humpi: The python code for the Hurricane Maximum Potential Intensity (HuMPI) model

[apalarcon]

Submitting Author: Albenis Pérez-Alarcón (@apalarcon)
Package Name: HuMPI: Hurricane Maximum Potential Intensity model One-Line Description of Package: https://github.com/apalarcon/HuMPI-master Repository Link: https://github.com/apalarcon/HuMPI-master Version submitted: V1.0 Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD

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Description

• Include a brief paragraph describing what your package does: The potential intensity (PI) of tropical cyclones (TCs) is the maximum surface wind speed and minimum central pressure limits found by representing the storm as a thermal heat engine. The PI theory proposed by @Emanuel1986 (hereafter E-PI) has been widely accepted as the upper bound for TCs intensity. In the E-PI theory, the dynamic and thermodynamic processes of the TC are described as an energy cycle like a Carnot engine, absorbing heat from the ocean, giving it up at the tropopause. Nevertheless, the "superintensity" phenomenon, which occurs when the observed or modelled TC intensity is higher than the E-PI prediction, is a research challenge nowadays. In a recent attempt to avoid the "superintensity" phenomenon, it was proposed a new hurricane maximum potential intensity (HuMPI) model based on the E-PI theory. HuMPI describes the TC thermo-energetic cycle as a generalized Carnot cycle and includes a TC model for the atmospheric boundary layer. This work aims to implement the HuMPI model formulation in Python.

Scope

• Please indicate which category or categories this package falls under:
  • [ ] Data retrieval
  • [ ] Data extraction
  • [ ] Data munging
  • [ ] Data deposition
  • [x] Reproducibility
  • [ ] Geospatial
  • [x] Education
  • [ ] Data visualization*

* Please fill out a pre-submission inquiry before submitting a data visualization package. For more info, see notes on categories of our guidebook.

• Explain how the and why the package falls under these categories (briefly, 1-2 sentences):

humpi is the Python code of the HuMPI model, which will allow its easy use to calculate the potential intensity of tropical cyclones, both to check and support the results of already published research and for academic purposes

• Who is the target audience and what are scientific applications of this package?

humpi is aimed primarily at researchers in atmospheric sciences, climate change and risk studies and allows the calculation of the potential intensity of tropical cyclones

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

There is pyPI, another python package similar to HuMPI, but both differ in the physical approximations that support the model, that is, the way of calculating the potential intensity in both modules is different

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

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• [x] contains a vignette with examples of its essential functions and uses.
• [ ] has a test suite.
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[NickleDave]

Hi @apalarcon welcome to pyOpenSci and thank you for your interest!

It looks like HuMPI could be within scope, but let's please discuss more before beginning a review.

Could you please edit your initial comment above to address the questions in the template above under the "scope" section?

Explain how the and why the package falls under these categories (briefly, 1-2 sentences):

Who is the target audience and what are scientific applications of this package?

Are there other Python packages that accomplish the same thing? If so, how does yours differ?

Once you provide more detail, I can follow up with other editors.
Thank you again! Just let us know if we can help in any other way

[NickleDave]

@apalarcon just an update that I fixed our template so that it's clearer that submissions should address those points I asked you to fill out (as discussed in #53) -- I'm sorry that wasn't clearer

[lwasser]

hi there @apalarcon thank you so much for your submission to pyopensci. Because we have not heard from you since April 27 2022, we are going to close it. However, if you decide in the future that you wish to submit your package for peer review, you are welcome to resubmit at that time. Please be sure that you have time to respond with our editors before you submit.

@NickleDave thank you so much for taking on the editor role for this submission!!! 🎆