The Centre for Australian Weather and Climate Research A collaboration between CSIRO and the Bureau

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Contribution of Science in Climate Change Analysis
Chris Mitchell Foundation Director
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Acknowledgements

• Dr Michael Raupach
• Dr Pep Canadell
• Dr John Finnigan
• Dr Steve Phipps
• Dr John Church
• Dr Yingping Wang
• Dr Penny Whetton
• Dr Don Gunasekera
• ( many others)

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• Defining the system and understanding system
  behaviours
• Prediction
• Analysis/diagnoses of the current state of the
  system (real system response)

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System -- feedbacks (a few examples)

• Atmospheric feedbacks
• Physical
• Radiation-clouds
• Chemico-physical
• Aerosol-clouds-radiation
• Atmosphere-ocean
• El Nino Southern Oscillation
• Atmosphere-ocean-biosphere
• Sink strength
• Acidification

• Physical system
• Atmosphere
• Water
• Oceans - ice
• Physical/chemical
• Ozone
• Bio-geochemical physical
• Carbon
• Sulfur (aerosol)
• Nitrogen phosphorous (nutrients)
• Human physical biogeochemical

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IPCC, FAR WG1 Ch2
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HADLEY CENTRE EARTH SYSTEM MODEL
HadCM
HadGEM
HadGEM2
1975
1985
1992
1997
2004
2007
Atmosphere
Atmosphere
Atmosphere
Atmosphere
Atmosphere
Atmosphere
Land surface
Land surface
Land surface
Land surface
Land surface
Ocean sea-ice
Ocean sea-ice
Ocean sea-ice
Ocean sea-ice
Sulphate aerosol
Sulphate aerosol
Sulphate aerosol
Non-sulphate aerosol
Non-sulphate aerosol
Carbon cycle
Carbon cycle
Atmospheric chemistry
Sulphur cycle model
Non-sulphate aerosols
Ocean sea-ice model
Off-line model development Strengthening
colours denote improvements in models
Land carbon cycle model
Carbon cycle model
Ocean carbon cycle model
Atmospheric chemistry
Atmospheric chemistry
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Scope of the Australian Community Climate and
Earth System Simulator (ACCESS)
4-D Variational Assimilation
Observations
Observation Data-base
Observation Processing System
Supercomputing Software engineering Analysis
tools visualisation Downscaling Verification/valid
ation
Atmosphere
Dynamic Vegetation
Assimilation
Coupler
Atmospheric Chemistry
Land Surface Carbon/Hydrology
Social systems
EMIC
Sea Ice
Ocean Carbon cycle
Ocean
Energy systems
Economic systems
Dynamic Ocean Primary Prod
Ocean DataAssimilation
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Carbon cycle climate feedback

• Terrestrial biosphere and carbon-cycle (ve
  feedback)

292 ppm
Coupled Carbon Cycle Climate Model
Intercomparison Project (C4MIP) phase 2 results
Friedlingstein et al. (2006)
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Consideration of N reduces uncertainty
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Defining the system

• Three reasons models are becoming more complex
• It has been shown that parts of the system cannot
  be left out without introducing significant
  uncertainty
• In some cases additional processes/
  considerations adds additional constraints thus
  reducing uncertainty

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Real system response -- trends in airborne
fraction

• Airborne fraction fraction of CO2 emissions
  that remains in atmosphere CO2 growth
  rate / total CO2 emissions

• Filtering (Remove f lt 1 y and EVI part i.e.
  remove short noise and effects of volcanoes and
  ENSO)
• Significant AF trend (0.25 /y, P gt 0.95)

• No filtering
• AF trend not significant

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Importance of AF trend

• Land and ocean CO2 sinks are weakening ("losing
  the race") relative to emissions
• (even though sinks are increasing overall)
• Current carbon-climate models (C4MIP) do not see
  an increasing AF
• So models are not capturing some processes
• This is a severe model test

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Real system response Global CO2 emissionsfrom
fossil fuels
Raupach et al. (2007) PNAS

• Growth rates
• 1990-1999 1.3 y?1
• 2000-2005 3.3 y?1
• Scenarios underestimate actual emissions since
  2000

Revised for 2006Everything scaled to CDIAC 2000
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Projections of future climate (climate change
projections)

