High-Impact Weather Effects on Wind and Solar Power Systems under Future Climate Scenarios in China

This dataset accompanies a study that develops an integrated climate–renewable–power-system framework to assess how high-impact weather events and future climate conditions affect wind and solar power generation and supply–demand balance. The repository is designed to make the full workflow transparent and reproducible, from meteorological drivers, through renewable generation and transmission optimisation, to the quantitative indicators and figures reported in the paper.
The archive brings together three groups of Python codes and the numerical source data for all figures. The data processing codes include scripts for detecting high-impact weather (HIW) events, harmonising and aggregating meteorological inputs, and treating missing values and outliers. The integrated assessment framework codes implement the core modules that link climate drivers, renewable power generation and the inter-regional transmission system, covering meteorology projection, wind and PV power conversion, and multi-period power-system optimisation under capacity, loss and storage constraints. The data analysis codes post-process the model outputs into annual deficits, durations, peak shortfalls and scenario-comparison metrics that underpin the results in the main text and Supplementary Information.
In addition, the repository provides a compressed figures source data package (numerical source data for each figure and panel, together with a short note on plotting) and a dataset description/framework description that document the external data sources, directory structure and typical workflow for running the model. Due to licensing restrictions, raw meteorological and demand datasets are not redistributed here; instead, users can obtain them directly from the original providers following the links and guidance in Dataset description.txt and then use the supplied scripts to reproduce the analyses. All codes are written in Python (version ≥3.10) using standard scientific libraries and are released under the CC BY 4.0 license.