Transcript The Indian monsoon and climate change

10-11 December 2007, Park Inn Hotel, York
The Indian monsoon and climate
change
Andrew Turner, Julia Slingo & Pete Inness
NCAS-Climate
Walker Institute for Climate System
Research, University of Reading
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Introduction
Indian summer monsoon affects the lives of
more than 2 billion people across South Asia,
and provides more than 75% of total annual
rainfall.
Agricultural and industrial consumers require
reliable source of water, together with an
appropriate forecast on seasonal and
intraseasonal timescales.
How monsoon characteristics may change in
the future is a key goal of climate research.
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Outline
Introduction
Model details
The mean monsoon
Extremes & active-break cycles
Interannual variability and predictability
Decadal-timescale uncertainties
Summary
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Model experiments
Hadley Centre coupled model HadCM3 run at
high vertical resolution (L30).
This better represents intraseasonal tropical
convection1 and has an improved atmospheric
response to El Niño2.
Control (1xCO2) and future climate (2xCO2)
integrations used to test the impact of increased
GHG forcing.
Further integration of each climate scenario to
test the role of systematic model biases.
1P.M.
2H.
Inness, J.M. Slingo, S. Woolnough, R. Neale, V. Pope (2001). Clim. Dyn. 17: 777--793.
Spencer, J.M. Slingo (2003). J. Climate 16: 1757--1774.
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Mean response of the monsoon to 2xCO2
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Mean monsoon response in the AR4 models
Fig 10.91: some consistency in the JJA response of precipitation
over India to A1B forcing with 2xCO2 result (but within intermodel spread).
Fig 10.121: less than 80% of models agree on annual mean
change in precip over India.
10.12
10.9
Of the six AR4 models
which reasonably simulate the monsoon
precipitation climatology of the 20th century, all show general
increases in seasonal rainfall over India in the 1pctto2x runs2.
12G.
H.
Annamalai,
Hamilton,
K. Climate
R. Sperber
(2007). J. Climate
20: 1071--1092
Meehl et al. K.
(2007)
Global
Projections.
In: Climate
Change 2007: The Physical
Science Basis.
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Systematic model bias and the uncertain response to 2xCO2
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Uncertainty in monsoon precipitation response to 2xCO2
Systematic bias
seems to mask full
impact of changing
climate
1A.G.
Turner, P.M. Inness, J.M. Slingo (2007a). QJRMS 133: 1143—1157.
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Intraseasonal variability & extreme events
Intraseasonal modes represent the largest
variations of the Indian summer monsoon.
2002
2007
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Active-break index
Simple active-break index constructed from AllIndia rainfall.
Active-break events defined as rainfall anomaly
to seasonal cycle lying outside ±1σ, persisting
for at least five days.
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Absolute precipitation in active & break events
Clear intensification of
active and break
events at 2xCO2.
Intensification of
break anomalies at
2xCO2 is tempered by
wetter climatological
seasonal cycle.
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Interannual variability
Year-to-year variability increases at 2xCO2 (+24%
using Webster-Yang index).
Increases are predominantly tied to ENSO.
strong-weak monsoon precip and 850hPa wind
1xCO2
2xCO2
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Monsoon-ENSO teleconnections: lag correlations
Systematic model bias can have a dramatic impact on
the teleconnection to ENSO.
JJAS Indian rainfall vs. Niño-3 SST
The teleconnection is generally robust with increased
CO2 forcing.
1A.G.
Turner, P.M. Inness, J.M. Slingo (2007a). QJRMS 133: 1143—1157.
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Monsoon-ENSO teleconnection: moving correlations
HadISST vs. All-India gauge data
Recent decades have
seen a marked decline in
the strength of the
teleconnection.
model rainfall
Model teleconnection
varies with similar amplitude
to observations despite fixed
CO2 forcing.
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Interdecadal uncertainty?
One possible source of uncertainty lies in El Nino, which is
known to consist of different mechanisms1,2 which vary in
strength over time.
Such changes to the nature of El Nino have
been found in 2xCO2 model integrations,
with associated impacts on the monsoon3.
31A.G.
Turner, P.M.
J.M.(2001).
Slingo J.
(2007b).
QJRMS
133:
A.V. Federov,
S.G.Inness,
Philander
Clim. 14:
3086—3101.
1159—1173.
2E. Guilyardi (2006). Clim. Dyn. 26: 329—348.
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Summary
Some qualitative agreement on future increases
in the mean monsoon.
Systematic model biases may mask the full
climate change signal in monsoon regions.
Increases in monsoon variability on interannual
and intraseasonal timescales.
Interdecadal variations in the monsoon and its
drivers add additional uncertainty to climate
change projections.
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