Climate simulation is very challenging that it involves a large number of interacting physical processes. Community earth system model (CESM) extensively applied to predict regional and global climate, is a state-of-art open source coupled climate system. CESM application requires great amount of computation, and future ultrahigh-resolution climate simulations demand even larger scale parallelism. In recent years, the emergence of ARM-based HPC clusters have provided a novel alternative to host these cyber-physical systems. Scalability and power efficiency are two critical issues for traditional HPC (high performance computing) platforms. Compared with traditional X86 platforms, ARM-based processors provide higher memory bandwidth and more cores per chip, which can potentially benefit the application scalability. In this work, we successfully port CESM to Huawei Kunpeng platform based on ARM architecture. Based on the runtime data of CESM, a customized C/Fortran compiler is proposed and the process scheduling algorithm is improved. Extensive experiments have been conducted on Huawei Kunpeng platform and Intel Xeon platform. Results illustrate that optimized CESM instance on Huawei Kunpeng platform has notable performance improvement, 31.78%~42.93% overall, and better scalability, in spite of relatively lower single core performance.