Disk subsystem is known to be a major contributor to the overall power budget of large-scale parallel systems. Most scientific applications today rely heavily on disk I/O for out-of-core computations, checkpointing, and visualization of data. To reduce excess energy consumption on disk system, prior studies proposed several hardware or OS-based disk power management schemes. While such schemes have been known to be effective in certain cases, they might miss opportunities for better energy savings due to their reactive nature. While compiler based schemes can make more accurate decisions on a given application by extracting disk access patterns statically, the lack of runtime information on the status of shared disks may lead to wrong decisions when multiple applications exercise the same set of disks concurrently. In this paper, we propose a runtime system based approach that provides more effective disk power management. In our scheme, the compiler provides crucial information on the future disk access patterns and preferred disk speeds from the perspective of individual applications, and a runtime system uses this information along with current state of the shared disks to make decisions that are agreeable to all applications. We implemented our runtime system support within PVFS2, a parallel file system. Our experimental results with four I/O-intensive scientific applications indicate large energy savings: 19.4% and 39.9% over the previously-proposed pure software and pure hardware based schemes, respectively. We further show in this paper that our scheme can achieve consistent energy savings with a varying number and mix of applications and different disk layouts of data.