Rapid Joint Downscaling of Multiple Atmospheric Fields to Kilometer Scale With Deep Learning
A U‐Net‐based deep learning framework, the Joint Atmospheric fields Downscaling Network (JADNet), for rapid, joint downscaling of multiple atmospheric variables to kilometer resolution is introduced, offering a powerful tool for scalable high‐resolution weather and climate applications.