Implementation of tangent linear and adjoint models for neural networks based on a compiler library tool

ArXi:2603.16976v1 Announce Type: cross This paper presents TorchNWP, a compilation library tool for the efficient coupling of artificial intelligence components and traditional numerical models. It aims to address the issues of poor cross-language compatibility, insufficient coupling flexibility, and low data transfer efficiency between operational numerical models developed in Fortran and Python-based deep learning frameworks.