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Chemistry and Aerosol","monthly_downloads":1618,"total_dependent_repos":1,"total_dependent_packages":1,"readme":"pyrcel: cloud parcel model\n==========================\n\n![sample parcel model run](docs/figs/model_example.png)\n\n[![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.io/en/latest/index.html)\n\n\nThis is an implementation of a simple, adiabatic cloud parcel model for use in\naerosol-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\n and changes over [Nenes et al (2001)][nenes2001]:\n\n* Implementation of κ-Köhler theory for condensation physics ([Petters and\nKreidenweis, 2007)][pk2007]\n* Extension of model to handle arbitrary sectional representations of aerosol\npopulations, based on user-controlled empirical or parameterized size distributions\n* Improved, modular numerical framework for integrating the model, including bindings\nto several different stiff integrators:\n    - ~~`lsoda` - [scipy ODEINT wrapper](http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.odeint.html)~~\n    - ~~`vode, lsode*, lsoda*` - ODEPACK via [odespy][hplgit]~~\n    - `cvode` - SUNDIALS via [Assimulo](http://www.jmodelica.org/assimulo_home/index.html#)\n\namong 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.\n\n\u003e [!WARNING]\n\u003e As of version 1.3, we no longer support any ODE solver backends other than `cvode`.\n\u003e All publications using this model have used this backend, so users shouldn't expect\n\u003e any inconsistencies with historical results. A future version is planned to add a new\n\u003e suite of ODE solvers from the [diffrax][diffrax] toolkit.\n\nUpdated 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).\n\n[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.\n\nQuick Start\n-----------\n\nAs of February, 2025, we provide an ultra simple way to run `pyrcel` without any installation\nor setup using [`pixi`](https://pixi.sh/latest/).\n`pixi` is an all-in-one package management tool that makes handling complex environment\nsetup and dependencies extremely easy.\n\nClone or download this repo, then **cd** into the top-level folder from a terminal.\nFrom there, execute:\n\n``` shell\n$ pixi run run_parcel examples/simple.yml\n```\n\nThis will automatically prepare an environment with all of `pyrcel`'s dependencies installed,\nand then run an example model setup.\nThe first time the model runs, it may take a few second after invoking the script; this is\nnormal, and is just a side-effect of `numba` caching and pre-compiling some of the functions\nused to drive the parcel model simulation.\n\n\u003e [!NOTE]\n\u003e We provide `pixi` environments for Linux, MacOS (both Intel and Apple Silicon) and\n\u003e Windows, but we have never tried to run the model on a Windows computer so your mileage\n\u003e may vary. Contact the authors if you have any questions and we can try to support your\n\u003e use case.\n\nInstallation\n------------\n\nTo get started with using `pyrcel`, complete the following steps:\n\n1. Set up a new Python environment; we recommend using [mambaforge](https://conda-forge.org/miniforge/):\n  \n``` shell\n  $ mamba create -n pyrcel_quick_start python=3.11\n```\n\n2. 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:\n  \n``` shell\n  $ mamba activate pyrcel_quick_start\n  $ pip install pyrcel\n  $ mamba install -c conda-forge assimulo\n```\n\n3. 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):\n  \n``` shell\n  $ run_parcel simple.yml\n```\n\n* Visualize the output NetCDF (should be in the directory you ran the CLI tool, at **output/simple.nc**)\n\nThat's it! You should be able to import `pyrcel` into any script or program running in the\nenvironment you created.\n\n\nRequirements\n------------\n\n**Required**\n\n* Python \u003e= 3.8\n* [numba](http://numba.pydata.org)\n* [NumPy](http://www.numpy.org)\n* [SciPy](http://www.scipy.org)\n* [pandas](http://pandas.pydata.org)\n* [xarray](http://xarray.pydata.org/en/stable/)\n* [PyYAML](http://pyyaml.org/)\n\nAdditionally, the following packages are used for better numerics (ODE solving)\n\n* [Assimulo](http://www.jmodelica.org/assimulo)\n\nThe easiest way to satisfy the basic requirements for building and running the\nmodel is to use the [Anaconda](http://continuum.io/downloads) scientific Python\ndistribution. Alternatively, a\n[miniconda environment](http://conda.pydata.org/docs/using/envs.html) is\nprovided to quickly set-up and get running the model. Assimulo's dependency on\nthe SUNDIALS library makes it a little bit tougher to install in an automated\nfashion, so it has not been included in the automatic setup provided here; you\nshould refer to [Assimulo's documentation](http://www.jmodelica.org/assimulo_home/installation.html)\nfor more information on its installation process. Note that many components of\nthe model and package can be used without Assimulo.\n\nDevelopment\n-----------\n\n[http://github.com/darothen/pyrcel]()\n\nPlease fork this repository if you intend to develop the model further so that the\ncode's provenance can be maintained.\n\nLicense / Usage\n---------------\n\n[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).\n\nYou are free to use this code however you would like.\nIf you use this for any scientific work resulting in a publication or citation, please\ncite our original publication detailing the model, and let the authors know:\n\n```\n@article { \n      author = \"Daniel Rothenberg and Chien Wang\",\n      title = \"Metamodeling of Droplet Activation for Global Climate Models\",\n      journal = \"Journal of the Atmospheric Sciences\",\n      year = \"2016\",\n      publisher = \"American Meteorological Society\",\n      address = \"Boston MA, USA\",\n      volume = \"73\",\n      number = \"3\",\n      doi = \"10.1175/JAS-D-15-0223.1\",\n      pages= \"1255 - 1272\",\n      url = \"https://journals.ametsoc.org/view/journals/atsc/73/3/jas-d-15-0223.1.xml\"\n}\n```\n\n\n[author_email]: mailto:daniel@danielrothenberg.com\n[nenes2001]: http://nenes.eas.gatech.edu/Preprints/KinLimitations_TellusPP.pdf\n[pk2007]: http://www.atmos-chem-phys.net/7/1961/2007/acp-7-1961-2007.html\n[hplgit]: https://github.com/hplgit/odespy\n[diffrax]: https://docs.kidger.site/diffrax/\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["optimize","archiving","transforms","measur","generic","observation","compose","conversion","projection","animals"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/123985","html_url":"https://ost.ecosyste.ms/projects/123985"}