Uncertainties in aerosol radiative forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of precipitation formation. In former assessments of aerosol radiative forcings, these effects have not been quantified. Also, with global aerosol-climate models simulating interactively aerosols and cloud microphysical properties, a quantification of the aerosol forcings in the traditional way is difficult to define properly. Here we argue that fast feedbacks should be included because they act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Based on our results, we recommend RFP as a valid option to compare different forcing agents, and to compare the effects of particular forcing agents in different models.

Statistical analysis of satellite data shows a positive correlation between aerosol optical depth (AOD) and total cloud cover (TCC). Reasons for this relationship have been disputed in recent literature. The aim of this study is to explore how different processes contribute to one model’s analog of the positive correlation between aerosol optical depth and total cloud cover seen in the satellite retrievals. We compare the slope of the linear regression between the logarithm of TCC and the logarithm of AOD, or the strength of the relationship, as derived from three satellite data sets to the ones simulated by a global aerosol-climate model. We analyse model results from two different simulations with and without a parameterisation of aerosol indirect effects, and using dry compared to humidified AOD. Perhaps not surprisingly we find that no single one of the hypotheses discussed in the literature is able to uniquely explain the positive relationship. However the dominant contribution to the model’s AOD-TCC relationship can be attributed to aerosol swelling in regions where humidity is high and clouds are coincidentally found. This finding leads us to hypothesise that much of the AOD-TCC relationship seen in the satellite data is also carried by such a process, rather than the direct effects of the aerosols on the cloud fields themselves.

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.

Aerosols have a significant effect on the global radiation budget through their interactions with radiation and clouds. However, estimates of their effect are the dominant source of uncertainty in current estimates of total anthropogenic effect on climate. A major cause of this uncertainty is the high degree of variability of aerosol properties and processes that affect their lifetime. Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. This thesis uses a synthesis of aerosol observations, global climate model (GCM) data, and a new aerosol modelling technique implemented within a regional-scale model to quantify the important scales of aerosol variability and the extent to which different sub-grid scale processes contribute to discrepancies in aerosol modelling. Analysis of black carbon (BC) plumes from aircraft observations shows that BC plumes represent a large portion of total BC mass and typically exist on scales of 65{ 100 km. Comparison of observed plume scales to those simulated by GCMs at multiple resolutions show that GCMs overestimate the scales of along- ight-track variability by 64% at the highest resolution. Variability is shown to be greater near sources than in remote regions, indicating that models may benefit from higher resolutions in regions of high emissions. Additionally, GCMs at all resolutions show higher variability in the latitudinal direction than the longitudinal direction, suggesting that capturing latitudinal variability may result in greater improvements in aerosol modelling. This work additionally presents a novel technique to allow one to isolate the effect of aerosol variability from other sources of variability within the model. Processes most affected by neglecting aerosol sub-grid variability are gas-phase chemistry and aerosol uptake of water through the aerosol/gas equilibrium reactions. The inherent non-linearities in these processes result in large changes in aerosol parameters when aerosol and gaseous species are artificially mixed over large spatial scales. These changes in aerosol and gas concentrations are exaggerated by convective transport, which transports these altered concentrations to altitudes where their effect is more pronounced. Future aerosol model development should focus on accounting for the effect of sub-grid variability on these processes at global scales in order to improve model predictions of the aerosol effect on climate.

Over the last decades, it has become clear that the size and chemical composition of atmospheric aerosol (AA) has a major impact on both human health and a number of processes in the atmosphere. Although there are increasing efforts to describe the behavior of AA, many phenomena are still not sufficiently understood to be able to predict aerosol behavior and associated phenomena to a satisfactory degree. This PhD thesis describes aerosol behavior at high temporal resolution within three main topics. The first topic is the description of the chemical and size composition of the non-refractory PM1 (NR-PM1) fraction at the Prague - Suchdol suburban station and the study of the influence of meteorological phenomena on the behavior of this aerosol. In order to identify seasonal effects, measurements were carried out in summer and winter. Positive Matrix Factorization (PMF) analysis was performed in connection with the aerosol description at the station, which identified chemically resolved mass profiles of aerosol sources and their temporal evolution. The second topic is the penetration of aerosol particles from the outdoor to the indoor environment. The influence of particle size and chemical composition on the penetration of particles from the outdoor to the indoor environment was investigated by...

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