Articles | Volume 16, issue 5
https://doi.org/10.5194/cp-16-1777-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-16-1777-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models
Josephine R. Brown
CORRESPONDING AUTHOR
School of Earth Sciences, University of Melbourne, Parkville, VIC, Australia
Chris M. Brierley
Department of Geography, University College London, London, UK
Soon-Il An
Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
Maria-Vittoria Guarino
British Antarctic Survey, High Cross, Madingley Road, Cambridge, UK
Samantha Stevenson
Bren School of Environmental Sciences and Management, University of California, Santa Barbara, CA, USA
Charles J. R. Williams
School of Geographical Sciences, University of Bristol, University Road, Bristol, UK
Department of Meteorology, University of Reading, Earley Gate, P.O. Box 243, Reading, UK
Qiong Zhang
Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
Anni Zhao
Department of Geography, University College London, London, UK
Ayako Abe-Ouchi
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
Pascale Braconnot
Laboratoire des Sciences du Climat et de l'Environnement–IPSL, unite mixte CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Esther C. Brady
National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO, USA
Deepak Chandan
Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, Canada
Roberta D'Agostino
Max-Planck-Institut für Meteorologie, Bundesstrasse 53, Hamburg, Germany
Chuncheng Guo
NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
Allegra N. LeGrande
NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY, USA
Gerrit Lohmann
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bussestr. 24, Bremerhaven, Germany
Polina A. Morozova
Institute of Geography Russian Academy of Sciences, Staromonetny L. 29, Moscow, Russia
Rumi Ohgaito
Japan Agency for Marine-Earth Science and Technology, 3173-25 Showamachi, Kanazawa-ward, Yokohama, Japan
Ryouta O'ishi
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
Bette L. Otto-Bliesner
National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO, USA
W. Richard Peltier
Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, Canada
Xiaoxu Shi
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bussestr. 24, Bremerhaven, Germany
Louise Sime
British Antarctic Survey, High Cross, Madingley Road, Cambridge, UK
Evgeny M. Volodin
Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow, Russia
Zhongshi Zhang
British Antarctic Survey, High Cross, Madingley Road, Cambridge, UK
Department of Atmospheric Science, School of Environmental studies, China University of Geoscience, Wuhan, China
Weipeng Zheng
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
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Discussed (final revised paper)
Latest update: 09 Oct 2024
Short summary
El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the...