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Emergence of an equatorial mode of
climate variability in the Indian Ocean
under altered mean states
Martin Puy1, P. DiNezio1, Kaustubh Thirumalai2
CVCWG Winter Meeting February 27th, 2019
1U. of Texas Institute for Geophysics, 2Brown University
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An Indian Ocean El Niño
Martin Puy1, P. DiNezio1, Kaustubh Thirumalai2
CVCWG Winter Meeting February 27th, 2019
1U. of Texas Institute for Geophysics, 2Brown University
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Last Glacial Maximum Future
Past and future mean states
conducive for stronger variability in
the IO?
CMIP5RCP8.5 scenario
Multi-model mean
CESM1
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CMIP5 projections supported by
historical observations
SST change1980-2017 epoch minus 1901-1950 epoch
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Both mean states are conducive for
stronger equatorial SST variability
Change in SST variabilityJuly-August-September
CESM1LGM
CMIP5RCP8.5 scenario
Multi-model mean
Last Glacial Maximum Future
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Change in surface wind stress along the
equator
Change in
SST
variability in
the EEIO
Consistent link between changes in mean
state and variability among models
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Additional LGM simulations:
• ENSO disabled
• ENSO and IOD disabled
Restored to
climatology
Restored
to
climatolog
y
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Restored to
climatology
Equatorial variability independent from ENSO and IOD
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Dynamics of equatorial mode
resembling El Niño
Precursor
April-May-JuneEvent peak
July-August-
September
Composite event based on peak SSTA over the eastern
equatorial IO from CESM1 LGM run with ENDO and IOD
disabled
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Equatorial mode currently inactive
Precursor
April-May-JuneEvent peak
July-August-
September
Composite event based on western IO zonal wind precursor
from ERA40 reanalysis. Thermocline depth anomalies from
ORAS4 ocean reanalysis.
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Equatorial mode also active under
greenhouse warming
Precursor
April-May-JuneEvent peak
July-August-
September
Composite event based on western IO zonal wind precursor in
RCP8.5 climate (2050-2100) from a subset of CMIP5 models.
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Rainfall impacts
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• Indian ocean capable of stronger SST
variability,
• Associated with an equatorial mode
resembling the Pacific El Niño:
– Triggered by wind precursor in the western
IO,
–Communicated to eastern IO via Kelvin
waves,
–Amplified by a favorable mean state with
equatorial upwelling and shallow
thermocline.
Conclusions
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Pattern of warming explains
rainfall predictions
Multi-model prediction for year
2100
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Zheng et. al 2013
Large uncertainty
among models
Shading shows
spread among
models
West
warms
faster
West and
East warm
at the
same rate
SST difference
West minus East
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Zheng et. al 2013
Large uncertainty among models
Shading shows one
standard deviation of inter-
model spread.
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Large
uncertainty in
variability
change
Zheng et. al 2013
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Spatio-temporal evolution of equatorial mode
resembles El Niño
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Seasonally reversing winds along the
equator
January-February-
March
July-August-September
ERA interim (1980-
2014)
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Saji et al. 1999
Strong air-sea coupling and SST variability
restricted to the SE Indian Ocean
May-June September-October
Precursor Peak