Session

DescriptionHigh-resolution weather and climate models are rapidly approaching the long-standing goal of simulating one year per day at 1 km global resolution, thanks to GPU-accelerated pre-Exascale and Exascale HPC systems. Achieving this performance sustainably, however, requires more than traditional code optimization – it demands HPC co-design, where scientific developers, numerical analysts, and computational experts collaborate to rethink algorithms for modern hardware. One promising strategy is the use of single- or reduced-precision arithmetic. Lower-precision computations improve memory bandwidth, cache efficiency, and energy usage, and enable exploitation of specialized GPU units optimized for fast, low-precision operations. At the same time, reducing precision raises important questions about scientific trust, numerical stability, and reproducibility, particularly in chaotic, multi-scale Earth system models. This minisymposium will bring together experts from climate science, numerical modeling, and HPC to share experiences, challenges, and best practices in adopting lower-precision computations. Topics include algorithmic reformulation, precision-aware software design, verification and validation strategies, and precision analysis tools. While focused on weather and climate models, the lessons learned are broadly applicable across computational science, offering guidance for building performant, trustworthy, and future-ready models on next-generation HPC platforms.