ERF is built upon the AMReX software framework for massively parallel block-structured applications.
| Regression Tests |  |
See Getting Started for instructions as to how to clone the ERF and AMReX codes, and for how to build and run an ERF example. Minimum requirements for system software are also given there.
Python tools for pre- and post-processing ERF can be found in the companion erftools repository.
Documentation of the ERF theory and implementation is available here.
In addition, there is doxygen documentation of the ERF Code available here.
See CONTRIBUTING.md for how to contribute to ERF development.
The development of the Energy Research and Forecasting (ERF) code is funded by the U.S. Department of Energy (DOE).
ERF is built on the AMReX library.
The license for ERF can be found at [LICENSE.md](LICENSE.md).
To cite ERF, please see the following publications:
@article{ERF_JOSS,
title = {ERF: Energy Research and Forecasting},
journal = {Journal of Open Source Software},
author = {Ann Almgren and Aaron Lattanzi and Riyaz Haque and Pankaj Jha and Branko Kosovic and Jeffrey Mirocha and Bruce Perry and Eliot Quon and Michael Sanders and David Wiersema and Donald Willcox and Xingqiu Yuan and Weiqun Zhang},
doi = {10.21105/joss.05202},
url = {https://doi.org/10.21105/joss.05202},
year = {2023},
publisher = {The Open Journal of Open Source Software},
volume = {8},
number = {87},
pages = {5202},
}
@article{ERF_JAMES,
author = {Lattanzi, Aaron and Almgren, Ann and Quon, Eliot and Natarajan, Mahesh and Kosovic, Branko and Mirocha, Jeffrey and Perry, Bruce and Wiersema, David and Willcox, Donald and Yuan, Xingqiu and Zhang, Weiqun},
title = {ERF: Energy Research and Forecasting Model},
journal = {Journal of Advances in Modeling Earth Systems},
volume = {17},
number = {11},
pages = {e2024MS004884},
doi = {https://doi.org/10.1029/2024MS004884},
year = {2025}
}