The response of cloud processes to an aerosol perturbation is one of the largest uncertainties in the anthropogenic forcing of the climate. It occurs at a variety of timescales, from the near-instantaneous Twomey effect to the longer timescales required for cloud adjustments. Understanding the temporal evolution of cloud properties following an aerosol perturbation is necessary to interpret the results of so-called “natural experiments” from a known aerosol source such as a ship or industrial site. This work uses reanalysis wind fields and ship emission information matched to observations of ship tracks to measure the timescales of cloud responses to aerosol in instantaneous (or“snapshot”) images taken by polar-orbiting satellites. As in previous studies, the local meteorological environment is shown to have a strong impact on the occurrence and properties of ship tracks, but there is a strong time dependence in their properties. The largest droplet number concentration (Nd) responses are found within 3 h of emission, while cloud adjustments continue to evolve over periods of 10 h or more. Cloud fraction is increased within the early life of ship tracks, with the formation of ship tracks in otherwise clear skies indicating that around 5 %–10%of clear-sky cases in this region may be aerosol-limited. The liquid water path (LWP) enhancement and the Nd– LWP sensitivity are also time dependent and strong functions of the background cloud and meteorological state. The nearinstant response of the LWP within ship tracks may be evidence of a bias in estimates of the LWP response to aerosol derived from natural experiments. These results highlight the importance of temporal development and the background cloud field for quantifying the aerosol impact on clouds, even in situations where the aerosol perturbation is clear.

Aerosols are thought to have a large effect on the climate, especially through their interactions with clouds. The magnitude and in some cases the sign of aerosol effects on cloud and precipitation are highly uncertain. Part of the uncertainty comes from the multiple competing effects that aerosols have been proposed to have on cloud properties. In addition, covariation of clouds and aerosol properties with changing meteorological conditions has the ability to generate spurious correlations between cloud and aerosol properties. This work presents a new way to investigate aerosol-cloud-precipitation interactions while accounting for the influence of meteorology on cloud and aerosol. The clouds are separated into cloud regimes, which have similar retrieved cloud properties, to investigate the regime dependence of aerosol-cloud-precipitation interactions. The strong aerosol optical depth (AOD)- cloud fraction (CF) correlation is shown to have the ability to generate spurious correlations. The AOD-CF correlation is accounted for by investigating the frequency of transitions between cloud regimes in different aerosol environments. This time-dependent analysis is also extended to investigate the development of precipitation from each of the regimes as a function of their aerosol environment. A modification of the regime transition frequencies consistent with an increase in stratocumulus persistence over ocean is found with increasing AI (aerosol index). Increases in transitions into the deep convective regime and in the precipitation rate consistent with an aerosol invigoration effect are also found over land. Comparisons to model output suggest that a large fraction of the observed effect on the stratocumulus persistence may be due to aerosol indirect effects. The model is not able to reproduce the observed effects on convective cloud, most likely due to the lack of parametrised effects of aerosol on convection. The magnitude of these effects is considerably smaller than correlations found by previous studies, emphasising the importance of meteorological covariation on observed aerosol-cloud-precipitation interactions.

The aerosol direct and indirect effects were investigated for three specific cases during the March 2000 Cloud IOP at the SGP site by using a modified WRF model. The WRF model was previously altered to include a two-moment bulk microphysical scheme for the aerosol indirect effect and a modified Goddard shortwave radiation scheme for the aerosol direct effect. The three cases studied include a developing low pressure system, a low precipitation event of mainly cirrus clouds, and a cold frontal passage. Three different aerosol profiles were used with surface concentrations ranging from 210 cm-3 to 12,000 cm-3. In addition, each case and each aerosol profile was run both with and without the aerosol direct effect. Regardless of the case, increasing the aerosol concentration generally increased cloud water and droplet values while decreasing rain water and droplet values. Increased aerosols also decreased the surface shortwave radiative flux for every case; which was greatest when the aerosol direct effect was included. For convective periods during polluted model runs, the aerosol direct effect lowered the surface temperature and reduced convection leading to a lower cloud fraction. During most convective periods, the changes to cloud, rain, and ice water mixing ratios and number concentrations produced a nonlinear precipitation trend. A balance between these values was achieved for moderate aerosol profiles, which produced the highest convective precipitation rates. In non-convective cases, due to the presence of ice particles, aerosol concentration and precipitation amounts were positively correlated. The aerosol threshold between precipitation enhancement and suppression should be further studied for specific cloud types as well as for specific synoptic weather patterns to determine its precise values.

