# Hybridization of CMIP6 and spatiotemporal models for assessing solar energy dynamics and transition risks in Guangxi under “dual-carbon” goals

## TL;DR

This study assesses solar energy potential and transition risks in Guangxi, China, under global carbon reduction goals using climate models and spatiotemporal analysis.

## Contribution

A novel hybrid framework combining CMIP6 and spatiotemporal models to evaluate solar energy dynamics and transition risks under different emission scenarios.

## Key findings

- Solar resources show the highest growth rate under medium-emission scenarios due to atmospheric purification effects.
- Dominant drivers of solar energy dynamics shift from topography to multi-factor synergy with increasing carbon intensity.
- The solar resource center migrates from the southwestern coast to the northeastern interior, increasing spatial instability risks.

## Abstract

Under the global dual-carbon goals, assessing regional solar potential is vital for the energy transition. This study evaluates solar resource potential and spatiotemporal redistribution risks in Guangxi, China, using ECMWF ERA5 and CMIP6 multi-scenario data. We develop an interactive spatiotemporal regression model by integrating optimal parameter geographic detectors with geographically weighted regression to quantify drivers' synergistic effects. Key findings: (1) solar resources exhibit strong path dependency, with the highest growth rate occurring under the medium-emission scenario due to the atmospheric purification effect.; (2) dominant drivers shift with scenarios: topography (low emissions), cloud-aerosol interactions (medium), and multi-factor synergy (high); and (3) The resource center migrates from the southwestern coast to the northeastern interior, with rising spatial-instability risks. This work supports optimized solar deployment and regional energy transition in Guangxi.

•Developed a framework linking pattern diagnosis, drivers, and probabilistic risk•Fastest solar growth in medium-emission scenario due to “air-cleansing effect”•Dominant drivers shift from topography to synergy as carbon scenarios intensify•A new paradigm for assessing subtropical energy-climate risks in complex terrain

Developed a framework linking pattern diagnosis, drivers, and probabilistic risk

Fastest solar growth in medium-emission scenario due to “air-cleansing effect”

Dominant drivers shift from topography to synergy as carbon scenarios intensify

A new paradigm for assessing subtropical energy-climate risks in complex terrain

Environmental science; Energy engineering; Energy Resources