A High-Resolution (1km) Daily Precipitation Dataset via Causal Deep Learning (2000–2023)

This dataset provides a high-resolution daily precipitation record specifically covering Hubei Province, China, spanning from 2000 to 2023. Generated utilizing advanced causal deep learning methodologies, it features a fine spatial resolution of 1 kilometer and a daily temporal resolution, making it highly suitable for detailed regional meteorological research, hydrological modeling, and climate change impact assessments across the province. By employing a causal deep learning framework rather than relying solely on traditional statistical correlations, this dataset explicitly models the underlying cause-and-effect relationships within the climate system. This innovative approach ensures a physically robust, accurate, and reliable representation of complex spatial and temporal precipitation dynamics tailored to the specific geographical and climatic conditions of Hubei Province. The development of this dataset was financially supported by the Wuhan Natural Science Foundation Exploration Project (Chenguang Project) under grant number 2024040801020279. Researchers and practitioners utilizing this precipitation data for academic or applied studies are kindly requested to properly cite the dataset and acknowledge this funding source in their related publications and research outputs.