Large-scale Computational Fluid Dynamics (CFD) simulations are typical HPC applications that require both high memory bandwidth and large memory capacity. However, it is difficult to achieve high performance for such applications on modern high-performance processors due to their low memory bandwidth compared to their high computational power. Near-memory computing can overcome this problem by placing on-chip memory near arithmetic units and reducing off-chip accesses. MN-Core is a distributed memory SIMD processor with each core having its own addressable memory, realizing a near-memory computing processor. MN-Core can be an attractive platform for executing bandwidth-demanding HPC applications. This paper reports the performance of MN-Core for three kernels from the NICAM benchmark, taken from NICAM global climate model. The evaluation results show that MN-Core realizes 986 GFLOPS at the maximum, which is 13.4% of its peak performance. This efficiency is comparable to those obtained on CPUs with high memory bandwidth, such as Fujitsu A64FX.