• Describe the future state of the system
• Information used as input to
• Assessing future impacts (damage)
• Cost-benefit assessment of abatement actions
• Assessing opportunities, as well as potential
  damage, and planning a response (adaptation)
• Adaptation is possible without knowledge of
  future state but is then
• Reactive
• Autonomous
• Unplanned

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Limitations of climate change projections

• Wide range of future states considered plausible
  (driven significantly by future socio-economic
  conditions)
• Uncertainty
• Regional detail
• Climatic variables relevant to (impacted)
  systems response
• The disproportionate effect of climatic extremes
  in damage

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Top 20 insurance losses (Apr. 2006)
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The frequency of flooding events of a given
magnitude has increased even small changes in
averages can have a large effect on return period
A 1 in 5 year event becomes a 1 in 2 year event.

Church et al., 2006
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Decrease in the return period of extreme events
for a 0.1 m sea-level rise
For a 0.5 m rise, a 1 in 100 year event could
happen several times/year
Hunter 2007 Church et al. 2008
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Projections temperature
2030 2050 2070

• Probability density functions of local climate
  change per degree of global warming are combined
  with those for global warming
• The resulting patterns of change can be scaled
  for selected years and IPCC emission scenarios
• The central estimate is the median or 50th
  percentile
• Little difference between scenarios in 2030, but
  significant differences by 2070

B1
A1T
B2
A1B
A2
A1FI
Median warming (oC)
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Projections temperature in 2070
B1
A1B
A1FI

• PDFs let us calculate the probability of
  exceeding selected thresholds for various years
  and emission scenarios
• In 2070 in Melbourne for B1, theres an 80-90
  chance of exceeding 1oC warming, but less than
  10 for 2oC. For A1FI, theres over 90 chance of
  exceeding 1oC, 80-90 for 2oC, 30-40 for 3oC and
  less than 10 for 4oC

gt 1oC
gt 2oC
gt 3oC
gt 4oC
Probability ()
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Strategies for addressing uncertainty in
projections of climate change

• Separating sources of uncertainty (where
  feasible)
• Eg uncertainty due to spread of emissions from
  the uncertainty arising climate response,
  understanding spread
• Wide variety of models in analysis is a sample
  of scientific uncertainty in the climate response
• Presenting information in probabalistic terms
• Suitable use in risk assessment
• Can focus on likelihood on exceeding known
  thresholds

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Some key science directions

• Continue to improve the comprehensiveness of
  representation in the analysis
• Key feedbacks
• Carbon climate feedback
• Ice-climate feedback (sea-level, abrupt change)
• Earth system-human system feedbacks
• Refine projections of climate change
• Regions
• Extremes
• Improved treatment of uncertainty
• Analysis of system state
• Constraints on projections

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• Feedbacks are important the feedback/s between
  the earth system and socio-economic system are
  strengthening based on experience it will be
  necessary to include these processes in model
  systems
• Corollary the behaviour of the earth system
  cannot be externalised in economic analysis, nor
  can economics and social analysis be excluded
  from climate projections
• Science places important constraints on policy
• Eg achievable concentrations
• Assist in defining damage

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Growth rates of fossil-fuel CO2 emissionsSRES
scenarios and observations 2000-2005
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Attribution of cause and effect
High
Greenhouse gases (GHGs) keep the planet warm
Confidence decreases as complexity increases
The Earth has warmed 0.7 C and sea-level has
risen 18 cm since 1900
Future GHG scenarios will lead to a warming of
1.4-5.8 C and a sea-level rise of 0-88 cm by 2100
Most of the warming of the past 50 years is due
to increases in GHGs
Human activities have contributed to changes in
ocean temperature, hemispheric temperature
contrast, regional warming
There will also be regional changes in annual
average temperature, rainfall, winds, ocean
currents, soil moisture, polar ice and clouds
Confidence level
There will also be local changes in extreme daily
temperature, rainfall, winds, fires, droughts,
tropical cyclones
Human activities have contributed to changes in
rainfall and drought
There may be rapid melting of the Greenland
Antarctic ice caps, leading to a slow-down in the
oceans overturning circulation
Low
Complexity
Simple
Complex