This master thesis deals with creation of library for volumetric clouds. The paper describes specific techniques for creation and rendering volumetric clouds as clouds and atmospheric scattering. For rendering this type of effects we have to cover theory for participating media.

Exposure to mercury poses significant risks to the health of humans and wildlife. Globally, coal-fired power plant (CFPP) is a major source of mercury emissions, with China being the largest contributor to global atmospheric mercury. As a signatory country of the Minamata Convention on Mercury, China is developing its National Implementation Plan on Mercury Control, which gives priority to control of mercury emissions from CFPPs. While social benefits play an important role in designing environmental policies in China, the potential public health and economic benefits of mercury control in the nation are not yet understood, mainly due to the scientific challenges to trace mercury’s emissions-to-impacts path. Moreover, little is known about the potential benefits for the neighboring countries in East Asia resulted from China’s mercury control. This study evaluates the health and economic benefits for China and neighboring countries in East Asia from mercury reductions from China’s CFPPs. Four representative mercury control policy scenarios are analyzed, and the evaluation is explicitly conducted following the policies-to-impacts path under each policy scenario. We link a global atmospheric model to health impact assessment and economic valuation models to estimate economic gains for China and its three neighboring countries (Japan, South Korea and North Korea) from avoided mercury-related adverse health outcomes under the four emission control scenarios, and also take into account the key uncertainties in the policies-to-impacts path. Under the most stringent control scenario, the cumulative benefit of the mercury reduction by 2030 is projected to be $430 billion for the four countries together (the 95% confidence interval is $102-903 billion, in 2010 USD). Our findings suggest that although China is the biggest beneficiary of the mercury reduction in CFPPs, neighboring countries including Japan, South Korea and North Korea can also benefit (~7% of the total benefits) from China’s mercury reduction.

In first part of the study we discuss impact of dynamical core in simulation of tropical rainfall. Over years many new dynamical cores have been developed for atmospheric models to increase efficiency and reduce numerical errors. CAM3.1 gives an opportunity to study the impact of the dynamical core on simulations with its three dynamical cores namely Eulerian spectral(EUL) , Semilagrangian dynamics(SLD) and Finite volume(FV) coupled to a single parametrization package. A past study has compared dynamical cores of CAM3 in terms on tracer transport and has showed advantages using FV in terms of tracer transport. In this study we compare the dynamical cores in climate simulations and at their optimal configuration, which is the intended use of the model. The model is forced with AMIP type SST and rainfall over seasonal, interannual scales is compared. The significant differences in simulation of seasonal mean exist over tropics and over monsoon regions with observations and among dynamical cores. The differences among EUL and SLD, which use spectral transform methods are lesser compared that of with FV clearly indicating role of numerics in differences. There exist major errors in simulation of seasonal cycle in all dynamical cores and errors in simulation of seasonal means over many regions are associated with errors in simulation of seasonal cycle such as over south china sea. Seasonal cycle in FV is weaker compared to SLD and EUL. The dynamical cores exhibit different interannual variability of rainfall over Indian monsoon region, the period of maximum power corresponding to a dynamical core differs substantially with another. From this study there seems no superiority associated with FV dynamical core over all climate scales as seen in tracer transport. The next part of the study deals with impact of diurnal ocean atmosphere coupling in an AGCM,CAM3.1. Due to relatively low magnitude of diurnal cycle of SST and lack of SST observations over diurnal scales current atmospheric models are forced with SSTs of periods grater than a day. CAM 3.1 standalone model is forced with monthly SSTs but the interpolation is linear to every time step between any two months and this linear interpolation implies a linear diurnal and intraseasonal variation of SST which is not true in nature. To test the sensitivity of CAM3.1 to coupling of SST on diurnal scales, we prescribed over tropics(20S20N) a diurnal cycle of SST over daily mean interpolated SST of different magnitudes and phase comparable to observations. This idea of using a diurnal cycle of SST retaining seasonal mean SST in an atmospheric model is novel and provides an interesting frame work to test sensitivity of model to interpolations used in coupling of boundary conditions. Our analysis shows a high impact of using diurnal cycle of SST on simulation of mean rainfall over tropics. The impact in a case where diurnal cycle of SST is fixed and retained to daily mean SST implies that changes associated with a coupled model are to some extent due to change in representation of diurnal cycle of SST. A decrease of excess rainfall over western coast of Bay of Bengal and an increase of rainfall over northern bay of Bengal in such case is similar to the improvement due to coupling atmospheric model to a slab ocean model. This also implies that problems with current AMIP models in simulation of seasonal mean Indian monsoon rainfall could be due to erroneous representation of diurnal cycle of SST in models over this region where the diurnal cycle of SST is high in observations. The high spatial variability of the impact in various cases over tropics implies that a similar spatial variation of diurnal cycle could be important for accurate simulation of rainfall over tropics. Preliminary analysis shows that impact on rainfall was due to changes in moisture convergence. We also hypothesized that diurnal cycle of SST could trigger convection over regions such as northern Bay of Bengal and rainfall convergence feedback sustains it. The impact was also found on simulation of internal interannual variability of rainfall