This research focuses on aircraft observational studies of aerosol-cloud interactions in cumulus clouds. The data were collected in the summer of 2004, the spring of 2007 and the mid-winter and spring of 2008 in Texas, central Saudi Arabia and Istanbul, Turkey, respectively. A set of 24 pairs of sub-cloud aerosol and cloud penetration data are analyzed. Measurements of fine and coarse mode aerosol concentrations from 3 different instruments were combined and fitted with lognormal distributions. The fit parameters of the lognormal distributions are compared with cloud droplet effective radii retrieved from 260 cloud penetrations. Cloud condensation nuclei (CCN) measurements for a subset of 10 cases from the Istanbul region are compared with concentrations predicted from aerosol size distributions. Ammonium sulfate was assumed to represent the soluble component of aerosol with dry sizes smaller than 0.5 mm and sodium chloride for aerosol larger than 0.5 mm. The measured CCN spectrum was used to estimate the soluble fraction. The correlations of the measured CCN concentration with the predicted CCN concentration were strong (R2 > 0.89) for supersaturations of 0.2, 0.3 and 0.6%. The measured concentrations were typically consistent with an aerosol having a soluble fraction between roughly 0.5 and 1.0, suggesting a contribution of sulfate or some other similarly soluble inorganic compound. The predicted CCN were found to vary by +or-3.7% when the soluble fraction was varied by 0.1. Cumulative aerosol concentrations at cutoff dry diameters of 1.1, 0.1 and 0.06 mm were found to be correlated with cloud condensation nuclei concentrations but not with maximum cloud base droplet concentrations. It is also shown that in some cases the predominant mechanisms involved in the formation of precipitation were altered and modified by the aerosol properties. This study suggests that CCN-forced variations in cloud droplet number concentration can change the effective radius profile and the type of precipitation hydrometeors. These differences may have a major impact on the global hydrological cycle and energy budget.

Im Rahmen dieser Dissertation wurden die mikrophysikalischen Eigenschaften von Aerosolpartikeln im Passatklima und deren Einfluss auf Passatwolken untersucht. Die Arbeit basiert auf Messungen mit der hubschrauber-getragenen Messplattform ACTOS. Es wurden zwei Intensivmesskampagnen im November 2010 und April 2011 durchgeführt, welche 31 Forschungsflüge in der Nähe der östlichsten Karibik-Insel Barbados umfassen. Die gemessenen Partikel-Anzahl-Größenverteilungen weisen meist eine bimodale Verteilung auf, welche typisch für marines Aerosol ist. Im Vergleich zu kontinentalen Verhältnissen ist die Totalanzahlkonzentration der Aerosolpartikel von 100-1000 cm-3 gering. Eine statistische Analyse einzelner Wolken lässt auf typische Anzahlkonzentrationen von aktivierten Partikeln bis zu 400 cm-3 und minimale Aktivierungsdurchmesser in der Größenordnung von 40 nm bis 180 nm mit entsprechenden maximalen kritischen Übersättigungen zwischen 0.1 und 0.9% schließen. Zusätzlich wurden wesentliche Einflussfaktoren auf die Anzahlkonzentration aktivierter Partikel identifiziert: 1) Vertikalwind an der Wolkenunterkante und 2) Anzahlkonzentration der verfügbaren Aerosolpartikel, die als Wolkenkondensationskeime dienen können. Mit Hilfe von Beobachtungsdaten und einer umfassenden Sensitivitätsstudie unter Verwendung eines Luftpaketmodells mit spektraler Wolkenmikrophysik wurde die Sensitivität der Wolkentropfenkonzentration gegenüber Änderungen in den physikalischen Eigenschaften und der Hygroskopizität von Aerosolpartikeln untersucht. Die beobachteten Ergebnisse in Form von sogenannten \"aerosol-cloud interaction metrics\" (ACI, Maß für den Einfluss von Änderungen einer bestimmten Aerosoleigenschaft auf eine bestimmte Wolkeneigenschaft) zeigen eine sehr hohe Sensitivität der Tropfenanzahlkonzentration gegenüber Änderungen in der Partikelanzahlkonzentration (in der Nähe des physikalisch sinnvollen Maximums von eins). Diese