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.

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.

1720 MHz OH masers have been detected towards a number of supernova remnants (SNRs) at the shock interface where the SNR slams into the interstellar medium. Models indicate that these masers are shock excited and can only be produced under tight constraints of the physical conditions. In particular, the masers can only form behind a C-type shock. Jets from newlyformed stars plow into the surrounding gas, creating nebulous regions known as Herbig Haro (HH) objects. Signatures of C-type shocks have been found in many HH objects. If conditions behind the shock fronts of HH objects are able to support 1720 MHz OH masers they would be a usefull diagnostic tool for star formation. A survey toward HH objects detected a number of 1720 MHz OH lines in emission, but future observations with arrays are required to confirm the presence of masers. / Physics / M.Sc. (Astronomy)

Im Rahmen der Arbeit wurden Lidar- und Wolkenradarmessungen von troposphärischen Schichtwolken durchgeführt und ausgewertet, um den Zusammenhang zwischen Vertikalwinden und Eisbildung in diesen Wolken zu untersuchen. Der Eis- und Flüssigwassergehalt von Schichtwolken wurde mit einer Kombination aus Raman-Lidar und Wolkenradar untersucht. Die vertikalen Windbewegungen an der Wolkenunterkante wurden mit einem Doppler-Lidar aufgezeichnet. Durch die Auswertung vorangegangener Messkampagnen konnte die Vertikalwindstatistik in mittelhohen Schichtwolken zwischen den Standorten Leipzig und Praia (Kap Verde) verglichen werden. Messverfahren für die Vertikalwindmessung mit Doppler-Lidar wurden im Rahmen dieser Arbeit weiterentwickelt. In Zusammenarbeit mit dem Deutschen Wetterdienst wurde außerdem die Kombination von Doppler-Lidar, Wolkenradar und Wind-Profiler getestet. Die Eisbildungseffizienz in der Troposphäre wurde im Temperaturbereich zwischen 0 und -40°C für den Standort Leipzig untersucht und sowohl mit vorangegangenen Lidarmessungen, als auch mit aktuellen Satellitenmessungen verglichen. Zum ersten Mal wurde außerdem die statistische Verteilung von Vertikalwinden an der Basis von Mischphasenwolken dargestellt. Es wurde festgestellt, dass sich bei einer Temperatur von (-9 +/- 3)°C bereits in 50% der Schichtwolken über Leipzig Eis bildet. Zwischen -15 und 0°C wurden Verhältnisse zwischen Eis- und Flüssigwasserpfad zwischen 0,1 und 0,0001 abgeschätzt. Im Rahmen der Messgenauigkeit wurden zwischen den Standorten Leipzig und Praia keine Unterschiede in der Vertikalwindstatistik festgestellt.

1720 MHz OH masers have been detected towards a number of supernova remnants (SNRs) at the shock interface where the SNR slams into the interstellar medium. Models indicate that these masers are shock excited and can only be produced under tight constraints of the physical conditions. In particular, the masers can only form behind a C-type shock. Jets from newlyformed stars plow into the surrounding gas, creating nebulous regions known as Herbig Haro (HH) objects. Signatures of C-type shocks have been found in many HH objects. If conditions behind the shock fronts of HH objects are able to support 1720 MHz OH masers they would be a usefull diagnostic tool for star formation. A survey toward HH objects detected a number of 1720 MHz OH lines in emission, but future observations with arrays are required to confirm the presence of masers. / Physics / M.Sc. (Astronomy)

