Kilometer-Scale AI-Powered and Performance-Portable Earth System Model (AP3ESM) to Achieve Year-Scale Simulation Speed on Heterogeneous Supercomputers

Kilometer-scale Earth system models (ESMs) necessitate exascale supercomputers to facilitate realistic simulations of weather phenomena and climate variability over a time span ranging from days to decades. We present AP3ESM, an ultra‑high‑resolution, AI‑Powered, Performance‑Portable ESM coupling atmosphere, land surface, ocean, and sea ice components. By leveraging the performance portability features of Kokkos and OpenMP, the AP3ESM operates efficiently on two heterogeneous systems while incurring minimal development overhead. Advanced optimization techniques, such as adaptive parallel algorithms, AI-enhanced physical parameterizations, and mixed-precision computations, have been implemented to further boost the computational efficiency. Breaking the 1-km resolution barrier, AP3ESM delivers 0.85 and 1.98 simulated-years-per-day (SYPD) for the standalone atmosphere and ocean components on 34.1 million Sunway cores and 16085 GPUs, respectively; the holistic AP3ESM achieves 0.54 SYPD on 37.2 million Sunway cores. Notably, the forecast experiment successfully captures Super Typhoon Doksuri in 2023 and its associated extreme rainfall across China.