Uncertainty in wind and solar projections depends on global and regional climate models

TL;DR

This study analyzes how different climate models contribute to uncertainty in wind and solar energy projections, highlighting the dominant sources of variability across regions and seasons to improve energy planning under climate change.

Contribution

It quantifies the relative contributions of regional and global climate models to projection uncertainty, guiding better ensemble design for energy decision-making.

Findings

RCMs dominate variability in historical wind and solar data.

GCMs primarily influence projected wind speed changes.

Seasonal and regional differences affect model contribution to uncertainty.

Abstract

Ensembles of regional-global climate model combinations show substantial spread in projected wind and solar resources. Using 31 RCM-GCM pairs, we quantify the sources of this spread with a spatially and seasonally resolved variance decomposition, separating contributions from RCMs and GCMs. For both wind speed and solar radiation, RCMs dominate the variability in the absolute historical fields. In contrast, projected changes in wind speed are largely controlled by the driving GCMs, except in mountainous regions where RCM-induced variance becomes larger than that induced by GCMs. For solar radiation, contributions are strongly season-dependent, with RCMs dominating in summer and GCMs in winter. Our findings support that GCM and RCM variability together define the uncertainty of wind and solar climate projections. This provides guidance for designing climate model ensembles that better support uncertainty-aware energy system decisions under climate change.