Scientific applications are diverse in terms of the resource requirements, and tend to vary significantly from commercial applications. In order to provide sustained performance, a target high performance computing (HPC) platform must offer a balance between CPU performance to memory, interconnect and I/O subsystems performance. We characterize the system balance requirements for two largescale Office of Science applications, GYRO (fusion simulation) and POP (climate modeling), and develop platformindependent parameterized requirement models. We measure the parallel efficiencies for GYRO and POP on three multiprocessor systems: an SMP cluster (IBM p690), a shared-memory system (SGI Altix) and a vector supercomputer (Cray X1). The higher computational intensity and interconnect bandwidth requirements of GYRO result in higher performance efficiencies on the vector platform. At the same time, small message sizes in POP benefit from low MPI latencies of the shared-memory platform. Overall results confirm system balance requirements that are generated by the requirement models.