The changing climate research agenda
Chris Gordon, Deputy Director of Climate Science
Monash
University, 8 April 2010
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Structure of Met Office Hadley Centre
Integrated Climate Programme
Delivery and Communications
Climate
Monitoring
and
Attribution
Quantifying
the Risks of
Dangerous
Climate
Change
Science to
support
Mitigation
Science to
support
Adaptation
Met Office Hadley Centre Underpinning Capability
Climate Observations;
Understanding climate processes, model development and evaluation;
Climate predictions and prediction systems;
Supercomputing and IT infrastructure
Underpinning capability external to the climate programme
Met Office Weather Forecasting capability
Met Office IT Infrastructure
NERC climate research capability (through JCRP), LWEC etc.
International UM collaboration with Met Services and the research
community
20%
80%
Outline of talk
• Focus on predictions for near term adaptation
and extremes
• Making progress in model development
• Decadal predictions
• Climate Services
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Global average temperature 1850-2009
2000s warmest decade
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Means and extremes …
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Observed climate changes
East Asia
Mean temperature change
East Asia
Change in frequency of
1961-90, one-in-ten year
warm summers.
East Asia
Exceedance of
1-in-10 threshold
1900
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2000
Now happening 5 out of 10
years.
2100
Temperature change (ºC)
Projections of future global
warming
Evaluation of
impacts
High Emissions
Low Emissions
MITIGATION
Emission
scenario
independent
NEAR TERM
ADAPTATION
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Role of natural variability
European winter temperature
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Extremes and variability
• Over the next 30 years, climate temperature extremes will
generally occur because of a combination of the long
climate trend and natural variability.
• When they are in phase extremes occur and people say
climate change is accelerating, when they cancel people
say climate change has gone away!
Arctic sea
ice
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European Summer
Temperatures
Observed temperatures
Simulated temperatures
2060s
2040s
2003
Summer 2003:
normal by 2040s, cool by 2060s
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Stott Nature 2004 – updated to 2007 – HadGEM1
PDFs of possible temperatures in 19992008 window – with and without climate
change (Western Europe)
ALL and NAT
components
+
internal variability
(CONTROL)
Solid Lines: HadGEM1
Dashed Lines: MIROC
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‘New’ agenda
• Regional prediction of extremes
• Out to decadal timescales for near term
adaptation planning
• Linked to application impact models
• Need robust information for decision making
• Underpinned by process understanding and
reduction of uncertainty
In the Met Office, the ‘long range forecasting’
activities have been a third priority behind NWP
and long term climate. Now putting these on a
more equal footing.
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Same model across all
timescales
Daily
Weather
Seasonal
Forecasting
Decadal
forecasting
and integration with impact models
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Climate
prediction
Challenges to climate science
IPCC 4th Assessment Report:
Projections of likely shifts in
rainfall patterns
 % change in rainfall by end of 21st
century, where more than 2/3 of
the models agree on the sign of
the change.
 White areas denote regions
where no consistent signal is
predicted e.g. Africa.
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Climate scenarios for India
Simulated Changes
in the ‘All India’
monsoon rainfall
Work at IITM
in Pune
AR4 Models
HadCM3 QUMP models
- Could choose models that are ‘good’ at known features of the summer
Asian monsoon. Need methodology to define ‘good’. Methodology is
being widely applied.
- Use these to provide downscaled scenarios of rainfall for India.
- Also including impacts – water, agriculture.
- Requirement is better future modelling of monsoon rainfall
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CET
Model Intercomparison: Monsoon
processes
• HadGEM models seriously
underestimate Indian rainfall
• Monsoon performance in
HadGEM3-A is better than many
other models in terms of
circulation and interannual
variability, despite poor
climatological rainfall.
• Strong teleconnections with Pacific
SSTs during 1980-1989 period
suggest predictability in HadGEM
models which may be absent in
other models.