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-05-14T20:44:44Z No. of bitstreams: 1 WALÉRIA SOUZA FIGUEIRA – DISSERTAÇÃO (PPGMET) 2015.pdf: 2735921 bytes, checksum: c2ab85caa20115480b90d1325acfad13 (MD5) / Made available in DSpace on 2018-05-14T20:44:44Z (GMT). No. of bitstreams: 1 WALÉRIA SOUZA FIGUEIRA – DISSERTAÇÃO (PPGMET) 2015.pdf: 2735921 bytes, checksum: c2ab85caa20115480b90d1325acfad13 (MD5) Previous issue date: 2015-03-05 / CNPq / Este trabalho teve como objetivo estudar o efeito da remoção de umidade da camada limite planetária por cúmulos rasos. Para tal, esse efeito foi inserido no código do modelo BRAMS. Foram realizados dois experimentos: no primeiro experimento de controle (EXP_ORI), o modelo foi inicializado em sua forma original e no segundo (EXP_AJUST), o modelo foi integrado para as mesmas condições que o EXP_ORI, porém com o devido ajuste realizado no código do BRAMS. O modelo foi integrado para um período de 774 horas a partir da 00 UTC do dia 1° de janeiro até a 00 UTC do dia 1° de fevereiro de 2011. Para facilitar a análise quanto ao impacto desse ajuste no ciclo diário médio das variáveis termodinâmicas de superfície e da precipitação convectiva, foram feitas médias em duas áreas distintas de 1°x1°, uma área sobre superfície florestada (localizada no sul do Amazonas) e outra área sobre superfície desflorestada (localizada no norte da Bolívia). De forma geral, os resultados mostraram que houve diferenças notáveis no perfil termodinâmico da troposfera inferior devido à implementação do novo ajuste. As taxas de aquecimento e umedecimento, em ambas as áreas, tiveram picos as 09 e 09:30 horas local, embora o seu efeito líquido tenha se mostrado nas horas seguintes, o principal impacto ocorreu no início da tarde. O ciclo diário dos fluxos à superfície também foram sensíveis ao ajuste realizado no modelo. Já o comportamento e a quantidade da precipitação convectiva acumulada ao longo do dia foram melhorados no EXP_AJUST, principalmente na área desflorestada. / The objective of this work was to the effects of moisture removal from the planetary boundary layer by shallow cumulus. To reach this goal, this effect was implemented into the BRAMS model code. Two experiments were performed: in the control experiment (EXP_ORI), the model was initialized in its original form and in the second one (EXP_AJUST) the model was run to the same conditions as the EXP_ORI but with due adjustment made in BRAMS code. The model was run for a period of 774 hours, from 00 UTC of 1 January to 00 UTC of 1 February 2011. To facilitate the analysis of the impact of this adjustment on the mean daily cycle of thermodynamic variables of surface and convective precipitation, averages were performed in two different areas of 1° x 1°, an area of forested area (located in the south of the Amazon) and other deforested area on surface (located in northern Bolivia). Overall, the results showed that there were important differences in the thermodynamic profile of the lower troposphere due to the implementation of new setting in the BRAMS code. Values of moistening and heating rates in both areas peaked around 09 and 09:30 local time, although their net effect were felt later, the impact occurred mainly early afternoon. The daily cycle of surface fluxes were also sensitive to the adjustment performed in the model. Also the behavior and the amount of convective precipitation accumulated during the day in EXP_AJUST were improved, especially in deforested area.

Infrastructure-as-a-Service(IaaS), one of the service models of cloud computing, provides resources in the form of Virtual Machines(VMs). Many applications hosted on the IaaS cloud have time varying workloads. These kind of applications benefit from the on-demand provision ing characteristic of cloud platforms. Applications with time varying workloads demand time varying resources in IaaS, which requires elastic resource provisioning in IaaS, such that their performance is intact. In current IaaS cloud systems, VMs are static in nature as their configurations do not change once they are instantiated. Therefore, fluctuation in resource demand is handled in two ways: allocating more VMs to the application(horizontal scaling) or migrating the application to another VM with a different configuration (vertical scaling). This forces the customers to characterize their workloads at a coarse grained level which potentially leads to under-utilized VM resources or under performing application. Furthermore, the current IaaS architecture does not provide performance guarantees to applications, because of two major factors: 1)Performance metrics of the application are not used for resource allocation mechanisms by the IaaS, 2) Current resource allocation mechanisms do not consider virtualization overheads, can significantly impact the application’s performance, especially for I/O workloads. In this work, we develop an Elastic Resource Framework for IaaS, which provides flexible resource provisioning mechanism and at the same time preserves performance of applications specified by the Service Level Agreement(SLA). For identification of workloads which needs elastic resource allocation, variability has been defined as a metric and is associated with the definition of elasticity of a resource allocation system. We introduce new components Forecasting Engine based on a Cost Model and Resource manager in Open Nebula IaaS cloud, which compute a n optimal resource requirement for the next scheduling cycle based on prediction. Scheduler takes this as an input and enables fine grained resource allocation by dynamically adjusting the size of the VM. Since the prediction may not always be entirely correct, there might be under-allocation or over-allocation of resources based on forecast errors. The design of the cost model accounts for both over-allocation of resources and SLA violations caused by under-allocation of resources. Also, proper resource allocation requires consideration of the virtualization overhead, which is not captured by current monitoring frameworks. We modify existing monitoring frameworks to monitor virtualization over head and provide fine-grained monitoring information in the Virtual Machine Monitor (VMM) as well as VMs. In our approach, the performance of the application is preserved by 1)binding the application level performance SLA store source allocation, and 2) accounting for virtualization over-head while allocating resources. The proposed framework is implemented using the forecasting strategies like Seasonal Auto Regressive and Moving Average model (Seasonal ARIMA), and Gaussian Process model. However, this framework is generic enough to use any other forecasting strategy as well. It is applied to the real workloads, namely web server and mail server workloads, obtained through Supercomputer Education and Research Centre, Indian Institute of Science. The results show that significant reduction in the resource requirements can be obtained while preserving the performance of application by restricting the SLA violations. We further show that more intelligent scaling decisions can be taken using the monitoring information derived by the modification in monitoring framework.

