This paper presents a parallel file object environment to support distributed array store on shared-nothing distributed computing environments. Our environment enables programmers to extend the concept of array distributions from memory levels to file levels. It allows parallel I/O that facilitates the distribution of objects in an application. When objects are read and/or written by multiple applications using different distributions, we present a novel scheme to help programmers to select the best data distribution pattern according to a minimum amount of remote data movements for the store of array objects on distributed file systems. Our selection scheme, to the best of our knowledge, is the first work to attempt to optimize the distribution patterns in the secondary storage for HPF-like programs with inter-application cases. This is especially important for a class of problems called multiple disciplinary optimization (MDO) problems. Our test bed is built on an 8-node DEC Farm connected with an ethernet, FDDI, or ATM switch. Our experimental results with scientific applications show that not only our parallel file system can provide aggregate bandwidths, but also our selection scheme effectively reduces the communication traffic for the system.