Incorporating features from the Stochastic Time-Inverted Lagrangian Transport (STILT) model into the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: a unified dispersion model for time-forward and time-reversed applications Article Swipe
Christopher P. Loughner
,
Benjamin Fasoli
,
Ariel Stein
,
John C. Lin
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1175/jamc-d-20-0158.1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1175/jamc-d-20-0158.1
The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL). In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include: a new vertical interpolation algorithm for WRF derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian timescale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical and in better agreement with observations than the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared against backward-time equivalents and found to be statistically comparable to one another.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1175/jamc-d-20-0158.1
- https://journals.ametsoc.org/downloadpdf/journals/apme/60/6/JAMC-D-20-0158.1.pdf
- OA Status
- hybrid
- Cited By
- 43
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3153429575
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3153429575Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1175/jamc-d-20-0158.1Digital Object Identifier
- Title
-
Incorporating features from the Stochastic Time-Inverted Lagrangian Transport (STILT) model into the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: a unified dispersion model for time-forward and time-reversed applicationsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-04-21Full publication date if available
- Authors
-
Christopher P. Loughner, Benjamin Fasoli, Ariel Stein, John C. LinList of authors in order
- Landing page
-
https://doi.org/10.1175/jamc-d-20-0158.1Publisher landing page
- PDF URL
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https://journals.ametsoc.org/downloadpdf/journals/apme/60/6/JAMC-D-20-0158.1.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://journals.ametsoc.org/downloadpdf/journals/apme/60/6/JAMC-D-20-0158.1.pdfDirect OA link when available
- Concepts
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HYSPLIT, Dispersion (optics), Trajectory, Hydrometeorology, Meteorology, Lagrangian, Environmental science, Physics, Applied mathematics, Mathematics, Optics, Astronomy, PrecipitationTop concepts (fields/topics) attached by OpenAlex
- Cited by
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43Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 10, 2023: 20, 2022: 7, 2021: 2Per-year citation counts (last 5 years)
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31Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2791226409, https://openalex.org/W1522164011, https://openalex.org/W2169593822, https://openalex.org/W2162070159, https://openalex.org/W2172622149, https://openalex.org/W2038371231, https://openalex.org/W1582183711, https://openalex.org/W1983075738, https://openalex.org/W2551720803, https://openalex.org/W2025703850, https://openalex.org/W2040812301, https://openalex.org/W2087662098, https://openalex.org/W2979270417, https://openalex.org/W2809727535, https://openalex.org/W2915783575, https://openalex.org/W2150572267, https://openalex.org/W2046410742, https://openalex.org/W309370816, https://openalex.org/W2109065826, https://openalex.org/W2026422942, https://openalex.org/W2338625632, https://openalex.org/W2158077860, https://openalex.org/W1485504984, https://openalex.org/W2175515323, https://openalex.org/W2059560274, https://openalex.org/W1985545401, https://openalex.org/W2626788930, https://openalex.org/W2108508241, https://openalex.org/W9703093, https://openalex.org/W2178292396, https://openalex.org/W1646349196 |
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