Merge trees are a common topological descriptor for data with a hierarchical component, such as terrains and scalar fields. The interleaving distance, in turn, is a common distance measure for comparing merge trees. However, the interleaving distance for merge trees is solely based on the hierarchical structure, and disregards any other geometrical or topological properties that might be present in the underlying data. Furthermore, the interleaving distance is NP-hard to compute. In this paper, we introduce a form of ordered merge trees that does capture intrinsic order present in the data. We further define a natural variant of the interleaving distance, the monotone interleaving distance, which is an order preserving distance measure for ordered merge trees. Analogous to the regular interleaving distance for merge trees, we show that the monotone variant has three equivalent definitions in terms of two maps, a single map, or a labelling. The labelling-based definition fairly directly leads to an efficient algorithm for computing the monotone interleaving distance, but unfortunately it computes only an approximation thereof. Instead, we discover a surprising connection between the monotone interleaving distance of ordered merge trees and the Fr\'{e}chet distance of 1D curves. As a result, the monotone interleaving distance between two ordered merge trees of total complexity $n$ can be computed exactly in $\tilde O(n^2)$ time. The connection between the monotone interleaving distance and the Fr\'{e}chet distance establishes a new bridge between the fields of computational topology/topological data analysis, where interleaving distances are studied extensively, and computational geometry, where Fr\'{e}chet distances are studied extensively.

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