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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-279
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-279
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 20 Oct 2020

Submitted as: model description paper | 20 Oct 2020

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This preprint is currently under review for the journal GMD.

pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python

Daniel M. Gilford1,2 Daniel M. Gilford
  • 1Institute of Earth, Ocean, and Atmospheric Sciences, Rutgers University, 71 Dudley Road, Suite 205, New Brunswick, NJ08901, USA
  • 2Department of Earth and Planetary Sciences, Rutgers University, Piscataway, NJ, USA

Abstract. Potential intensity (PI) is the maximum speed limit of a tropical cyclone found by modeling the storm as a thermal heat engine. Because there are significant correlations between PI and actual storm wind speeds, PI is a useful diagnostic for evaluating or predicting tropical cyclone intensity climatology and variability. Previous studies have calculated PI given a set of atmospheric and oceanographic conditions, but although a PI algorithm – originally developed by Kerry Emanuel – is in widespread use, it remains under-documented. The Tropical Cyclone Potential Intensity Calculations in Python (pyPI, v1.3) package develops the PI algorithm in Python, and for the first time details the full background and algorithm (line-by-line) used to compute tropical cyclone potential intensity constrained by thermodynamics. The pyPI package (1) provides a freely available, flexible, validated Python PI algorithm, (2) carefully documents the PI algorithm and its Python implementation, and (3) demonstrates and encourages the use of PI theory in tropical cyclone analyses. Validation shows pyPI output is nearly identical to the previous potential intensity computation, but is an improvement on the algorithm's consistency and handling of missing data. Example calculations with reanalyses data demonstrate pyPI's usefulness in climatological and meteorological research. Planned future improvements will improve on pyPI's assumptions, flexibility, and range of applications and tropical cyclone thermodynamic calculations.

Daniel M. Gilford

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Daniel M. Gilford

Model code and software

pyPI v1.3 (initial package release) Daniel M. Gilford https://doi.org/10.5281/zenodo.3985975

Daniel M. Gilford

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Latest update: 01 Dec 2020
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Short summary
Potential intensity (PI) is a tropical cylone's maximum speed limit given by modeling the storm as a thermal heat engine. pyPI is the first software package fully documenting the PI algorithm and translating it to Python. This study details/validates the underlying PI model and demonstrates its use in tropical cyclone intensity research. pyPI supports open science and transparency in the tropical meteorological community, and is ideally suited for ongoing community development and improvement.
Potential intensity (PI) is a tropical cylone's maximum speed limit given by modeling the storm...
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