Quantifying Physical Climate Risk in Renewable Portfolios: Future Yield, Damage, and Financial Impact

The expansion of global renewable energy capacity is critical for the net-zero transition, yet traditional top-down risk assessments often obscure the specific physical hazards threatening individual assets. To construct truly resilient portfolios, risk managers and portfolio investors require a bottom-up risk assessment framework that aggregates granular, asset-level exposures into a comprehensive financial view. We applied this bottom-up methodology to a global portfolio of utility-scale wind and solar assets with capacities exceeding 20 MW, from the Global Energy Monitor’s Global Wind and Solar Power Trackers database.

Our methodology moves beyond regional averages to model asset-level risk based on specific geolocation and technology types. For solar photovoltaics, we model future power yield by calculating solar cell temperatures at the module level, derived from ambient temperature, incident shortwave radiation, and wind-driven cooling. This allows for precise estimation of temperature-dependent efficiency losses and thermal degradation. For wind energy, bias-corrected wind projections are extrapolated to turbine-specific hub heights, dynamically adjusting power curves and capacity factors. We further refine this bottom-up analysis by incorporating first-principles damage functions for wind and heat impacts on critical components, calibrated against industry-informed damage thresholds.

Our analysis highlights significant regional disparities: while 2030 yield projections in North America and Europe remain relatively stable (showing negligible median deviations of <0.1%), Asia and South America face severe exposure to heat-induced component damage under RCP 8.5, with projected heat damages exceeding 8% and total climate losses in Asia surpassing 20%. These findings represent a critical step towards integrating physical climate science directly into financial asset management. By granulating risk at the asset level, we are advancing the capability to identify optimal locations for technology upgrades and re-energization strategies that are intrinsically resilient to future climate states. Ultimately, this work advances the shift from static historical baselines to dynamic, forward-looking risk assessments. By quantifying these physical constraints, we support investment strategies that ensure the long-term bankability and systemic resilience of the global renewable energy transition.