Includes bibliographical references (pages 139-143). / The central theme of this study concerns the use of classification schemes on weather modification experiments designed to investigate the possibility of increasing rainfall from individual cumuli or cumulus cloud systems. The principal objectives of these experiments are the evaluation of treatment effects and the identification of situations where seeding with artificial ice-nuclei is likely to have positive results. The classification of experimental units into categories that are associated with significantly different physical processes aids the evaluation process and the formulation of seeding strategies in the desired manner. As part of this study a classification scheme, which stratifies convective events on the basis of the synoptic situations which give rise to and maintain the convection, is formulated. In chapter seven and eight this scheme and another scheme presently being employed on a cumulus cloud weather modification experiment are examined statistically. Investigations show that the formulated scheme attains the objectives of classification to a greater degree. Certain attributes of the second scheme, permit the development of a classification procedure whereby the most effective stratification of experimental units can be accomplished.

A code for the quasi-stationary solution of the coupled heat and mass transport equations for aerosols in a finite volume was developed. Both mass and heat are conserved effectively in the volume, which results in a competitive aerosol condensation growth computational model. A further model that couples this competitive aerosol condensation growth computational model with computational fluid dynamics (CFD) software (ANSYS FLUENT) enables the simulation of the realistic atmospheric environment. One or more air parcels, where the aerosols reside, are placed in a very big volume in order to mimic the large atmospheric environment. Mass (water vapor) and heat transportat between the air parcels and the environment facilitates the growth and prevents the parcels from unrealistically overheating. The suppression of cloud condensation nuclei (CCN) growth by high number densities was quantified by our model study. Model study with organic particles (Lmalic acid and maleic acid) indicates that when these organic species and ammonium sulfate are internally mixed, the particles can grow much more than if they are separately associated with distinct particles. Moreover, by using more multiple air parcels, which are randomly assigned with different initial relative humidity values according to a power law distribution, we studied the effects of atmospheric stochastic RH distribution on the growth of CCN.

