A Comprehensive Long-term (1981–2020) Radiation Dataset for China: Ensuring Consistency, Comparability, and Incorporating Uncertainty

The dataset provides comprehensive radiation data and associated uncertainties on both monthly and yearly scales for global radiation, diffuse radiation, photosynthetically active radiation (PAR), and diffuse PAR across China from 1981 to 2020, based on observations from the China Meteorological Administration (CMA) and the Chinese Ecosystem Research Network (CERN).In a previous study, our research group established a radiation dataset for China spanning 1981 to 2010 (Ren et al., 2018). Building on this foundation, the present study integrated all available radiation observations spanning 1981–2020 to re-optimize the empirical model parameters and thereby reconstruct a new, continuous 40-year radiation dataset. Subsequently, an advanced machine learning approach—Gaussian Process Regression (GPR)—was applied to produce a spatially continuous, high-accuracy radiation dataset for 1981–2020, encompassing global radiation, PAR, and their diffuse components, along with corresponding uncertainty estimates.This dataset is valuable for analyzing the spatio-temporal variations of solar radiation in China, investigating the impact of radiation on terrestrial ecosystems, and conducting ecosystem modeling and uncertainty analysis.