abgeleiteten ACI-Metriken eignen sich als Basis für Abschätzungen des indirekten Strahlungsantriebes auf der Grundlage von Beobachtungen. Zusätzliche Modellrechnungen umfassen die gemessenen Partikeleigenschaften während der gesamten Kampagnen. Die Ergebnisse unterstreichen besonders die Bedeutung der physikalischen Partikeleigenschaften. Die Suszeptibilität der Tropfenanzahlkonzentration gegenüber Änderungen in der Partikelanzahlkonzentration (Wertebereich: 0-1) ist am größten (> 0.9) für den Fall eines stark ausgeprägten Akkumulations-Mode und nimmt ab, je stärker der Aitken-Mode ausgeprägt ist (> 0.6). Im Gegensatz dazu ist die Sensitivität der Tropfenanzahlkonzentration gegenüber Änderungen in der Hygroskopizität der Partikel generell geringer (< 0.4). Die hier präsentierten Ergebnisse stellen eine umfangreiche Charakterisierung der Aerosol- und Wolkeneigenschaften im Passatklima dar und können helfen, die vorhergesagte Sensitivität der Wolkeneigenschaften in Klimamodellen gegenüber Änderungen der Aerosoleigenschaften zu evaluieren und deren Unsicherheiten zu reduzieren. / Within the scope of this dissertation, microphysical properties of aerosol particles in the trade wind regime and their influence on microphysical properties of trade wind cumulus clouds have been investigated. The study is based on measurements performed with the helicopter-borne measurement platform ACTOS. Two intensive measurement periods were carried out in November 2010 and April 2011, including 31 research flights close to the easternmost Caribbean island - Barbados. Aerosol particle number size distributions show a bimodal structure, which is typical for marine aerosol particles. The total particle concentrations of approximately 100-1000 cm-3 are compared to continental conditions relatively low. A statistical analysis of individual clouds reveals typical number concentrations of activated particles up to 400 cm-3 and minimum activation diameters between 40 and 180 nm with corresponding critical supersaturations between 0.1 and 1%. Additionally, major factors affecting the number concentration of activated particles are identifed: 1) vertical wind velocity at cloud base and, 2) number concentration of available aerosol particles as potential cloud condensation nuclei. With the help of observational data and a comprehensive sensitivity study using a spectral cloud microphysical parcel model, the sensitivity of the cloud droplet number concentration towards changes in the microphysical aerosol particle properties and their hygroscopicity has been investigated. Observational results in terms of so-called aerosol-cloud interactions metrics (describes a measure of the influence of changes in one specific aerosol property on one specific cloud property) show a very high sensitivity (close to the physical meaningful maximum of unity) of the number concentration of activated particles towards changes in the particle number concentration. These aerosol-cloud interaction metrics can be used as basis for observationally-based radiative forcing estimates. Additional model calculations cover the entire range of the observed aerosol properties during both campaigns. The results underline particularly the importance of the physical aerosol properties. The calculated susceptibility (valuation: 0-1) of the droplet number concentration towards changes in the particle number concentration is highest (> 0.9) for accumulation mode dominated particle number size distributions and decreases for Aitken mode dominated size distributions (> 0.6). In contrast, for the modeled parameter space, the sensitivity towards changes in the particle hygroscopicity is generally below 0.4. The findings presented in this study represent a comprehensive characterization of aerosol and cloud microphysical properties in the trade wind regime. These findings may help to evaluate the predicted sensitivity of cloud microphysical properties by climate models towards changes in particle microphysical properties and reduce the uncertainties in climate sensitivity estimates.