Weather forecasting relies on the availability of observational data as input parameters. However,such data are not readily available, because of difficulties to collect weather data due toinaccessibility to many places in the world, such as oceans or mountain regions. For this reason,satellite surveillance is a suitable tool to observe the atmosphere in regions where it is notpossible by other means. This master thesis is a study of convective cloud cluster formation over Thailand, conductedthrough satellite image analysis. Characteristics of cloud cluster formations are investigatedthrough an implementation of the Maximum Spatial Correlation Technique (MASCOTTE),described by Carvalho and Jones (2001). This method allows tracking of convective cloud systemsthrough region based analysis of satellite images. The aim of this study is to investigate whether satellite image analysis, through the implementationof the MASCOTTE methodology, can provide characteristics of convective cloud systems,in order to discern convective systems by intensity, accurately enough to be able to discernsevere thunderstorms from ordinary thunderstorms. The annual distribution of the occurrenceof life cycles detected through the analysis is studied, as well as their monthly distribution ofmean and maximum life times. Moreover, the yearly distribution of life cycle mean and minimumbrightness temperatures are analysed, as well as the number of detected split and mergeevents. This is followed by a comparison of life cycle structural properties to investigate thepossibility to use individual parameters, alone or in combination with each other, as indicatorsof the degree of convective activity within life cycles. Yearly distributions were studied in order to verify if this method could reveal seasonal variations,such as the onset period of the wet season, in terms of the occurrence of life cycles andtheir life time. The findings of this study verified that the most convectively intense life cycles exist under theinfluence of the Inter Tropical Convergence Zone (ITCZ), during the onset and beginning ofthe monsoon season. Analysis of life cycle structural properties, showed that properties likemean and minimum brightness temperature as well as fractional convective area, could be usedas indicators to discern between life cycles with different level of convective activity. However,it is concluded that studies, including ground-based remote sensing technologies such asRADAR/LIDAR, as well as data from rawinsondes, needs to be conducted in order to clarifyif it is possible to use this methodology to successfully discern severe thunderstorms fromordinary thunderstorms. / Tillgängligheten av meteorologiska mätdata är väsentlig för att kunna prognostisera väder. Idag är tillgängligheten på dessa data relativt gles, bland annat på grund av svårigheter att mäta på många platser runt om i världen, t.ex över världshaven eller vid otillgängliga bergsområden. Därför är satellitövervakning ett bra alternativ till andra typer av väderobservationer, eftersom denna teknik kan tillhandahålla mätdata över stora områden som annars inte är möljiga att samla data från. Denna magisteruppsats är en studie om egenskaper hos konvektiv molnbildning över Thailand. Studien är genomförd med hjälp av satellitbildsanalys. Egenskaper hos olika konvektiva molnceller har studerats genom att använda en metod baserad på ”the Maximum Spatial Correlation Technique” (MASCOTTE), beskriven av Carvalho and Jones (2001). Tanken bakom denna metod är att hitta och följa utvecklingen av olika konvektiva molnceller baserat på deras storlek och temperatur. Målet med studien är att undersöka hurvida denna metoden kan ge kunskap som leder till att man kan skilja på konvektiva celler, genom intensitetsskillnader, med tillräcklig noggrannhet för att kunna urskilja vanliga konvektiva celler från intensiva celler. För att få en uppfattning om förekomsten av intensiva konvektiva system, har antalet detekterade livscykler per månad studerats. För sedan att få en bild av hurvida deras livscykler skiljer sig åt över året, har även egenskaper som medellivslängd och maximal livslängd studerats. Dessutom studerades den årliga fördelningen av livscyklernas medel och minimum temperaturer, samt förekomsten av delningar och sammanslagningar av konvektiva celler. För att finna kunskap om skillnader i intensitet mellan individuella livscykler, har egenskaper som medel och minimum temperatur analyserats. Dessutom har andelen moln med extremt låg temperatur studerats i syfte att kunna använda dessa parametrar som intensitetsindikatorer vid satellitbildsanalys. Resultaten i denna studie visar att de mest intensiva konvektiva molnsystemen (kraftigaste åskvädren), förekommer under påverkan av ITCZ (Inter Tropical Convergence Zone), under antågandet och början av regnperioden. Studier av de konvektiva systemens egenskaper visade att parametrar, som andelen extremt kallt område i molnceller (fractional convective area), och livscyklernas medel och minimum temperaturer, skulle kunna användas som intensitetsindikatorer för att skilja på olika livscykler med avseende på deras styrka i intensitet. Slutsatsen av studien är att det behövs fler studier där andra typer av meteorologiska mätdata, såsom RADAR/LIDAR och sonderingsdata är involverade, för att skaffa ytterligare kunskap om hur man genom satellitbildsanalys kan urskilja kraftiga åskväder.

Anthropogenic atmospheric aerosols (suspended particulate matter) can modify the radiative balance (and climate) of the Earth by altering the properties and global distribution of clouds. Current climate models however cannot adequately account for many important aspects of these aerosol-cloud interactions, ultimately leading to a large uncertainty in the estimation of the magnitude of the effect of aerosols on climate. This thesis focuses on the development of physically-based descriptions of aerosol-cloud processes in climate models that help to address some of such predictive uncertainty. It includes the formulation of a new analytical parameterization for the formation of ice clouds, and the inclusion of the effects of mixing and kinetic limitations in existing liquid cloud parameterizations. The parameterizations are analytical solutions to the cloud ice and water particle nucleation problem, developed within a framework that considers the mass and energy balances associated with the freezing and droplet activation of aerosol particles. The new frameworks explicitly account for the impact of cloud formation dynamics, the aerosol size and composition, and the dominant freezing mechanism (homogeneous vs. heterogeneous) on the ice crystal and droplet concentration and size distribution. Application of the new parameterizations is demonstrated in the NASA Global Modeling Initiative atmospheric and chemical and transport model to study the effect of aerosol emissions on the global distribution of ice crystal concentration, and, the effect of entrainment during cloud droplet activation on the global cloud radiative properties. The ice cloud formation framework is also used within a parcel ensemble model to understand the microphysical structure of cirrus clouds at very low temperature. The frameworks developed in this work provide an efficient, yet rigorous, representation of cloud formation processes from precursor aerosol. They are suitable for the study of the effect of anthropogenic aerosol emissions on cloud formation, and can contribute to the improvement of the predictive ability of atmospheric models and to the understanding of the impact of human activities on climate.

