TY - JOUR
T1 - A Python interface to the Dutch Atmospheric Large-Eddy Simulation
AU - van den Oord, Gijs
AU - Jansson, Fredrik
AU - Pelupessy, Inti
AU - Chertova, Maria
AU - Grönqvist, Johanna H.
AU - Siebesma, Pier
AU - Crommelin, Daan
PY - 2020
Y1 - 2020
N2 - We present a Python interface for the Dutch Atmospheric Large Eddy Simulation (DALES), an existing Fortran code for high-resolution, turbulence-resolving simulation of atmospheric physics. The interface is based on an infrastructure for remote and parallel function calls and makes it possible to use and control the DALES weather simulations from a Python context. The interface is designed within the OMUSE framework, and allows the user to set up and control the simulation, apply perturbations and forcings, collect and analyse data in real time without exposing the user to the details of setting up and running the parallel Fortran DALES code. Another significant possibility is coupling the DALES simulation to other models, for example larger scale numerical weather prediction (NWP) models that can supply realistic lateral boundary conditions. Finally, the Python interface to DALES can serve as an educational tool for exploring weather dynamics, which we demonstrate with an example Jupyter notebook.
AB - We present a Python interface for the Dutch Atmospheric Large Eddy Simulation (DALES), an existing Fortran code for high-resolution, turbulence-resolving simulation of atmospheric physics. The interface is based on an infrastructure for remote and parallel function calls and makes it possible to use and control the DALES weather simulations from a Python context. The interface is designed within the OMUSE framework, and allows the user to set up and control the simulation, apply perturbations and forcings, collect and analyse data in real time without exposing the user to the details of setting up and running the parallel Fortran DALES code. Another significant possibility is coupling the DALES simulation to other models, for example larger scale numerical weather prediction (NWP) models that can supply realistic lateral boundary conditions. Finally, the Python interface to DALES can serve as an educational tool for exploring weather dynamics, which we demonstrate with an example Jupyter notebook.
KW - Atmospheric sciences
KW - Large-eddy simulation
UR - http://www.scopus.com/inward/record.url?scp=85092293694&partnerID=8YFLogxK
U2 - 10.1016/j.softx.2020.100608
DO - 10.1016/j.softx.2020.100608
M3 - Article
AN - SCOPUS:85092293694
VL - 12
SP - 1
EP - 6
JO - SoftwareX
JF - SoftwareX
SN - 2352-7110
M1 - 100608
ER -