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Title: The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale

Abstract

Many think that the time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain ofmore » processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms).« less

Authors:
 [1];  [2];  [1];  [1];  [3];  [1];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [1];  [11];  [12];  [13];  [2];  [14];  [15] more »;  [16] « less
  1. Met Office, Exeter (United Kingdom)
  2. Univ. of Reading, Reading (United Kingdom). National Centre for Atmospheric Science
  3. Univ. of Exeter, Exeter (United Kingdom)
  4. Texas A & M Univ., College Station, TX (United States). Dept. of Oceanography
  5. Univ. of Oxford (United Kingdom). Atmospheric, Oceanic and Planetary Physics
  6. Alfred Wegener Inst., Hemholtz for Polar and Marine Research, Bremerhaven (Germany)
  7. Univ. of Reading, Reading (United Kingdom). National Centre for Atmospheric Science; Univ. of Bern (Switzerland). Center for Space and Habitability
  8. NOAA/GFDL, Princeton, NJ (United States)
  9. Royal Netherlands Meteorological Institute, De Bilt, (Netherlands)
  10. Alfred Wegener Inst., Hemholtz for Polar and Marine Research, Bremerhaven (Germany); Univ. of Bremen, Bremen (Germany). Department of Physics and Electrical Engineering
  11. Hokkaido Univ., Sapporo (Japan). Div. of Earth and Planetary Sciences, Faculty of Science
  12. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Div.
  13. Univ. of Tokyo (Japan). Atmosphere and Ocean Research Inst.
  14. Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna (Italy)
  15. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA (United States); Met Office, Exeter (United Kingdom); Univ. of Reading, Reading (United Kingdom). National Centre for Atmospheric Science
  16. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Div
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1526546
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 99; Journal Issue: 11; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES

Citation Formats

Roberts, M. J., Vidale, P. L., Senior, C., Hewitt, H. T., Bates, C., Berthou, S., Chang, P., Christensen, H. M., Danilov, S., Demory, M. -E., Griffies, S. M., Haarsma, R., Jung, T., Martin, G., Minobe, S., Ringler, T., Satoh, M., Schiemann, R., Scoccimarro, E., Stephens, G., and Wehner, M. F. The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale. United States: N. p., 2018. Web. doi:10.1175/BAMS-D-15-00320.1.
Roberts, M. J., Vidale, P. L., Senior, C., Hewitt, H. T., Bates, C., Berthou, S., Chang, P., Christensen, H. M., Danilov, S., Demory, M. -E., Griffies, S. M., Haarsma, R., Jung, T., Martin, G., Minobe, S., Ringler, T., Satoh, M., Schiemann, R., Scoccimarro, E., Stephens, G., & Wehner, M. F. The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale. United States. doi:10.1175/BAMS-D-15-00320.1.
Roberts, M. J., Vidale, P. L., Senior, C., Hewitt, H. T., Bates, C., Berthou, S., Chang, P., Christensen, H. M., Danilov, S., Demory, M. -E., Griffies, S. M., Haarsma, R., Jung, T., Martin, G., Minobe, S., Ringler, T., Satoh, M., Schiemann, R., Scoccimarro, E., Stephens, G., and Wehner, M. F. Tue . "The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale". United States. doi:10.1175/BAMS-D-15-00320.1. https://www.osti.gov/servlets/purl/1526546.
@article{osti_1526546,
title = {The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale},
author = {Roberts, M. J. and Vidale, P. L. and Senior, C. and Hewitt, H. T. and Bates, C. and Berthou, S. and Chang, P. and Christensen, H. M. and Danilov, S. and Demory, M. -E. and Griffies, S. M. and Haarsma, R. and Jung, T. and Martin, G. and Minobe, S. and Ringler, T. and Satoh, M. and Schiemann, R. and Scoccimarro, E. and Stephens, G. and Wehner, M. F.},
abstractNote = {Many think that the time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain of processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms).},
doi = {10.1175/BAMS-D-15-00320.1},
journal = {Bulletin of the American Meteorological Society},
number = 11,
volume = 99,
place = {United States},
year = {2018},
month = {12}
}

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