The atmospheres of exoplanets are being characterised in increasing detail by observational facilities and will be examined with even greater clarity with upcoming space based missions such as the James Webb Space Telescope (JWST) and the Wide Field InfraRed Survey Telescope (WFIRST). A major component of exoplanet atmospheres is the presence of cloud particles which produce characteristic observational signatures in transit spectra and influence the geometric albedo of exoplanets. Despite a decade of observational evidence, the formation, dynamics and radiative-transport of exoplanet atmospheric cloud particles remains an open question in the exoplanet community. In this thesis, we investigate the kinetic chemistry of cloud formation in hot Jupiter exoplanets, their effect on the atmospheric dynamics and observable properties. We use a static 1D cloud formation code to investigate the cloud formation properties of the hot Jupiter HD 189733b. We couple a time-dependent kinetic cloud formation to a 3D radiative-hydrodynamic simulation of the atmosphere of HD 189733b and investigate the dynamical properties of cloud particles in the atmosphere. We develop a 3D multiple-scattering Monte Carlo radiative-transfer code to post-process the results of the cloudy HD 189733b RHD simulation and compare the results to observational results. We find that the cloud structures of the hot Jupiter HD 189733b are likely to be highly inhomogeneous, with differences in cloud particle sizes, number density and composition with longitude, latitude and depth. Cloud structures are most divergent between the dayside and nightside faces of the planet due to the instability of silicate materials on the hotter dayside. We find that the HD 189733b simulation in post-processing is consistent with geometric albedo observations of the planet. Due to the scattering properties of the cloud particles we predict that HD 189733b will be brighter in the upcoming space missions CHaracterising ExOPlanet Satellite (CHEOPS) bandpass compared to the Transiting Exoplanet Space Survey (TESS) bandpass.

Weather radars are increasingly used for the study of clouds, understanding the precipitation systems and also for forecasting very short range weather (one hour to a few hours). Now, Doppler Weather Radar (DWR) data are available in India and it is possible to study cloud properties at fine temporal and spatial scales. Radar is a complex system and calibration of a radar is not an easy job. But derived cloud properties strongly depend on the absolute magnitude of the reflectivity. Therefore, there is a need to check how data from two or more radars compare if they measure a common volume. Chennai and SHAR radars are within 66 km from each other, and the data collected during their calibration and intercomparison experiment in 2006 enables the comparison of their reflectivity(Z) values. Individual reflectivity are compared after plotting SHAR versus Chennai in a scatter plot. Fitting a least square linear best fit line shows that the intercept has a value around 6 dBZ and the slope of the line is 1.06. Thus, there is a trend as well, and the difference between the two radars increase with Z, and for Z around 40 dBZ (for SHAR DWR), the difference between the two is around 8.5 dBZ. Visual intercomparison also validated the results. Data from the two radars are compared with Precipitation Radar (PR) data on board TRMM satellite. TRMM radar slightly overestimates compared to Chennai radar above the range of 30 dBZ. After standardized, SHAR data is used for understanding the evolution and propagation of cloud systems. The diurnal variation in convection is strong in the study region, with increase around local evening and morning and weakening around midnight except in December. Average liquid water content in the clouds is about 0.5 gm/m3. There is some seasonal dependence but no clear dependence on cloud size. Smaller systems of May have more liquid water content compared to larger ones. For nowcasting vertically projected maximum reflectivity is taken. A threshold of 30 dBZ is set to identify the cloud systems. Both center of gravity tracking (CG) and cross-correlation (CC) methods are used to track them. Frequent merging and splitting is common in the clouds which makes storm tracking difficult. Tracking by CC is giving better result than that by the CG method in the case of large systems (i.e., clusters). For smaller systems (individual cloud systems), CC method gives better result than CG method but not as good as cluster.