Skip to content
This repository was archived by the owner on Jul 29, 2024. It is now read-only.
/ pycles Public archive

A python based infrastructure for cloud large eddy simulation.

License

Notifications You must be signed in to change notification settings

pressel/pycles

Folders and files

NameName
Last commit message
Last commit date

Latest commit

df39365 · Mar 15, 2019
Apr 14, 2016
Mar 23, 2018
Aug 27, 2015
May 10, 2016
Mar 23, 2018
Feb 21, 2018
Mar 23, 2018
Sep 17, 2015
Mar 15, 2019
Feb 23, 2016
Feb 24, 2016
May 2, 2016
Oct 12, 2016
Aug 7, 2017
Mar 23, 2018
Aug 28, 2015
Aug 27, 2015
Mar 23, 2018
Mar 23, 2018
Oct 13, 2015
Feb 9, 2016
Jul 31, 2015
Mar 23, 2018
Sep 3, 2015
Sep 7, 2015
Jul 31, 2015
Jan 24, 2018
Sep 4, 2015
Mar 23, 2018
Mar 23, 2018
Mar 23, 2018
Mar 23, 2018
Oct 28, 2015
Mar 23, 2018
Sep 21, 2015
Aug 7, 2017
Jul 28, 2017
Mar 23, 2018
Feb 9, 2016
Feb 9, 2016
Aug 24, 2015
Jan 20, 2016
Aug 24, 2015
Sep 4, 2015
Aug 24, 2015
Aug 7, 2017
Aug 7, 2017
Aug 7, 2017
Feb 16, 2018
Mar 23, 2018
Mar 23, 2018
Mar 23, 2018
Mar 19, 2018
Apr 19, 2016
Mar 23, 2018
Apr 27, 2016
Aug 7, 2017
Mar 23, 2018
Mar 23, 2018
Sep 10, 2015
Aug 7, 2017
Jul 31, 2015
Aug 7, 2018
Aug 24, 2015
Oct 13, 2015
Mar 23, 2018
Mar 23, 2018
Nov 18, 2016
Nov 18, 2016
May 4, 2016
Jun 5, 2017
Mar 23, 2018
Mar 23, 2018
Sep 7, 2015
Jan 24, 2018
Dec 4, 2015
Mar 23, 2018
Oct 15, 2015
Feb 10, 2016
Aug 7, 2018
Aug 7, 2018
Nov 9, 2015
Nov 18, 2015
Jan 24, 2018
Nov 16, 2016
Aug 7, 2018
Mar 23, 2018
Mar 23, 2018
Aug 27, 2015
Mar 23, 2018
Mar 23, 2018
Aug 27, 2015
Sep 24, 2018
Jan 24, 2018
Sep 10, 2015

Repository files navigation

Python Cloud Large Eddy Simulation, or PyCLES (pronounced pickles), is a massively parallel anelastic atmospheric large eddy simulation infrastructure designed to simulate boundary layer clouds and deep convection. PyCLES is written in Python, Cython, and C. It was primarily developed by Kyle Pressel and Colleen Kaul as part of the Climate Dynamics Group at both the California Institute of Technology and ETH Zurich.

The model formulation is describe in detail in:

Pressel, K. G., C. M. Kaul, T. Schneider, Z. Tan, and S. Mishra, 2015: Large-eddy simulation in an anelastic framework with closed water and entropy balances. Journal of Advances in Modeling Earth Systems, 7, 1425–1456, doi:10.1002/2015MS000496.

PyCLES Related Publications:

Zhang, X., T. Schneider, and C. M. Kaul, 2018: Arctic mixed-phase clouds in large-eddy simulations and a mixed-layer model. Journal of Advances in Modeling Earth Systems, submitted. PDF

Tan, Z., C. M. Kaul, K. G. Pressel, Y. Cohen, T. Schneider, and J. Teixeira, 2018: An extended eddy-diffusivity mass-flux scheme for unified representation of subgrid-scale turbulence and convection. Journal of Advances in Modeling Earth Systems, In Press. Early Release

Pressel, K. G., S. Mishra, T. Schneider, C. M. Kaul, Z. Tan, 2017: Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds. Journal of Advances in Modeling Earth Systems, 9, 1342-1365, doi:10.1002/2016MS000778.

Tan, Z., T. Schneider, J. Teixeira, and K. G. Pressel, 2017: Large-eddy simulation of subtropical cloud-topped boundary layers: 2. Cloud response to climate change. Journal of Advances in Modeling Earth Systems, 9, 19-38, doi:10.1002/2016MS000804.

Schneider, T., J. Teixeira, C. S. Bretherton, F. Brient, K. G. Pressel, C. Schär, and A. P. Siebesma, 2017: Climate goals and computing the future of clouds. Nature Climate Change, 7, 3-5, doi:10.1038/nclimate3190.

Tan, Z., T. Schneider, J. Teixeira, and K. G. Pressel, 2016: Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance. Journal of Advances in Modeling Earth Systems, 8, 1565-1585, doi:10.1002/2016MS000655.

Pressel, K. G., C. M. Kaul, T. Schneider, Z. Tan, and S. Mishra, 2015: Large-eddy simulation in an anelastic framework with closed water and entropy balances. Journal of Advances in Modeling Earth Systems, 7, 1425–1456, doi:10.1002/2015MS000496.

Ait-Chaalal, F., T. Schneider, B. Meyer, and B. Marston, 2016: Cumulant expansions for atmospheric flows. New Journal of Physics, 18, 025019, doi:10.1088/1367-2630/18/2/025019.

About

A python based infrastructure for cloud large eddy simulation.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published