  One way of defining probability distributions for circular variables
(directions in two dimensions) is to radially project probability
distributions, originally defined on $\mathbb{R}^2$, to the unit circle.
Projected distributions have proved to be useful in the study of circular and
directional data. Although any bivariate distribution can be used to produce a
projected circular model, these distributions are typically parametric. In this
article we consider a bivariate P\'olya tree on $\mathbb{R}^2$ and project it
to the unit circle to define a new Bayesian nonparametric model for circular
data. We study the properties of the proposed model, obtain its posterior
characterisation and show its performance with simulated and real datasets.
