  We review how machine learning has transformed our ability to model the Earth
system, and how we expect recent breakthroughs to benefit end-users in
Switzerland in the near future. Drawing from our review, we identify three
recommendations.
  Recommendation 1: Develop Hybrid AI-Physical Models: Emphasize the
integration of AI and physical modeling for improved reliability, especially
for longer prediction horizons, acknowledging the delicate balance between
knowledge-based and data-driven components required for optimal performance.
Recommendation 2: Emphasize Robustness in AI Downscaling Approaches, favoring
techniques that respect physical laws, preserve inter-variable dependencies and
spatial structures, and accurately represent extremes at the local scale.
Recommendation 3: Promote Inclusive Model Development: Ensure Earth System
Model development is open and accessible to diverse stakeholders, enabling
forecasters, the public, and AI/statistics experts to use, develop, and engage
with the model and its predictions/projections.
