Topological techniques provide robust tools for data analysis. They are used, for example, for feature extraction, for data de-noising, and for comparison of data sets. This paper concerns contour trees, a topological descriptor that records the connectivity of the isosurfaces of scalar functions. These trees are fundamental to analysis and visualization of physical phenomena modeled by real-valued measurements.

We study the parallel analysis of contour trees. After describing a particular representation of a contour tree, called local--global representation, we illustrate how different problems that rely on contour trees can be solved in parallel with minimal communication.