MetaSD: a unified framework for scalable downscaling of meteorological variables in diverse situations

Key Points

• Downscaling of meteorological variables enhances accuracy in diverse models, offering better predictive capabilities.
• The framework facilitates scalability for different climatic conditions, supporting versatile data integration.
• Analysis incorporates various climate models, enhancing adaptability and applicability across regions.
• Applications may revolutionize climate forecasting, though challenges in implementing diverse situations remain.