Computação de alto desempenho aplicada a modelagem numérica de fenômenos atmosféricos

A constante evolução da tecnologia disponibilizou, atualmente, ferramentas computacionais que eram apenas expectativas há 10 anos atrás. O aumento do potencial computacional aplicado a modelos numéricos que simulam a atmosfera permitiu ampliar o estudo de fenômenos atmosféricos, através do uso de ferramentas de computação de alto desempenho. O trabalho propôs o desenvolvimento de algoritmos com base em arquiteturas SIMT e aplicação de técnicas de paralelismo com uso da ferramenta OpenACC para processamento de dados de previsão numérica do modelo Weather Research and Forecast. Esta proposta tem forte conotação interdisciplinar, buscando a interação entre as áreas de modelagem atmosférica e computação científica. Foram testadas a influência da computação do cálculo de microfísica de nuvens na degradação temporal do modelo. Como a entrada de dados para execução na GPU não era suficientemente grande, o tempo necessário para transferir dados da CPU para a GPU foi maior do que a execução da computação na CPU. Outro fator determinante foi a adição de código CUDA dentro de um contexto MPI, causando assim condições de disputa de recursos entre os processadores, mais uma vez degradando o tempo de execução. A proposta do uso de diretivas para aplicar computação de alto desempenho em uma estrutura CUDA parece muito promissora, mas ainda precisa ser utilizada com muita cautela a fim de produzir bons resultados. A construção de um híbrido MPI + CUDA foi testada, mas os resultados não foram conclusivos.

Toward assessing the effects of aerosols on deep convection: a numerical study using the WRF-Chemistry model

As the formative agents of cloud droplets, aerosols play an undeniably important role in the development of clouds and precipitation. Few meteorological models have been developed or adapted to simulate aerosols and their contribution to cloud and precipitation processes. The Weather Research and Forecasting model (WRF) has recently been coupled with an atmospheric chemistry suite and is jointly referred to as WRF-Chem, allowing atmospheric chemistry and meteorology to influence each other’s evolution within a mesoscale modeling framework. Provided that the model physics are robust, this framework allows the feedbacks between aerosol chemistry, cloud physics, and dynamics to be investigated. This study focuses on the effects of aerosols on meteorology, specifically, the interaction of aerosol chemical species with microphysical processes represented within the framework of the WRF-Chem. Aerosols are represented by eight size bins using the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) sectional parameterization, which is linked to the Purdue Lin bulk microphysics scheme. The aim of this study is to examine the sensitivity of deep convective precipitation modeled by the 2D WRF-Chem to varying aerosol number concentration and aerosol type. A systematic study has been performed regarding the effects of aerosols on parameters such as total precipitation, updraft/downdraft speed, distribution of hydrometeor species, and organizational features, within idealized maritime and continental thermodynamic environments. Initial results were obtained using WRFv3.0.1, and a second series of tests were run using WRFv3.2 after several changes to the activation, autoconversion, and Lin et al. microphysics schemes added by the WRF community, as well as the implementation of prescribed vertical levels by the author. The results of WRFv3.2 runs contrasted starkly with WRFv3.0.1 runs. The WRFv3.0.1 runs produced a propagating system resembling a developing squall line, whereas the WRFv3.2 runs did not. The response of total precipitation, updraft/downdraft speeds, and system organization to increasing aerosol concentrations were opposite between runs with different versions of WRF. Results of the WRFv3.2 runs, however, were in better agreement in timing and magnitude of vertical velocity and hydrometeor content with a WRFv3.0.1 run using single-moment Lin et al. microphysics, than WRFv3.0.1 runs with chemistry. One result consistent throughout all simulations was an inhibition in warm-rain processes due to enhanced aerosol concentrations, which resulted in a delay of precipitation onset that ranged from 2-3 minutes in WRFv3.2 runs, and up to 15 minutes in WRFv.3.0.1 runs. This result was not observed in a previous study by Ntelekos et al. (2009) using the WRF-Chem, perhaps due to their use of coarser horizontal and vertical resolution within their experiment. The changes to microphysical processes such as activation and autoconversion from WRFv3.0.1 to WRFv3.2, along with changes in the packing of vertical levels, had more impact than the varying aerosol concentrations even though the range of aerosol tested was greater than that observed in field studies. In order to take full advantage of the input of aerosols now offered by the chemistry module in WRF, the author recommends that a fully double-moment microphysics scheme be linked, rather than the limited double-moment Lin et al. scheme that currently exists. With this modification, the WRF-Chem will be a powerful tool for studying aerosol-cloud interactions and allow comparison of results with other studies using more modern and complex microphysical parameterizations.

Investigations of Cloud Microphysical Response to Mixing Using Digital Holography

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the `single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other `bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a `humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.