Abstract
The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts, perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.
| Original language | English |
|---|---|
| Pages (from-to) | 2377-2411 |
| Number of pages | 35 |
| Journal | Journal of Advances in Modeling Earth Systems |
| Volume | 11 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 1 2019 |
Funding
Phil Rasch and Shaocheng Xie co-led the model development team of over most of its development cycle, with help from Steve Klein and Peter Caldwell during early stages of the project. Many members of the DOE leadership and scientific community influenced the model evolution through formal and informal conversations about model characteristics, strengths, deficiencies, and opportunities for improvement. We are also grateful to many members of the CESM team (particularly the Atmospheric Model Working Group, the Software Engineering Working Group, and Bill Large) for their collaboration as E3SM made the transition to an independent modeling activity, and we continue to appreciate and benefit from discussions with that team. Special thanks to Michael Brunke, Bill Collins, Andrew Gettelman, Michael Prather, Steve Smith, Guang Zhang, Minghua Zhang, and Xubin Zeng for their insight about the model, parameterizations, simulations, input fields that drive the model and discussions of opportunities for improvement. This research was supported as part of the Energy Exascale Earth System Model (E3SM) project (doi:10.11578/E3SM/dc.20180418.36), funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. The E3SM model code and input data are available at https://e3sm.org. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under contract DE-AC02-05CH11231; the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357; the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC05-00OR22725; a high-performance computing cluster provided by the BER Earth System Modeling program and operated by the Laboratory Computing Resource Center at Argonne National Laboratory; The Pacific Northwest National Laboratory Institutional Computing (PIC) program. Work at LLNL was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Sandia National Laboratories is a multimission laboratory managed and operated by NTESS, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. The Pacific Northwest National Laboratory is operated for the U.S. DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. J.-H. Yoon was supported by National Research Foundation Grant NRF_2017R1A2b4007480.
| Funders | Funder number |
|---|---|
| Argonne Leadership Computing Facility | |
| Laboratory Computing Resource Center | |
| National Research Foundation | NRF_2017R1A2b4007480 |
| Office of Biological and Environmental Research | |
| Software Engineering Working Group | |
| U.S. Department of Energy Office of Science | DE-AC02-05CH11231 |
| U.S. Department of Energy | |
| Battelle | DE-AC05-76RL01830 |
| Office of Science | |
| National Nuclear Security Administration | DE-NA0003525 |
| Biological and Environmental Research | |
| Argonne National Laboratory | DE-AC05-00OR22725, DE-AC02-06CH11357 |
| Lawrence Livermore National Laboratory | DE-AC52-07NA27344 |
Keywords
- Earth system
- atmospheric model
- climate
- climate change
- climate modeling
- general circulation modeling