This doctoral dissertation discusses the performance and ageing of PV modules and PV systems operating in different climates worldwide. The primary focus is developing new techniques for assessing the gain and loss factors of PV technologies. Several novel data-driven techniques, such as the Typical Daily Profiles (TDP) method, the Köppen-Geiger-Photovoltaic (KGPV) climate classification scheme, and the Climate Change Yield Assessment (CCYA), are introduced and explained with interesting case studies. The basis of the gain and loss factors of energy production based on typical PV technologies are discussed. Here, diverse and large amounts of data from research facilities, PV power plants, climate models, and satellite-based information are retrieved, combined, cleaned, and processed, bringing valuable insights to the PV industry. The research categorizes data resources into geographical information systems (GIS) and single-time-series, taking advantage of both ways separately and combined. In the frame of this thesis, the selection of relevant PV related data sources and methodologies has allowed the presentation of eye-catching global maps to identify the best places for energy production and the identification of risky locations in terms of degradation, soiling and snow shading. Finally, key performance indicators, such as performance ratio and degradation rates, are analyzed, modelled, and evaluated on a temporal and spatial scale, being able to assess climatic impacts on historical data and under different climate change scenarios.