Articles | Volume 15, issue 9
Geosci. Model Dev., 15, 3879–3899, 2022
https://doi.org/10.5194/gmd-15-3879-2022
Geosci. Model Dev., 15, 3879–3899, 2022
https://doi.org/10.5194/gmd-15-3879-2022
Development and technical paper
13 May 2022
Development and technical paper | 13 May 2022

On numerical broadening of particle-size spectra: a condensational growth study using PyMPDATA 1.0

Michael A. Olesik et al.

Model code and software

PyMPDATA 1.0 Piotr Bartman, Jakub Banaśkiewicz, Szymon Drenda, Maciej Manna, Michael A. Olesik, Paweł Rozwoda, Michał Sadowski, and Sylwester Arabas. https://doi.org/10.5281/zenodo.6329303

PyMPDATA-examples 1.0.1 Piotr Bartman, Jakub Banaśkiewicz, Szymon Drenda, Maciej Manna, Michael A. Olesik, Paweł Rozwoda, Michał Sadowski, and Sylwester Arabas https://doi.org/10.5281/zenodo.6471494

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Short summary
In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.