PNNL

Abstract

Recent studies have shown that reducing the precision of floating-point calculations in an atmospheric model can improve the models' computational performance without affecting model fidelity, but code changes are needed to accommodate lower precision, and a small number of calculations might need to retain higher precision to prevent undue round-off error. For complex and computationally expensive systems like the Energy Exascale Earth System Model (E3SM), a method is needed to objectively assess the quality of the lower-precision simulations and to quickly identify problematic code pieces This paper demonstrates that solution correctness can be evaluated through a simple and quantitative error metric based on time step convergence. The proposed test method can unambiguously detect the accumulation of precision error and objectively assess its impact on solution accuracy. Since fast physical processes are known to affect key features of the multi-year mean climate in an atmospheric model, we show that the convergence test applied to short simulations can provide useful information about the impact of reduced precision on a model’s long-term behavior. In contrast, the traditional way of climate model evaluation requires multi-year simulations and involves inspecting many physical quantities for statistical significance in the presence of natural variability. The simplicity, computational efficiency, and objectivity of the proposed method makes it very attractive for high-resolution model development. The method is also expected to be applicable to other models that numerically solve time evolution equations.