Atmospheric particles can affect climate directly, by scattering solar radiation, or indirectly, by acting as the seed upon which cloud droplets form. These clouds can then cool the earth's surface by reflecting incoming sunlight. In order to constrain the large uncertainties in predicting the ultimate effect of aerosol on climate, the sources of atmospheric particles and their subsequent ability to turn into cloud droplets needs to be better understood. This thesis addresses two parts of this issue: the sources of Arctic aerosol and the hygroscopicity of continental organic aerosol. Small particles were observed in Baffin Bay during September 2008 that coincided with high atmospheric and ocean surface dimethyl sulphide (DMS) concentrations suggesting that the aerosol formed from oceanic sources. An aerosol microphysics box model confirmed that local DMS could have produced the observed particles. In addition, the particle chemical composition was measured using aerosol mass spectrometry in the central Arctic Ocean in August 2008 and particles were found to be 43% organic and 46% sulphate. Factor analysis further apportioned the aerosol mass to marine biogenic and continental sources 33% and 36% of the time, respectively, with the source of the remaining mass unidentified. The second part of the study parameterises the hygroscopicity of the ambient organic aerosol fraction (κorg) at Egbert, Ontario and Whistler, British Columbia. This was done using two methods: 1) by assuming that the oxygenated organic component was hygroscopic and that the unoxygenated organic component was non-hygroscopic, κ of the oxygenated component was found to be 0.22 ± 0.04, and 2) by assuming that κorg varied linearly with the atomic oxygen to atomic carbon ratio, it could be parameterised as κorg = (0.29 ± 0.05) × (O/C). Calculations predict that knowing κorg is important in urban, semi-urban, and remote locations whenever the inorganic mass fraction is low.

Atmospheric particles can affect climate directly, by scattering solar radiation, or indirectly, by acting as the seed upon which cloud droplets form. These clouds can then cool the earth's surface by reflecting incoming sunlight. In order to constrain the large uncertainties in predicting the ultimate effect of aerosol on climate, the sources of atmospheric particles and their subsequent ability to turn into cloud droplets needs to be better understood. This thesis addresses two parts of this issue: the sources of Arctic aerosol and the hygroscopicity of continental organic aerosol. Small particles were observed in Baffin Bay during September 2008 that coincided with high atmospheric and ocean surface dimethyl sulphide (DMS) concentrations suggesting that the aerosol formed from oceanic sources. An aerosol microphysics box model confirmed that local DMS could have produced the observed particles. In addition, the particle chemical composition was measured using aerosol mass spectrometry in the central Arctic Ocean in August 2008 and particles were found to be 43% organic and 46% sulphate. Factor analysis further apportioned the aerosol mass to marine biogenic and continental sources 33% and 36% of the time, respectively, with the source of the remaining mass unidentified. The second part of the study parameterises the hygroscopicity of the ambient organic aerosol fraction (κorg) at Egbert, Ontario and Whistler, British Columbia. This was done using two methods: 1) by assuming that the oxygenated organic component was hygroscopic and that the unoxygenated organic component was non-hygroscopic, κ of the oxygenated component was found to be 0.22 ± 0.04, and 2) by assuming that κorg varied linearly with the atomic oxygen to atomic carbon ratio, it could be parameterised as κorg = (0.29 ± 0.05) × (O/C). Calculations predict that knowing κorg is important in urban, semi-urban, and remote locations whenever the inorganic mass fraction is low.

Atmospheric trace components play a critical role in the earth–atmosphere system through their interaction and perturbation to global atmospheric chemistry. They perturb the climate through scattering and absorbing of solar radiation (direct effects), thereby impacting on the heat energy balance of the atmosphere, and alter cloud microphysical properties affecting cloud formation, cloud lifetime and precipitation formation (indirect effects). These trace components can also have adverse effects on human health, visibility and air quality (AQ) composition, including various feedback processes on the state of the atmosphere. As well as their direct and indirect effects, aerosols are important for cloud formation. They serve as cloud condensation and ice nuclei (CCN and IN) during cloud droplet and ice crystal formations. Although many connections between clouds and aerosol effects have been established in cloud physics and climate modelling, aerosol–cloud interaction (ACI) is still one of the areas of large uncertainties in modern climate and weather projections. Different models have been developed placing much emphasis on ACIs, to have robust and more consistent description processes within the meteorological and chemical variables to account for ACIs and feedback processes. Because pollutant distributions are controlled by a specific meteorology that promotes