Literature DB >> 25433385

A comparison of HYSPLIT backward trajectories generated from two GDAS datasets.

Lin Su1, Zibing Yuan2, Jimmy C H Fung3, Alexis K H Lau4.   

Abstract

The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is widely used to generate backward trajectories in given starting locations. However, differences exist between trajectories generated from the model with different input datasets. In this study, backward trajectories in Hong Kong in the entire year of 2011 are derived by HYSPLIT model. Two sets of Global Data Assimilation System (GDAS) output data associated with different horizontal and vertical resolutions (GDAS1 and GDAS0P5) are used as drivers in an attempt to quantify the differences between the results and discover the underlying reasons responsible for discrepancy. The results reveal that the significant differences between back trajectories generated from the two GDAS datasets can be mainly attributed to different vertical velocity calculation methods due to the absence of vertical velocity in GDAS0P5 dataset. The HYSPLIT trajectories are also sensitive to the horizontal and vertical resolutions of the input meteorological data, but to lesser extents. Results of cluster analysis indicate that when the air mass is from the north, northeast, or west with a long-to-medium range, the HYSPLIT backward trajectories are sensitive to the vertical advection calculation method and data resolution, whereas when the air mass is from the south or southwest with a long range, the trajectories are more likely to remain unchanged with the shifting of vertical velocity or data resolution. By comparing the vertical velocities with the observations and the performance in retrieving PM contributions from different directions, we conclude that GDAS1 dataset is more plausible in backward trajectory analysis in the Pearl River Delta.
Copyright © 2014 Elsevier B.V. All rights reserved.

Keywords:  Backward trajectory; GDAS; HYSPLIT; Hong Kong; Vertical velocity

Mesh:

Substances:

Year:  2014        PMID: 25433385     DOI: 10.1016/j.scitotenv.2014.11.072

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

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Journal:  Nat Commun       Date:  2022-02-22       Impact factor: 17.694

  4 in total

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