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CMIP5 scientific gaps and recommendations for CMIP6

MPG-Autoren
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Stevens,  Björn
Director’s Research Group AES, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Zitation

Stouffer, R. J., Eyring, V., Meehl, G. A., Bony, S., Senior, C., Stevens, B., et al. (2017). CMIP5 scientific gaps and recommendations for CMIP6. Bulletin of the American Meteorological Society, 98, 95-105. doi:10.1175/BAMS-D-15-00013.1.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0028-4BB6-B
Zusammenfassung
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: How does the Earth system respond to changes in forcing? What are the origins and consequences of systematic model biases? 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. 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.