residence times and vertical mixing in the atmosphere, reliable chemical composition measurements are required to understand the changes occurring in the earth–atmosphere system. Also, because atmospheric pollution is a combination of both natural and man-made (anthropogenic) sources, to direct controlled and/or mitigation procedures efficiently, contributions of different sources need to be considered. Occasionally these are explored from a particular region or global environment, depending on a specific area of interest. A fully coupled online meteorology–chemistry model framework (WRF-Chem) is used to investigate atmospheric ACIs over southern Africa –a region characterized by a strong and intense seasonal biomass burning (BB) cycle. The large transport of aerosol plumes originating from the seasonal burning from agriculture, land-use management and various activities give rise to a unique situation warranting special scrutiny. Simulations are conducted for the 2008 dry season BB episode, implementing a chemical dataset from various emission sources (anthropogenic, BB, biogenic, dust and sea salt) with the meteorological conditions. A base line (CNTRL) simulation was conducted with all emission sources from 26 August to 10 September 2008. To probe the contribution of BB on the regional pollution and influence on ACIs, a sensitivity (TEST) simulation was conducted without BB emissions and compared to the base line. The impact of natural and anthropogenic aerosol particles is studied and quantified for the two simulations, focusing on aerosol concentration and cloud responses under different model resolutions. A statistical analysis of pollutant concentration of major regulated species and cloud variables is conducted and the percentage difference used to assess the contribution due to BB emissions. Results confirm the high variability of spatial and temporal patterns of chemical species, with the greatest discrepancies occurring in the tropical forests whereas the subtropics show more urban/industrial related emissions. Whilst CO and O3 show statistically significant increases over a number of cities/towns, the trend and spatial variability is much less uniform with NO2 and PM in most urban and populous cities. Statistical analysis of major chemical pollutants was mainly influenced by BB emissions. O3, NOx, CO and PM increase by 24%, 76%, 51%, 46% and 41% over the main source regions, whereas in the less affected regions concentrations increased by 5%, 5%, 5%, 3% and 2% when BB emissions are included. This study sheds new light on the response of cloud processes to changing aerosol concentrations and different model resolutions. In the parameterised case (dx = 20 km), clouds become more cellular, correlated with high supersaturations, whereas in the resolved case (dx = 4 km), they become more faint with relatively lower supersaturations. Aerosol effects on cloud properties were further studied and statistical analysis conducted on CCN, cloud droplet number concentration (CDNC), supersaturation and aerosol optical depth (AOD) at two different grid spacings. Most clouds occur to the west of the domain coincident with increase in aerosol concentration and AOD, while single scattering albedo (SSA) decreases. A considerable cloud ‘burn-off’ occurs in tropical west Africa, where aerosols can also be lofted up to 500-hPa level when BB emissions are included in the simulation. Due to BB, absorbing aerosol increased by 76% and 23% over tropical west and subtropical southeast, while tropical east shows no change. The study shows that tropical central Africa is characterized by an increased build-up in biomass burning aerosols (BBAs), forming a regional haze with high AOD; this becomes stronger near active burning areas with a significant proportion occurring to the west. AOD enhancement increases up to 38%, 31% and 11% in the west, east and south respectively. Although CDNC increased in areas with high aerosol concentration, supersaturation decreases (in the small domains) since increase in aerosol number concentration decreases maximum supersaturation Smax. Changes in absorbed radiation increased by +56 Wm-2, +23 Wm-2 and +14 Wm-2 in the west, east and southeast. To further evaluate the model sensitivity and its skill, an analysis was conducted by comparing the model performance with measurement data. Simulated AOD, surface concentrations of CO and O3, ozonesondes and liquid water path (LWP) were compared with measured data from MODIS satellite, SAFARI2000 field study and Cape Point WMO. The model shows a good skill in capturing and reproducing the trends as that measured. However, a severe lack of measurement data over southern Africa makes it more difficult to effectively evaluate WRF-Chem over southern Africa. There is a need for increased availability of measurements to adequately compare with models. This study is one of the first WRF-Chem studies conducted over southern Africa to simulate the weather and pollution interaction. The novelty of the present study is the combined analysis of ACI sensitivity to aerosol loading and cloud response in a regime-based approach. The study concludes with a brief discusssion of future directions for work on AQ and modelling interactions between pollution and weather over southern Africa.

