE from region to region. Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS), the sixyear mean anthropogenic + dust AIE is −0.27Wm−2 and is greatest during the summer months (<−2.0Wm−2) during which aerosol concentrations (from both dust and anthropogenic sources) are greatest. Comparing AIE as a function of thin (LWP<20 gm−2) vs. thick (LWP≥20 gm−2) clouds under conditions of large scale ascent or decent at 850 hPa showed that AIE is greatest for thick clouds during periods of upward vertical motion. In the Bay of Bengal, AIE is negligible owing to less favorable atmospheric conditions, a lower concentration of aerosols, and a non-alignment of aerosol and cloud layers. In the eastern North Atlantic, AIE is weakly positive (+0.1Wm−2) with dust aerosol concentration being much greater than the anthropogenic or sea salt components. However, elevated dust in this region exists above the maritime cloud layers and does not have a hygroscopic coating, which occurs in AS, preventing the dust from acting as CCN and limiting AIE. The Western Atlantic has a large anthropogenic aerosol concentration transported from the eastern United States producing a modest anthropogenic AIE (−0.46Wm−2). Anthropogenic AIE is also present off the West African coast corresponding to aerosols produced from seasonal biomass burning (both natural and man-made). Interestingly, atmospheric conditions are not particularly favorable for cloud formation compared to the other regions during the times where AIE is observed; however, clouds are generally thin (LWP<20 gm−2) and concentrated very near the surface. Overall, we conclude that vertical motion, aerosol type, and aerosol layer heights do make a significant contribution to AIE and that these factors are often more important than total aerosol concentration alone and that the relative importance of each differs significantly from region to region.

Aerosol indirect effects are considered to be the most uncertain yet important anthropogenic forcing of climate change. The goal of the present study is to reduce this uncertainty by constraining two different general circulation models (LMDZ and ECHAM4) with satellite data. We build a statistical relationship between cloud droplet number concentration and the optical depth of the fine aerosol mode as a measure of the aerosol indirect effect using MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data, and constrain the model parameterizations to match this relationship. We include here “empirical” formulations for the cloud albedo effect as well as parameterizations of the cloud lifetime effect. When fitting the model parameterizations to the satellite data, consistently in both models, the radiative forcing by the combined aerosol indirect effect is reduced considerably, down to −0.5 and −0.3Wm−2, for LMDZ and ECHAM4, respectively.

A weekly cycle in aerosol pollution and some meteorological quantities is observed over Europe. In the present study we exploit this effect to analyse aerosol-cloudradiation interactions. A weekly cycle is imposed on anthropogenic emissions in two general circulation models that include parameterizations of aerosol processes 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 those observed 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 modelled second aerosol indirect effects.

Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather similar, about −0.6Wm−2 to −0.7Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change in net shortwave forcing in the models due to varying the autoconversion scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model “noise”. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from −0.3Wm−2 to −1.4Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of 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 (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) 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 tau a 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–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, 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±0.5Wm−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 clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.

In this study, we examine the time evolution of the relative contribution of sulfate aerosols and greenhouse gases to anthropogenic climate change. We use the new IPSL-CM4 coupled climate model for which the first indirect effect of sulfate aerosols has been calibrated using POLDER satellite data. For the recent historical period the sulfate aerosols play a key role on the temperature increase with a cooling effect of 0.5 K, to be compared to the 1.4 K warming due to greenhouse gas increase. In contrast, the projected temperature change for the 21st century is remarkably independent of the effects of anthropogenic sulfate aerosols for the SRES-A2 scenario. Those results are interpreted comparing the different radiative forcings, and can be extended to other scenarios. We also highlight that the first indirect effect of aerosol strongly depends on the land surface model by changing the cloud cover.

The indirect effects of anthropogenic aerosols are expected to cause a significant radiative forcing of the Earth’s climate whose magnitude, however, is still uncertain. Most climate models use parameterizations for the aerosol indirect effects based on so-called ‘‘empirical relationships’’ which link the cloud droplet number concentration to the aerosol concentration. New satellite datasets such as those from the POLDER and MODIS instruments are well suited to evaluate and improve such parameterizations at a global scale. We derive statistical relationships of cloud-top droplet radius and aerosol index (or aerosol optical depth) from satellite retrievals and fit an empirical parameterization in a general circulation model to match the relationships. When applying the fitted parameterizations in the model, the simulated radiative forcing by the first aerosol indirect effect is reduced by 50% as compared to our baseline simulation (down to -0.3 and -0.4 Wm-2 when using MODIS and POLDER satellite data, respectively).

In their contribution to PNAS, Penner et al. (1) used a climate model to estimate the radiative forcing by the aerosol first indirect effect (cloud albedo effect) in two different ways: first, by deriving a statistical relationship between the logarithm of cloud droplet number concentration, ln Nc, and the logarithm of aerosol optical depth, ln AOD (or the logarithm of the aerosol index, ln AI) for present-day and preindustrial aerosol fields, a method that was applied earlier to satellite data (2), and, second, by computing the radiative flux perturbation between two simulations with and without anthropogenic aerosol sources. They find a radiative forcing that is a factor of 3 lower in the former approach than in the latter [as Penner et al. (1) correctly noted, only their “inline” results are useful for the comparison].

Realistic simulations of clouds are of uppermost importance for climate modelling using general circulation models. Satellite data are well suited to evaluate model parametrizations. In this study we use the Laboratoire de Me´te´orologie Dynamique general circulation model (LMDZ). We evaluate the current LMDZ cloud phase parametrization, in which the repartition of condensed cloud water between liquid and ice is a function of the local temperature. Three parameters are used to derive a relation between liquid cloud water content and temperature, two of which are not physically based. We use the POLDER-1 satellite data to infer more realistic parameters by establishing statistical relationships between cloud top thermodynamical phase and cloud top temperature, consistently in both satellite data and model results. We then perform a multitude of short model integrations and derive a best estimate for the lowest local temperature where liquid water can exist in a cloud (Tice = -32°C in our parametrization). The other parameter which describes the shape of the transition between ice and liquid water is also estimated. A longer simulation has then been performed with the new parameters, resulting in an improvement in the representation of the shortwave cloud radiative forcing.

Among anthropogenic perturbations of the Earth\''s atmosphere, greenhouse gases and aerosols are considered to have a major impact on the energy budget through their impact on radiative fluxes. We use three ensembles of simulations with the LMDZ general circulation model to investigate the radiative impacts of five species of greenhouse gases (CO2, CH4, N2O, CFC-11 and CFC-12) and sulfate aerosols for the period 1930-1989. Since our focus is on the atmospheric changes in clouds and radiation from greenhouse gases and aerosols, we prescribed sea surface temperatures in these simulations. Besides the direct impact on radiation through the greenhouse effect and scattering of sunlight by aerosols, strong radiative impacts of both perturbations through changes in cloudiness are analysed. The increase in greenhouse gas concentration leads to a reduction of clouds at all atmospheric levels, thus decreasing the total greenhouse effect in the longwave spectrum and increasing absorption of solar radiation by reduction of cloud albedo. Increasing anthropogenic aerosol burden results in a decrease in high-level cloud cover through a cooling of the atmosphere, and an increase in the low-level cloud cover through the second aerosol indirect effect. The trend in low-level cloud lifetime due to aerosols is quantified to 0.5 min day-1 decade-1 for the simulation period. The different changes in high (decrease) and low-level (increase) cloudiness due to the response of cloud processes to aerosols impact shortwave radiation in a contrariwise manner, and the net effect is slightly positive. The total aerosol effect including also the aerosol direct and first indirect effects remains strongly negative.