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Title: High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Journal Article · · Geoscientific Model Development (Online)
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  1. United Kingdom Meteorological Office, Exeter, Devon (United Kingdom)
  2. Stony Brook Univ., NY (United States)
  3. Chinese Academy of Sciences (CAS), Beijing (China)
  4. Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
  5. Columbia Univ., Palisades, NY (United States). Lamont-Doherty Earth Observatory
  6. Ouranos, Montreal, QC (Canada)
  7. Texas A & M Univ., College Station, TX (United States)
  8. National Taiwan Normal Univ., Taipei (Taiwan)
  9. Univ. of Oxford (United Kingdom)
  10. National Centre for Atmospheric Research (NCAR), Boulder, CO (United States)
  11. Helmholtz Centre for Ocean Research Kiel (GEOMAR) (Germany)
  12. Univ. of Hamburg (Germany)
  13. Japan Agency for Marine-Earth Science and Technology, Yokohama (Japan)
  14. Seoul National Univ. (Korea, Republic of)
  15. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
  16. Meteorological Research Inst. (MRI), Tsukuba (Japan)
  17. National Institute for Space Research, São José dos Campos (Brazil)
  18. Euro-Mediterranean Center on Climate Change (CMCC), Bologna (Italy)
  19. Univ. of Brest (France). Laboratoire d'Océanographie Physique et Spatiale (LOPS); CNRS, IRD, Ifremer, IUEM, Brest (France)
  20. Academia Sinica, Taipei (Taiwan)
  21. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
  22. Univ. of Reading (United Kingdom)
  23. Pennsylvania State Univ., University Park, PA (United States)
  24. Princeton Univ., NJ (United States)
  25. Utah State Univ., Logan, UT (United States)
  26. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States)

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
Academia Sinica; DSIT; European Commission (EC); JSPS KAKENHI; Japan Society for the Promotion of Science (JSPS); Ministry of Education, Culture, Sports, Science and Technology (MEXT); Ministry of Science and ICT (MSIT); National Academies of Science and Engineering Gulf Research Program; National Academy of Sciences (NAS); National Aeronautics and Space Administration (NASA); National Institute for Health and Care Research (NIHR); National Key Research and Development Program of China; National Oceanic and Atmospheric Administration (NOAA); National Science Foundation (NSF); National Science and Technology Council (NSTC); Natural Environment Research Council (NERC); U.S. Geological Survey (USGS); UK government's Horizon Europe; USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science (BSS); Utah Department of Natural Resources
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830; AC52-07NA27344; SC0016605; SC0023333
OSTI ID:
2526259
Report Number(s):
PNNL-SA--208707
Journal Information:
Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Journal Issue: 4 Vol. 18; ISSN 1991-9603
Publisher:
Copernicus Publications, EGUCopyright Statement
Country of Publication:
United States
Language:
English

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