The transformation of solar energy into electricity is starting to impact to overall worldwide energy production mix. Photovoltaic-generated electricity can play a significant role in minimizing the use of non-renewable energy sources. Sunlight consists of three main components: global horizontal irradiance (GHI), direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI). Typically, these components are measured using specialized instruments in order to study solar radiation at any location. However, these measurements are not always available, especially in the case of the DNI and DHI components of sunlight. Consequently, many models have been developed to estimate these components from available GHI data. These models have their own merits. For this thesis, solar radiation data collected at four locations have been analyzed. The data come from Al-Hanakiyah (Saudi Arabia), Boulder (U.S.), Ma’an (Jordan), and Ottawa (Canada). The BRL, Reindl*, DISC, and Perez models have been used to estimate DNI and DHI data from the experimentally measured GHI data. The findings show that the Reindl* and Perez model outcomes offered similar accuracy of computing DNI and DHI values when comparing with detailed experimental data for Al-Hanakiyah and Ma’an. For Boulder, the Perez and BRL models have similar estimation abilities of DHI values and the DISC and Perez models are better estimators of DNI. The Reindl* model performs better when modeling DHI and DNI for Ottawa data. The BRL and DISC models show similar metrics error analyses, except in the case of the Ma’an location where the BRL model shows high error metrics values in terms of MAE, RMSE, and standard deviation (σ). The Boulder and Ottawa locations datasets were not complete and affected the outcomes with regards to the model performance metrics. Moreover, the metrics show very high, unreasonable values in terms of RMSE and σ. It is advised that a global model be developed by collecting data from many locations as a way to help minimize the error between the actual and modeled values since the current models have their own limitations. Availability of multi-year data, parameters such as albedo and aerosols, and one minute to hourly time steps data could help minimize the error between measured and modeled data. In addition to having accurate data, analysis of spectral data is important to evaluate their impact on solar technologies.

This thesis details work carried out by two students working as contractors at the Community Coordinated Modelling Center at Goddard Space Flight Center of the National Aeronautics and Space Administration. The thesis is made possible by and aims to contribute to the OpenSpace project. The first track of the work implemented is the handling of and putting together new data for a visualization of coronal mass ejections in OpenSpace. The new data allows for observation of coronal mass ejections at their origin by the surface of the Sun, whereas previous data visualized them from 30 solar radii out from the Sun and outwards. Previously implemented visualization techniques are used together to visualize different volume data and fieldlines, which together with a synoptic magnetogram of the Sun gives a multi-layered visualization. The second track is an experimental implementation of a generalized and less user involved process for getting new data into OpenSpace, with a priority on volume data as that was a subject of experience. The results show a space weather model visualization, and how one such model can be adapted to fit within the parameters of the OpenSpace project. Additionally, the results show how a GUI connected to a series of background events can form a data pipeline to make complicated space weather models more easily available.