Airborne aerosols are crucial atmospheric constituents that are involved in global climate change and human life qualities. Understanding the nature and magnitude of aerosol-cloud-precipitation interactions is critical in model predictions for atmospheric radiation budget and the water cycle. The interactions depend on a variety of factors including aerosol physicochemical complexity, cloud types, meteorological and thermodynamic regimes and data processing techniques. This PhD work is an effort to quantify the relationships among aerosol, clouds, and precipitation on both global and regional scales by using satellite retrievals and aircraft measurements. The first study examines spatial distributions of conversion rate of cloud water to rainwater in warm maritime clouds over the globe by using NASA A-Train satellite data. This study compares the time scale of the onset of precipitation with different aerosol categories defined by values of aerosol optical depth, fine mode fraction, and Ångstrom Exponent. The results indicate that conversion time scales are actually quite sensitive to lower tropospheric static stability (LTSS) and cloud liquid water path (LWP), in addition to aerosol type. Analysis shows that tropical Pacific Ocean is dominated by the highest average conversion rate while subtropical warm cloud regions (far northeastern Pacific Ocean, far southeastern Pacific Ocean, Western Africa coastal area) exhibit the opposite result. Conversion times are mostly shorter for lower LTSS regimes. When LTSS condition is fixed, higher conversion rates coincide with higher LWP and lower aerosol index categories. After a general global view of physical property quantifications, the rest of the presented PhD studies is focused on regional airborne observations, especially bulk cloud water chemistry and aerosol aqueous-phase reactions during the summertime off the California coast. Local air mass origins are categorized into three distinct types (ocean, ships, and land) with their influences on cloud water composition examined and implications of wet deposition discussed. Chemical analysis of cloud water samples indicates a wide pH range between 2.92 and 7.58, with an average as 4.46. The highest pH values were observed north of San Francisco, coincident with the strongest land mass influence (e.g. Si, B, and Cs). Conversely, the lowest pH values were observed south of San Francisco where there is heavy ship traffic, resulting in the highest concentrations of sulfate, nitrate, V, Fe, Al, P, Cd, Ti, Sb, P, and Mn. The acidic cloud environment with influences from various air mass types can affect the California coastal aquatic ecosystem since it can promote the conversion of micronutrients to more soluble forms. Beyond characterization of how regional air mass sources affect cloud water composition, aircraft cloud water collection provides precious information on tracking cloud processing with specific species such as oxalic acid, which is the most abundant dicarboxylic acid in tropospheric aerosols. Particular attention is given to explore relationship between detected metals with oxalate aqueous-phase production mechanisms. A number of case flights show that oxalate concentrations drop by nearly an order of magnitude relative to samples in the same vicinity with similar environmental and cloud physical conditions. Such a unique feature was consistent with an inverse relationship between oxalate and Fe. In order to examine the hypothesis that oxalate decreasing is potentially related to existing of Fe, chemistry box model simulations were conducted. The prediction results show that the loss of oxalate due to the photolysis of iron oxalato complexes is likely a significant oxalate sink in the study region due to the ubiquity of oxalate precursors, clouds, and metal emissions from ships, the ocean, and continental sources.

The book presents my PhD thesis, which is about aerosol-cloud interactions by means of a dual-field-of-view polarization lidar. Aerosol-cloud interactions (ACI) are a big challenge to quantify the overall effect of human activities on the radiative, heat, and precipitation budgets of the atmosphere. New observational capabilities are demanded. To study the influence of aerosol particles on cloud microphysics an analysis scheme composed of newly-developed arrays is introduced. The retrieval of microphysical properties of liquid-water clouds and of the aerosol particles below the clouds from lidar observations, in a practical and replicable way, is the major challenge tackled in this work. A lidar-based approach to derive liquid-water cloud microphysical properties from dual-field-of-view (DFOV) depolarization measurements is introduced. In addition, a new method to accurately obtain the aerosol properties below cloud layers was developed and implemented into the analysis infrastructure. Comparisons with alternative observational and modeling approaches corroborate the accuracy of both methods. The number concentration of cloud condensation nuclei (CCN) is derived from the aerosol particle extinction coefficient below the cloud, and in combination with the cloud-microphysics retrieval, they provide an aerosol-cloud scene, which allow us to study ACI. Long-term observations at the pristine location of Punta Arenas (PA), Chile, and at the polluted site of Dushanbe (DB), Tajikistan, were analyzed for this purpose. On average, similar values of cloud droplet and below-cloud CCN number concentrations, in the range of 10--150~cm$^{-3}$, were observed at PA. At DB, larger cloud droplet number concentrations were observed, in the order of 200--400 cm-3 but much