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https://github.com/darothen/pyrcel

A 0D, adiabatic cloud parcel model for studying aerosol activation.
https://github.com/darothen/pyrcel

Last synced: 12 days ago
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A 0D, adiabatic cloud parcel model for studying aerosol activation.

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README 

        
pyrcel: cloud parcel model

==========================



![sample parcel model run](docs/figs/model_example.png)



[![DOI](https://zenodo.org/badge/12927551.svg)](https://zenodo.org/badge/latestdoi/12927551)[![PyPI Version](https://badge.fury.io/py/pyrcel.svg)](https://badge.fury.io/py/pyrcel)[![CircleCI Build Status](https://circleci.com/gh/darothen/pyrcel/tree/master.svg?style=svg)](https://circleci.com/gh/darothen/pyrcel/tree/master)[![Documentation Status](https://readthedocs.org/projects/pyrcel/badge/?version=stable)](http://pyrcel.readthedocs.org/en/stable/?badge=stable)



This is an implementation of a simple, adiabatic cloud parcel model for use in

aerosol-cloud interaction studies. [Rothenberg and Wang (2016)](http://journals.ametsoc.org/doi/full/10.1175/JAS-D-15-0223.1) discuss the model in detail and its improvements

 and changes over [Nenes et al (2001)][nenes2001]:



* Implementation of κ-Köhler theory for condensation physics ([Petters and

Kreidenweis, 2007)][pk2007]

* Extension of model to handle arbitrary sectional representations of aerosol

populations, based on user-controlled empirical or parameterized size distributions

* Improved, modular numerical framework for integrating the model, including bindings

to several different stiff integrators:

    - `lsoda` - [scipy ODEINT wrapper](http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.odeint.html)

    - `vode, lsode*, lsoda*` - ODEPACK via [odespy][hplgit]

    - `cvode` - SUNDIALS via [Assimulo](http://www.jmodelica.org/assimulo_home/index.html#)



among other details. It also includes a library of droplet activation routines and scripts/notebooks for evaluating those schemes against equivalent calculations done with the parcel model.



Updated code can be found the project [github repository](https://github.com/darothen/pyrcel). If you'd like to use this code or have any questions about it, please [contact the author][author_email]. In particular, if you use this code for research purposes, be sure to carefully read through the model and ensure that you have tweaked/configured it for your purposes (i.e., modifying the accomodation coefficient); other derived quantities).



[Detailed documentation is available](http://pyrcel.readthedocs.org/en/latest/index.html), including a [scientific description](http://pyrcel.readthedocs.org/en/latest/sci_descr.html), [installation details](http://pyrcel.readthedocs.org/en/latest/install.html), and a [basic example](http://pyrcel.readthedocs.org/en/latest/examples/basic_run.html) which produces a figure like the plot at the top of this page.



Quick Start / Installation

--------------------------



To quickly get started with running pyrcel, complete the following steps:



* Set up a new Python environment; we recommend using [mambaforge](https://conda-forge.org/miniforge/):

  

``` shell

  $ mamba create -n pyrcel_quick_start python=3.11

```



* Activate the new Python environment and install the model and its dependencies. If you install the published version from PyPi (_recommended_), then you also need to install [Assimulo](http://www.jmodelica.org/assimulo) using the Mamba package manager - but no other manual dependency installation is necessary:

  

``` shell

  $ mamba activate pyrcel_quick_start

  $ pip install pyrcel

  $ mamba install -c conda-forge assimulo

```



* Run a test simulation using the CLI tool and a sample YAML file from **pyrcel/examples/\*.yml** (you may want to clone the repository or download them locally):

  

``` shell

  $ run_parcel simple.yml

```



* Visualize the output NetCDF (should be in the directory you ran the CLI tool, at **output/simple.nc**)



That's it!



Requirements

------------



**Required**



* Python >= 3.7

* [numba](http://numba.pydata.org)

* [NumPy](http://www.numpy.org)

* [SciPy](http://www.scipy.org)

* [pandas](http://pandas.pydata.org) - v0.25+

* [xarray](http://xarray.pydata.org/en/stable/) - v2023+

* [PyYAML](http://pyyaml.org/)



**Optional**



The following packages are used for better numerics (ODE solving)



* [Assimulo](http://www.jmodelica.org/assimulo)



The easiest way to satisfy the basic requirements for building and running the

model is to use the [Anaconda](http://continuum.io/downloads) scientific Python

distribution. Alternatively, a

[miniconda environment](http://conda.pydata.org/docs/using/envs.html) is

provided to quickly set-up and get running the model. Assimulo's dependency on

the SUNDIALS library makes it a little bit tougher to install in an automated

fashion, so it has not been included in the automatic setup provided here; you

should refer to [Assimulo's documentation](http://www.jmodelica.org/assimulo_home/installation.html)

for more information on its installation process. Note that many components of

the model and package can be used without Assimulo.



Development

-----------



[http://github.com/darothen/pyrcel]()



Please fork this repository if you intend to develop the model further so that the

code's provenance can be maintained.



License

-------



[All scientific code should be licensed](http://www.astrobetter.com/the-whys-and-hows-of-licensing-scientific-code/). This code is released under the New BSD (3-clause) [license](LICENSE.md).



[author_email]: mailto:[email protected]

[nenes2001]: http://nenes.eas.gatech.edu/Preprints/KinLimitations_TellusPP.pdf

[pk2007]: http://www.atmos-chem-phys.net/7/1961/2007/acp-7-1961-2007.html

[hplgit]: https://github.com/hplgit/odespy