The emergence of the exascale era necessitates development of new techniques to efficiently perform high-performance scientific simulations, online data analysis and on-the-fly visualization. Critical applications like cyclone tracking and earthquake modeling require high-fidelity and high- performance simulations involving large-scale computations and generate huge amounts of data. Faster simulations and simultaneous online data analysis and visualization enable scientists provide real-time guidance to policy makers. In this thesis, we present a set of techniques for efficient high-fidelity simulations, online data analysis and visualization in environments with varying resource configurations. First, we present a strategy for improving throughput of weather simulations with multiple regions of interest. We propose parallel execution of these nested simulations based on partitioning the 2D process grid into disjoint rectangular regions associated with each subdomain. The process grid partitioning is obtained from a Huffman tree which is constructed from the relative execution times of the subdomains. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. We observe up to 33% gain over the default strategy in weather models. Second, we propose a processor reallocation heuristic that minimizes data redistribution cost while reallocating processors in the case of dynamic regions of interest. This algorithm is based on hierarchical diffusion approach that uses a novel tree reorganization strategy. We have also developed a parallel data analysis algorithm to detect regions of interest within a domain. This helps improve performance of detailed simulations of multiple weather phenomena like depressions and clouds, thereby in- creasing the lead time to severe weather phenomena like tornadoes and storm surges. Our method is able to reduce the redistribution time by 25% over a simple partition from scratch method. We also show that it is important to consider resource constraints like I/O bandwidth, disk space and network bandwidth for continuous simulation and smooth visualization. High simulation rates on modern-day processors combined with high I/O bandwidth can lead to rapid accumulation of data at the simulation site and eventual stalling of simulations. We show that formulating the problem as an optimization problem can deter- mine optimal execution parameters for enabling smooth simulation and visualization. This approach proves beneficial for resource-constrained environments, whereas a naive greedy strategy leads to stalling and disk overflow. Our optimization method provides about 30% higher simulation rate and consumes about 25-50% lesser storage space than a naive greedy approach. We have then developed an integrated adaptive steering framework, InSt, that analyzes the combined e ect of user-driven steering with automatic tuning of application parameters based on resource constraints and the criticality needs of the application to determine the final parameters for the simulations. It is important to allow the climate scientists to steer the ongoing simulation, specially in the case of critical applications. InSt takes into account both the steering inputs of the scientists and the criticality needs of the application. Finally, we have developed algorithms to minimize the lag between the time when the simulation produces an output frame and the time when the frame is visualized. It is important to reduce the lag so that the scientists can get on-the- y view of the simulation, and concurrently visualize important events in the simulation. We present most-recent, auto-clustering and adaptive algorithms for reducing lag. The lag-reduction algorithms adapt to the available resource parameters and the number of pending frames to be sent to the visualization site by transferring a representative subset of frames. Our adaptive algorithm reduces lag by 72% and provides 37% larger representativeness than the most-recent for slow networks.

