ERF: Energy Research and Forecasting: Article No. 5202

Ann Almgren, Aaron Lattanzi, Riyaz Haque, Pankaj Jha, Branko Kosovic, Jeffrey Mirocha, Bruce Perry, Eliot Quon, Michael Sanders, David Wiersema, Donald Willcox, Xingqiu Yuan, Weiqun Zhang

Research output: Contribution to journalArticlepeer-review


The Energy Research and Forecasting (ERF) code is a new model that simulates the mesoscale and microscale dynamics of the atmosphere using the latest high-performance computing architectures. It employs hierarchical parallelism using an MPI+X model, where X may be OpenMP on multicore CPU-only systems, or CUDA, HIP, or SYCL on GPU-accelerated systems. ERF is built on AMReX (Zhang et al., 2019, 2021), a block-structured adaptive mesh refinement (AMR) software framework that provides the underlying performance-portable software infrastructure for block-structured mesh operations. The "energy" aspect of ERF indicates that the software has been developed with renewable energy applications in mind. In addition to being a numerical weather prediction model, ERF is designed to provide a flexible computational framework for the exploration and investigation of different physics parameterizations and numerical strategies, and to characterize the flow field that impacts the ability of wind turbines to extract wind energy. The ERF development is part of a broader effort led by the US Department of Energy's Wind Energy Technologies Office.
Original languageAmerican English
Number of pages4
JournalJournal of Open Source Software
Issue number87
StatePublished - 2023

NREL Publication Number

  • NREL/JA-5000-85388


  • atmospheric modeling
  • C++
  • mesoscale
  • microscale
  • wind energy


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