Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 9
Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3879-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-3879-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 9
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, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas

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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.
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