The Python package enstools-freda provides a very easy-to-use framework for
the development of new data assimilation algorithms. New algorithms are
implemented as plugins, often in a few lines of code, and can be easily
exchanged. In the best case, this takes the form of a single Python function,
which only describes the actual mathematical implementation of the algorithm.
The framework covers the rest, including parallelization, data handling, and
I/O. Ensemble square root and Kalman filters (EnSRF, EnKF) have been
implemented as a first step.
FREDA is developed within Waves to Weather - Transregional Collaborative Research Project (SFB/TRR165).
mamba is the easiest way to install enstools-freda along with all dependencies.
./venv-setup-mamba.sh
The directory examples contains a Jupyter Notebook that illustrates the functionality.
FREDA (enstools-freda) is a collaborative development of the subprojects
B6 and
Z2 within
Waves to Weather (SFB/TRR165). The development has been funded by the
German Research Foundation (DFG).
The code is released under an Apache-2.0 licence.