Temporal or dynamic textures (DT's) are video sequences that are spatially repetitive and temporally stationary. DT's are temporal analogs of the well known spatial still image texture. Examples of DT's include moving water, foliage, smoke, clouds, etc. We present a new DT model that can efficiently compress DT sequences. Our proposed method compactly represents the spatiotemporal properties of a DT by modelling its varying Fourier phase content, which can be shown to be the major determinant of both its dynamics and appearance. This is possible because this method combines both temporal and spatial properties in a compact spectral framework. Making use of the benefits inherent to working in the frequency domain, this model provides a significant improvement in DT compression, which can be used to improve the performance of MPEG-2 encoding. We will present experimental evidence that validates this method for a variety of complex sequences, while also comparing it to the most recent DT representational model that is based on modelling a DT as a linear dynamical system (LDS).