Scientific workflows allow scientists to conduct experiments that manipulate data with multiple computational activities using Scientific Workflow Management Systems (SWfMSs). As the scale of the data increases, SWfMSs need to support workflow execution in High Performance Computing (HPC) environments. Because of various benefits, cloud emerges as an appropriate infrastructure for workflow execution. However, it is difficult to execute some scientific workflows in one cloud site because of geographical distribution of scientists, data and computing resources. Therefore, a scientific workflow often needs to be partitioned and executed in a multisite environment. Also, SWfMSs generally execute a scientific workflow in parallel within one site. This paper proposes a non-intrusive approach to execute scientific workflows in a multisite cloud with three workflow partitioning techniques. We describe an experimental validation using an adaptation of Chiron SWfMS for Microsoft Azure multisite cloud. The experiment results reveal the efficiency of our partitioning techniques, and their superiority in different environments.