Comment on gmd-2021-395

Abstract

Working with measurement data in atmospheric science often necessitates the collocation of observations from instruments or platforms at different locations, with different geographical and/or temporal data coverage. Varying complexity and abundance of the different data sets demand a consolidation of the observations. This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of observations and other derived parameters in the vicinity of intersections to achieve the optimal combination of various data sets and measurement techniques. The TrackMatcher tool has been designed specifically for matching height-resolved remote-sensing observations along the ground track of a satellite with position data of aircraft (flight tracks) and clouds (cloud tracks) and intended extension for ships (shiptracks) and air parcels (forward and backward trajectories). The open-source algorithm is written in the Julia programming language. The core of the matching algorithm consist of interpolating tracks of different objects with a piecewise cubic Hermite interpolating polynomial with subsequent identification of an intercept point by minimising the norm between the different track point coordinate pairs. The functionality wrapped around the two steps allows for application of the TrackMatcher tool to a wide range of scenarios. Here, we present three examples of matching satellite tracks with the position of individual aircraft and clouds that demonstrate the usefulness of TrackMatcher for application in atmospheric science.