Transcript Document

RMetS meeting, Wednesday 20 June 2007
The Indian Summer Monsoon and Climate
Change
Andrew Turner
with Pete Inness & Julia Slingo
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, increasingly, 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.
Outline
Introduction
Model framework
Climate change and the mean monsoon
Interannual and intraseasonal variability
How do systematic model biases affect the
result?
The monsoon-ENSO teleconnection
Model set-up
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.
2xCO2 response of HadCM3
Summer climate of HadCM3 2xCO2
Response to 2xCO2
The monsoon in IPCC AR4 models
Annamalai et al. (2007):
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
runs (including HadCM3 L19).
H. Annamalai, K. Hamilton, K. R. Sperber (2007). J. Climate 20: 1071--1092
Interannual variability
Exceptional seasons of persistent flood or
drought have devastating economic and
human consequences.
PDF of seasonal
rainfall over India
in HadCM3.
Interannual variability is projected to increase
at 2xCO2 (+24%), particularly through
increased likelihood of very wet seasons.
Intraseasonal variability
Intraseasonal monsoon variations are
arguably of most importance to local
populations, active and break events
bringing intense rains and short droughts to
monsoon regions.
The extended and
intense break of July
2002 contributed to
nationwide drought
with 19% reduction in
JJAS rainfall from
climatology.
Source: www.tropmet.res.in/~kolli/MOL
Intraseasonal variability
Changes to active-break cycles at 2xCO2:
break events
Break event precipitation
Break events defined where AIR
anomalies to annual cycle:
daily precip falls 1σ below the
2xCO2 minus 1xCO2
mean.
More intense break events over
India at 2xCO2 (and active events,
not shown).
Various indices tested.
Caveats?
Intraseasonal variability
Changes to heavy precipitation
Precipitation values at upper percentiles
Levels of heavy
precipitation
increase at upper
percentiles in 2xCO2
climate.
Changes are
beyond those due to
the change in mean
precipitation.
1xCO2
2xCO2
Model set-up
Hadley Centre coupled model HadCM3 run at
higher vertical resolution (L30 vs. L19).
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.
Systematic biases in HadCM3
Summer climate of HadCM3 1xCO2
HadCM3 minus observations
Flux adjustments at 1xCO2
Flux adjustments are
calculated by relaxing IndoPacific SSTs back toward
climatology in a control
integration.
The heat fluxes required for
the relaxation are saved and
meaned to form an annual
cycle.
Annual cycle applied to the
equatorial band of a new
integration*.
Annual Mean
Amplitude of annual cycle
* After: P.M. Inness, J.M. Slingo, E. Guilyardi, J. Cole (2003). J. Climate 16: 365-382.
Systematic biases in HadCM3
& their reduction in HadCM3FA
Results from A.G. Turner, P.M. Inness, J. M.
Slingo (2005) QJRMS 131: 781-804
Maritime Continent cooled; cold tongue warmed
Coupled response: reduced trade wind errors and monsoon jet
Reduced convection over Maritime Continent & other precip errors opposed
HadCM3 minus observations
HadCM3FA minus HadCM3
Flux adjustments at 2xCO2
Assume systematic biases will still be
present in the future climate.
Assume that the adjustments necessary to
correct these biases will be the same.
Same annual cycle of flux adjustments used
at 2xCO2 (in common with previous studies
where adjustments were necessary to
combat drift).
2xCO2 response of HadCM3
Summer climate of HadCM3 2xCO2
Response of HadCM3 2xCO2
2xCO2 response of HadCM3FA
Summer climate of HadCM3FA 2xCO2
Response of HadCM3FA to 2xCO2
Monsoon precipitation response
Systematic bias
seems to mask full
impact of changing
climate
Taken from A.G. Turner, P.M. Inness, J.M. Slingo (2007). QJRMS, accepted, due out soon
Monsoon-ENSO teleconnection:
lag-correlations
DMI
Indian rainfall
Flux adjustments have dramatic impact on the
teleconnection, particularly when measured by Indian rainfall.
The impact of increased GHG forcing is less clear but the
teleconnection is generally robust.
Summary
Projections of the future climate show robust /
enhanced mean monsoon consistent with other
modelling studies.
Intraseasonal and interannual modes of variation
are more intense at 2xCO2, potentially leading to
greater impacts of the monsoon on society.
Systematic model biases may be masking the
true impact of increased GHG forcing.
The monsoon-ENSO teleconnection, useful for
seasonal prediction, remains robust. Indeed
model error has more impact.
Thank you!