larger CCN concentrations of about 700--900 cm-3 were found. The so-called ACI index was assessed from the collected data sets. The most robust estimate of the index was obtained when calculating monthly averages over the whole measurement periods, fourteen months at PA and seven months at DB. Values of 0.83 +/- 0.20 and 0.57+/ 0.26 were derived at PA and DB, respectively, and they were used to estimate the radiative forcing due to the Twomey effect. A radiative cooling from -0.70 to -0.17 Wm-2 for PA and between -1.89 and -0.66 Wm-2 for DB is found. These results agree with global estimates of the cloud-mediated aerosol effect but are slightly larger than those values usually found at the specific locations considered. Furthermore, the results obtained at PA show the relevance of updraft movements to trigger ACI. When considering only updraft-dominated periods, the ACI index is up to 50% larger than when no wind information is considered. The new capabilities illuminated during this work may provide a big help for estimations of the cloud-mediated radiative effect and may provide a baseline to confront models dealing with cloud microphysics in future studies.:1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 2 Aerosol, clouds and their interaction - State of the art and research questions. . 7 2.1 Aerosol and clouds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Aerosol effect on liquid-water clouds . . . . . . . . . . . . . . . . . . . . . . . . .8 2.1.2 Aerosol effect on ice-containing clouds . . . . . . . . . . . . . . . . . . . . . . .9 2.1.3 Cloud processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 10 2.1.4 Modeling droplet number concentration Nd . . . . . . . . . . . . . . . . . . 10 2.2 Aerosol radiative effect via ACI in liquid-water clouds . . . . . . . . . . . . . .11 2.2.1 Aerosol-cloud-interaction index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.2 Observational approaches for the ACI index. . . . . . . . . . . . . . . . . . . .14 2.2.3 Strategies to evaluate the ACI index from observations . . . . . . . . . . .16 2.2.4 ACI studies based on lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3 Lidar measurements of aerosol-cloud interaction – Overview of applied methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 3.1 Multiple-scattering lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23 3.2 DFOV-Raman technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.3 Single-FOV polarization lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25 3.3.1 Comparison between DFOV-Raman and SFOV-Depol methods . . . 27 3.4 Dual-FOV depolarization approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.4.1 Calibration of the lidar system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.2 DFOV-Depol measurement cases . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.5 Implementation of the DFOV-Depol approach into the standardized lidar sys- tem Polly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33 4 Research results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 4.1 First publication: Polarization lidar: an extended three-signal calibration approach . . . . . . .39 4.2 Second publication: The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Theoretical framework . . . . . . . . .59 4.3 Third publication: The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Case studies . . . . . . . . . . . . . . . .79 5 Discussion and further applications – Long-term observations of aerosol- cloud interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101 5.1 Observations on cloud scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102 5.2 Long-term results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.2.1 Comparison of DFOV-Depol products with available estimations and observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108 5.3 Assessment of the ACI index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.4 Relevance of the ACI index for the radiative effect . . . . . . . . . . . . 112 6 Summary and outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117 Appendix A: Aerosol properties with lidar . . . . . . . . . . . . . . . . . . . .125 A.1 Lidar principles of elastic and Raman lidar . . . . . . . . . . . . . . . .125 A.2 Raman lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 A.2.1 Retrieval of extinction coefficient . . . . . . . . . . . . . . . . . . . . . 128 A.2.2 Retrieval of backscattering coefficient. . . . . . . . . . . . . . . . . . 128 A.2.3 Bottom-up approximation for Raman Signals . . . . .. . . . . . . 129 A.2.4 Evaluation of Raman methods. . . . . . . . . . . . . . . . . . . . . . . 130 A.3 Elastic Lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132 A.3.1 Klett-Fernald Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 A.3.2 Quasi-backscattering for high resolved retrievals. . . . . . . . . 133 A.3.3 Bottom-up approximation for elastic signals . . . . . . . . . . . . 135 A.3.4 Evaluation of methods based on elastic lidar. . . . . . . . . . . . 137 A.3.5 Microphysical properties from optical properties. . . . . . . . . . 139 Appendix B Characterization of DFOV-Depol lidar . . . . . . . . . . . . 143 B.1 Transmission ratio based on long-term analysis . . . . . . . . . . . 144 Appendix C: Author’s contributions to the three publications . . . . 149 Appendix D Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 D.1 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 D.2 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 D.3 List of Symbols (excluding cumulative part) . . . . . . . . . . 156 D.4 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158