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TrackMatcher – a tool for finding intercepts in tracks of geographical positions.

Authors :
Bräuer, Peter
Tesche, Matthias
Source :
Geoscientific Model Development; 2022, Vol. 15 Issue 20, p7557-7572, 16p
Publication Year :
2022

Abstract

Working with measurement data in atmospheric science often necessitates the co-location of observations from instruments or platforms at different locations with different geographical and/or temporal data coverage. The 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 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 is intended to be an extension for ships (ship tracks) 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 the 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 the 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1991959X
Volume :
15
Issue :
20
Database :
Complementary Index
Journal :
Geoscientific Model Development
Publication Type :
Academic Journal
Accession number :
160091897
Full Text :
https://doi.org/10.5194/gmd-15-7557-2022