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Article

A Lagrangian Backward Air Parcel Trajectories Clustering Framework

Computer Science and Engineering Department, University Politehnica of Bucharest, 060042 Bucharest, Romania
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Academic Editor: Kai Yan
Water 2021, 13(24), 3638; https://doi.org/10.3390/w13243638
Received: 25 November 2021 / Revised: 4 December 2021 / Accepted: 13 December 2021 / Published: 17 December 2021
(This article belongs to the Special Issue Smart Water Solutions with Big Data)
Many studies concerning atmosphere moisture paths use Lagrangian backward air parcel trajectories to determine the humidity sources for specific locations. Automatically grouping trajectories according to their geographical position simplifies and speeds up their analysis. In this paper, we propose a framework for clustering Lagrangian backward air parcel trajectories, from trajectory generation to cluster accuracy evaluation. We employ a novel clustering algorithm, called DenLAC, to cluster troposphere air currents trajectories. Our main contribution is representing trajectories as a one-dimensional array consisting of each trajectory’s points position vector directions. We empirically test our pipeline by employing it on several Lagrangian backward trajectories initiated from Břeclav District, Czech Republic. View Full-Text
Keywords: Lagrangian backward trajectories; clustering; HYSPLIT; position vectors Lagrangian backward trajectories; clustering; HYSPLIT; position vectors
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MDPI and ACS Style

Rădulescu, I.-M.; Boicea, A.; Rădulescu, F.; Popeangă, D.-C. A Lagrangian Backward Air Parcel Trajectories Clustering Framework. Water 2021, 13, 3638. https://doi.org/10.3390/w13243638

AMA Style

Rădulescu I-M, Boicea A, Rădulescu F, Popeangă D-C. A Lagrangian Backward Air Parcel Trajectories Clustering Framework. Water. 2021; 13(24):3638. https://doi.org/10.3390/w13243638

Chicago/Turabian Style

Rădulescu, Iulia-Maria, Alexandru Boicea, Florin Rădulescu, and Daniel-Călin Popeangă. 2021. "A Lagrangian Backward Air Parcel Trajectories Clustering Framework" Water 13, no. 24: 3638. https://doi.org/10.3390/w13243638

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