Alistair Sellar, Gill Martin
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Monsoon precipitation: Errors across
resolution and timescale
N96 – 135km
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N320 – 40km
Multi-Decade error
5day – 1 day tendency
Rainfall errors over Africa (JJA)
GPCP: 1992-2007
NWP 1992: Day 1 - GPCP
Climate 20 Year:
NWP 1992-2007:
HadGEM2 - GPCP
Day 1 - GPCP
NWP 2005: Day 1 - GPCP
A seamless modelling vision
Ultra- high resolution
•
•
Limited Area (LAM, RCM, CASCADE)
Atmosphere NWP (to 16km by 2011, L70)
Seasonal/Decadal
•
•
Resolution
Centennial/Ensembles
•
•
Complexity
& ensembles
•
Monthly to Decadal
Forecasting
Projections to 2100
Global climate (~100-150km, L63)
Multicentury runs/ S2D ensembles
Earth System
JULES: Coupling the Land Surface
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Global Coupled Climate (~60km, L85)
Multidecades on joint supercomputer
Understanding regional
processes
• Global Climate (~150km,L63)
Multicentury ensembles, rapid response
Simple models
•
Energy Balance Models
• Statistical sampling
long timescale feedbacks
Exploring scenarios
Model Development: Atmosphere
horizontal resolution
HadGEM3-HAO: Zonal mean response MAM: 150W-90W
SST
• First evidence of
an assymetric
ITCZ
Sensitivity to
resolution and
TKE mixing
parameters in
ocean
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Precip
Traceable Model Hierarchy – Impact of
Ocean resolution
Malcolm Roberts
SSTs in North Atlantic
Model Development: Ocean
Resolution
HadGEM3-HAO (N216)
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SST
errors
HadGEM3-AO (N96)
1/3o ocean
Tropical
instability waves
• Tropical Instability Waves in the
Tropical Pacific Ocean
• Resolved in HiGEM, poorly resolved
in HadGEM;
• Responsible for meridional heat
transport in the tropical Pacific
• Invoked for explaining improved mean
state in that region of the ocean,
important for El Niño
• See papers by M. Roberts and J.
Harle
1-1/3o ocean
Shaffrey et al, 2009, J. Clim.
Eddies, SSTs and ENSO
• Rôle of resolved versus
parametrised ocean mixing, for
example:
L
• Tropical Instability Waves
emerge in 90km-1/3o model
(HiGEM), performing meridional
mixing near Equator;
• ENSO is poorly represented in the
standard Hadley Centre climate
model (HadGEM1); a more
realistic ENSO is simulated by the
high-resolution HiGEM model;
H
• is this because the HiGEM mean
state in the tropical Pacific is so
much closer to reality ?
Eddy heat flux
ENSO
DJF
convergence
Obs
precipitation
anomalies
(a) Low res
• if so, this is a good example of a
smaller scale phenomenon
affecting the large scale mean
state and, through it, a major
element of climate variability.
(b) High res
Ocean temperature
profile along Equator
(c) Obs
Roberts et al, 2009
Nino3 SST normalised power spectrum
HadGEM1.1
HiGEM1.1
HadISST
Nino3 SST non-normalised
power spectrum
Near term climate change – the next 30
years
• Major climate anomalies will occur when man
made climate change and natural variability are
in phase.
• Models are relatively poor at the natural
variability part. High climate research priority.
• Requires international collaboration to improve
regional predictions.
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Decadal prediction system: Global
annual mean surface temperature
Observations
Forecast/hindcast
Forecast from 2008
Forecast from 2009
Smith et al., 2007
Assessment of forecast from June 2005
Temperature anomalies (wrt 1979-2001) for
the period June 2005 to Nov 2008
UK mean Temperature
Model prediction
No initial information
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Precip anomaly correlation
(35x35o lat/long boxes)
Climate Services:
Statement of Intent
The vision:
•To deliver the most trustworthy
predictions of how climate may
vary and change over the
coming weeks and decades.
•To interpret those predictions in
terms of the risks of hazardous
weather and climate extremes
•To provide products and advice
to help society plan for and
adapt to climate variability and
climate change in a timely
fashion
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The DFID-Met Office Hadley Centre Africa
Climate Science Research Partnership
(CSRP) - £1m/year
Improved understanding and
modelling of African climate
Real-time monthly-seasonaldecadal prediction products
Met Office FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom
Tel: 01392 885680 Fax: 01392 885681
Email: dawn.harrison@metoffice.gov.uk
Downscaling
Knowledge management
Workshops and study fellowships at
African institutions
Consultation
Establish the climate variables for
which improved prediction is a priority
CSRP-Africa
Summary
• Over next 10 years comprehensive climate
services will be developed internationally
• Focus on monthly to decadal timescales of near
term adaptation (unavoidable climate change)
• Natural climate variability and man made
change both important – extremes focus
• Current climate models indicate some levels of
skill for regional predictions but there is much to
be done to improve them – process focus.
• Will need strong links to application modelling
and risk analysis
• Adaptation is regional – international
collaboration and user engagement is critical
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