Simple superparameterization example in Python using the DALES model
This is a simplified superparameterization setup, where the global model consists of only advection. The purpose of this example is showing a lack of cloud advection in a superparameterized model, and exploring schemes to improve cloud advection by adjusting the small-scale variability of the total humidity in the local models.
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Install OMUSE (recommended in a virtual environment) and the DALES model within OMUSE. See the OMUSE installation instructions
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Other requirements: scipy, matplotlib, netCDF4 (
pip install netCDF4) -
Activate the OMUSE virtual environment
python simple-SP.py # run simulations, 10 minutes on 4-core desktop
python plot-lwp.py # plot result
(Instructions tested on Ubuntu 21.04, with OMUSE 2021.6.2.dev14+gf2bbc23).
The script is set up to perform three simulations with a moist bubble perturbation in the initial state:
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a single, wide LES
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a traditional superparameterization with four LES domains
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a modified superparameterization with four LES domains, where the moisture variability is coupled
DALES model description article: Formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES) and overview of its applications, T. Heus et al, Geosci. Model Dev., 3, 415-444, 2010
Superparamerization of OpenIFS with DALES: code repository, article: Regional Superparameterization in a Global Circulation Model Using Large Eddy Simulations, F. Jansson et al, Journal of Advances in Modeling Earth Systems, 11, 2958– 2979.