Les bâtiments représentent 40 pourcents de la consommation finale d'énergie. Ils sont ainsi le fer de lance des politiques de réduction des dépenses énergétiques. Récemment, des systèmes de modèles climatiques qui incluent un modèle atmosphérique régional et des paramétrisations urbaines sophistiquées ont été développés. Ils considèrent la complexité de l’îlot de chaleur urbain et ses interactions avec les besoins énergétiques des bâtiments. Dans quelle mesure ces systèmes constituent-ils des outils d’aide à la décision pour les autorités locales ? Cette étude menée sur le territoire de l'Eurodistrict (Strasbourg - Kehl) en 2010, puis en 2030, à l’aide du système de modèles de climat WRF/ARW-BEP+BEM a démontré que si le système de modèles estimait de manière fiable les besoins en chauffage des bâtiments, ces derniers étaient davantage sensibles aux caractéristiques intrinsèques des bâtiments qu'aux formes urbaines et à l'îlot de chaleur urbain induit par ces formes. / Buildings represent 40 percent of the end-use energy. Thus, they constitute a key point of the energy saving policies. Recently, climate modeling systems that include a mesoscale atmospheric model, sophisticated urban parameterizations have been developed to account for the complexity of the urban climate and its interactions with the building energy loads. This study aims to assess the capability of such climate modeling systems to provide climate and energy guidelines to urban planners. For this, we used the research collaborative WRF/ARW-BEP+BEM climate modeling system and performed sensitivity tests considering the territory of the Eurodistrict in 2010, and then in 2030. The results reveal that the climate modeling system achieves estimating the building energy needs over the study area, but also indicate that the building energy needs are more sensitive to the building intrinsic properties and occupant behavior than to the urban forms and their induced urban heat island.

In this thesis we examine intra-seasonal oscillations (ISO) in the aqua-planet setup of the Community Atmospheric Model (CAM) version 5.1, mainly based on July and January climatological sea surface temperature (SST). We investigate mainly two questions -what should be the SST distribution for the existence of (a) northward moving ISO in summer, and (b) eastward moving MJO-like modes in winter. In the first part of the thesis we discuss the northward propagation. A series of experiments were performed with zonally symmetric and asymmetric SST distributions. The basic lower boundary condition is specified from zonally averaged observed July and January SST. The zonally symmetric July SST experiment produced an inter tropical convergence zone (ITCZ) on both sides of the equator. Poleward movement is not clear, and it is confined to the region between the double ITCZ. In July, the Bay of Bengal (BOB) and West Pacific SST is high compared to the rest of the northern tropics. When we impose a zonally asymmetric SST structure with warm SST spanning about 80 of longitude, the model shows a monsoon-like circulation, and some northward propagating convective events. Analysis of these events shows that two adjacent cells with cyclonic and anticyclonic vorticity are created over the warm SST anomaly and to the west. The propagation occurs due to the convective region drawn north in the convergence zone between these vortices. Zonally propagating Madden-Julian oscillations (MJO) are discussed in the second part of the thesis. All the experiments in this part are based on the zonally symmetric SST. The zonally symmetric January SST configuration gives an MJO-like mode, with zonal wave number 1 and a period of 40-90 days. The SST structure has a nearly meridionally symmetric structure, with local SST maxima on either side of the equator, and a small dip in the equatorial region. If we replace this dip with an SST maximum, the time-scale of MJO becomes significantly smaller (20-40 days). The implication is that an SST maximum in the equatorial region reduces the strength of MJO, and a flat SST profile in the equatorial region is required for more energetic of MJO. This result was tested and found to be valid in a series of further experiments.