MENVSC / Department of Geography and Geo-Information Sciences / The process of cloud formation and distribution in the atmospheric circulation system is very important yet not easy to comprehend and forecast. Clouds affect the climate system by controlling the amount of solar radiation, precipitation and other climatic variables. Parameterised induced General Circulation Model (GCMs) are unable to represent clouds and aerosol particles explicitly and their influence on the climate and are thought to be responsible for most of the uncertainty in climate predictions. Therefore, the aim of the study is to investigate the climate of South Africa as simulated by Super Parameterised Community Atmosphere Model (SPCAM) for the period of 1987-2016. Community Atmosphere Model (CAM) and SPCAM datasets used in the study were obtained from Colorado State University (CSU), whilst dynamic and thermodynamic fields were obtained from the NCEP reanalysis ll. The simulations were compared against rainfall and temperature observations obtained from the South African Weather Service (SAWS) database. The accuracy of the model output from CAM and SPCAM was tested in simulating rainfall and temperature at seasonal timescales using the Root Mean Square Error (RMSE). It was found that CAM overestimates rainfall over the interior of the subcontinent during December - February (DJF) season whilst SPCAM showed a high performance in depicting summer rainfall particularly in the central and eastern parts of South Africa. During June – August (JJA), both configurations (CAM and SPCAM) had a dry bias with simulating winter rainfall over the south Western Cape region in cases of little rainfall in the observations. CAM was also found to underestimate temperatures during DJF with SPCAM results closer to the reanalysis. The study further analyzed inter-annual variability of rainfall and temperature for different homogenous regions across the whole of South Africa using both configurations. It was found that SPCAM had a higher skill than CAM in simulating inter-annual variability of rainfall and temperature over the summer rainfall regions of South Africa for the period of 1987 to 2016. SPCAM also showed reasonable skill simulating (mean sea level pressure, geopotential height, omega etc) in contrast to the standard CAM for all seasons at the low and middle levels (850 hPa and 500 hPa). The study also focused on major El Niño Southern Oscillation (ENSO) events and found that SPCAM tended to compare better in general with the observations. Although both versions of the model still feature substantial biases in simulating South African climate variables (rainfall, temperature, etc), the magnitude of the biases are generally smaller in the super parameterized CAM than the default CAM, suggesting that the implementation of the super parameterization in CAM improves the model performance and therefore seasonal climate prediction. / NRF

A climatology of thermodynamic phase of precipitating cloud is presented derived from global—land and ocean—, retrievals from Cloudsat, CALIPSO, and Moderate Resolution Imaging Spectroradiometer. Like precipitation rate, precipitation frequency is dominated by warm rain, defined as rain produced via the liquid phase only, over the tropical oceans outside the Intertropical Convergence Zone and by cold rain, produced via the ice phase, over the midlatitude oceans and continents. Warm rain is very infrequent over the continents, with significant warm rain found only in onshore flow in the tropics, and over India, China, and Indochina. Comparison of the properties of precipitating and nonprecipitating warm clouds shows that the scarcity of warm rain over land can be explained by smaller effective radii in continental clouds that delay the onset of precipitation. The results highlight the importance of ice-phase processes for the global hydrological cycle and may lead to an improved parameterization of precipitation in general circulation models.

Understanding how diffuse molecular clouds at large scales (~10 pc) assemble mass into dense, star-forming cores at small scales (~ 0.1 pc) is crucial to building a holistic theory of star formation. While recent observations suggest that filaments play an important role in the mass assembly of dense cores, detailed gas kinematics studies are still lacking. My dissertation presents three innovative techniques that enable us to study star-forming filaments' complex gas kinematics in unprecedented detail: multi-component spectral fit, multi-dimensional filament identification, and membership assignment of velocity-coherent structures. Through these techniques, I analyzed star-forming filaments in the Perseus Molecular Cloud and unveiled unexpectedly complex velocity structures at scales where filaments are well resolved, to as low as the 0.01 pc scale. Moreover, the correlations I discovered between the various filament properties further suggest a scenario in which thermally supercritical filaments grow continuously via accretion from their surroundings while simultaneously forming cores through fragmentation along their lengths. / Graduate / 2022-01-08