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Title: CMIP5 Scientific Gaps and Recommendations for CMIP6

Abstract

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP, that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases thatmore » appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States). Geophysical Fluid Dynamics Lab.
  2. German Aerospace Center (DLR), Oberpfaffenhofen (Germany). Inst. of Atmospheric Physics
  3. National Center for Atmospheric Research, Boulder, CO (United States)
  4. Centre National de la Recherche Scientifique (CNRS), Paris (France). Lab. de Meteorologie Dynamique, IPSL
  5. Met Office Hadley Centre, Exeter (United Kingdom)
  6. Max-Planck-Inst. for Meteorology, Hamburg (Germany)
  7. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Program for Climate Model Diagnosis and Intercomparison
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Contributing Org.:
French CNRS; German Ministry of Education and Research (BMBF); Max Planck Society
OSTI Identifier:
1377777
Report Number(s):
LLNL-JRNL-698186
Journal ID: ISSN 0003-0007
Grant/Contract Number:
AC52-07NA27344; FC02-97ER62402; GA01101; ANR-10-LABX-0018
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 98; Journal Issue: 1; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

Stouffer, R. J., Eyring, V., Meehl, G. A., Bony, S., Senior, C., Stevens, B., and Taylor, K. E.. CMIP5 Scientific Gaps and Recommendations for CMIP6. United States: N. p., 2017. Web. doi:10.1175/BAMS-D-15-00013.1.
Stouffer, R. J., Eyring, V., Meehl, G. A., Bony, S., Senior, C., Stevens, B., & Taylor, K. E.. CMIP5 Scientific Gaps and Recommendations for CMIP6. United States. doi:10.1175/BAMS-D-15-00013.1.
Stouffer, R. J., Eyring, V., Meehl, G. A., Bony, S., Senior, C., Stevens, B., and Taylor, K. E.. Mon . "CMIP5 Scientific Gaps and Recommendations for CMIP6". United States. doi:10.1175/BAMS-D-15-00013.1. https://www.osti.gov/servlets/purl/1377777.
@article{osti_1377777,
title = {CMIP5 Scientific Gaps and Recommendations for CMIP6},
author = {Stouffer, R. J. and Eyring, V. and Meehl, G. A. and Bony, S. and Senior, C. and Stevens, B. and Taylor, K. E.},
abstractNote = {The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP, that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.},
doi = {10.1175/BAMS-D-15-00013.1},
journal = {Bulletin of the American Meteorological Society},
number = 1,
volume = 98,
place = {United States},
year = {Mon Jan 23 00:00:00 EST 2017},
month = {Mon Jan 23 00:00:00 EST 2017}
}

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  • The usefulness of previous Coupled Model Intercomparison Project (CMIP) exercises has been hampered by a lack of radiative forcing information. This has made it difficult to understand reasons for differences between model responses. Effective radiative forcing (ERF) is easier to diagnose than traditional radiative forcing in global climate models (GCMs) and is more representative of the eventual temperature response. Here we examine the different methods of computing ERF in two GCMs. We find that ERF computed from a fixed sea surface temperature (SST) method (ERF_fSST) has much more certainty than regression based methods. Thirty year integrations are sufficient to reducemore » the 5–95% confidence interval in global ERF_fSST to 0.1Wm ~2. For 2xCO2 ERF, 30 year integrations are needed to ensure that the signal is larger than the local confidence interval over more than 90% of the globe. Within the ERF_fSST method there are various options for prescribing SSTs and sea ice. We explore these and find that ERF is only weakly dependent on the methodological choices. Prescribing the monthly averaged seasonally varying model’s preindustrial climatology is recommended for its smaller random error and easier implementation. As part of CMIP6, the Radiative Forcing Model Intercomparison Project (RFMIP) asks models to conduct 30 year ERF_fSST experiments using the model’s own preindustrial climatology of SST and sea ice. The Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) will also mainly use this approach. Lastly, we propose this as a standard method for diagnosing ERF and recommend that it be used across the climate modeling community to aid future comparisons.« less
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