Simulating Climate Responses to Large-Scale Photovoltaic Deployment with PlaSim

The rapid integration of renewable energy into national and global electricity systems is a cornerstone of climate mitigation strategies consistent with the Paris Agreement. Photovoltaics (PV) are central to this transition, with global installed capacity exceeding 800 GW by 2021 and projections indicating multi-terawatt deployment by mid-century (IRENA, World energy transitions outlook, 2023). While large-scale PV expansion is essential for decarbonization, it also constitutes a substantial land-surface modification that can influence surface energy fluxes, radiation balance, and atmospheric circulation. Quantifying these interactions is therefore important for understanding the broader environmental implications of renewable energy systems at scale.

Here, we investigate the climatic response to spatially extensive PV deployment using the intermediate-complexity climate model PLASIM (Fraedrich et al., 2005). We perform idealized global simulations with varying fractions of land surface covered by PV, across multiple horizontal resolutions (T21, T31, T42) and three model configurations: atmosphere-only, mixed-layer ocean, and a large-scale geostrophic ocean. This framework allows us to contrast short-term atmospheric adjustments with longer-term, ocean-coupled responses, and to assess the sensitivity of results to spatial resolution and coupling timescales.

Our results show that the climate response to PV deployment is strongly dependent on the albedo contrast between PV panels and the underlying surface. Low effective panel efficiency leads to surface warming due to reduced albedo, while intermediate efficiencies yield mixed regional responses. At high efficiencies, cooling emerges relative to the control climate. These non-linear responses highlight the importance of background land properties and surface–radiation interactions in shaping the climatic impacts of renewable energy deployment.

While the simulations represent idealized and prospective scenarios, we discuss pathways for linking such model-based assessments with long-term field measurements and remote-sensing observations of existing solar installations. Although a clear scale mismatch exists between climate-model grid cells and observed PV sites, observational datasets provide valuable constraints on surface temperature, albedo changes, and land-cover effects. Combining retrospective observations with prospective climate-model experiments offers a promising avenue for cross-examining renewable energy impacts across spatial and temporal scales.

This study contributes to the spatial and temporal modelling of renewable energy systems by bridging climate-system modelling, land-surface impacts, and future deployment scenarios, and by outlining how modelling and observations together can inform sustainable pathways for large-scale solar energy expansion.