Climate Impacts on Photovoltaic Performance and Implications for the Global Solar Energy Transition

Limiting global warming to 1.5 °C above pre-industrial levels requires a rapid and sustained transition to renewable energy systems, with photovoltaic (PV) solar energy playing a central role due to its scalability and declining costs. However, PV power generation is inherently sensitive to atmospheric conditions such as aerosols, cloud cover, and temperature, which vary spatially and are expected to evolve under climate change. While global PV capacity has expanded rapidly, climate-related impacts on PV energy generation, particularly at the facility level, remain insufficiently quantified. Many existing assessments rely on generalized assumptions, overlooking the heterogeneity of PV deployment and local environmental conditions, which limits their relevance for integrated energy system modelling and planning.

This study combines machine learning and satellite-based observations to improve the representation of PV systems and climate-related performance losses in global-scale assessments. A machine learning model is trained on diverse geospatial datasets to identify PV installations across a range of geographic and land-use contexts, including complex terrains. Facility-level PV data are then integrated with satellite and reanalysis products to quantify the influence of aerosols, cloud variability, and temperature on solar energy generation over the past decade.

Results reveal pronounced regional variability in PV energy losses, driven by differences in atmospheric composition, cloud dynamics, and thermal stress. Elevated aerosol loads are associated with significant reductions in surface solar irradiance, while cloud variability affects both average generation and short-term reliability. Extreme temperatures further reduce PV efficiency in certain regions. These findings highlight the importance of incorporating site-specific climate sensitivities into energy system models to better assess performance, resilience, and trade-offs in renewable energy deployment.

By shifting the focus from installed capacity to climate-related energy losses, this work contributes to integrated assessments of sustainable energy transitions. The approach provides actionable insights for system planning, model improvement, and policy development, supporting more robust and environmentally informed strategies for scaling solar energy within diversified and resilient energy systems.