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Prof. Michael Raupach "Synthesis in science and society" ACEAS Grand 2014 part A
1. Synthesis in science and society – part A
Michael Raupach1,2
1Climate Change Institute, Australian National University, Canberra
2Global Carbon Project, Future Earth
ACEAS Symposium, 7 May 2014
Thanks: colleagues in
• Institutional environments (CSIRO, ANU)
• International environments (Future Earth, Global Carbon Project)
• Project environments (Australia 2050, PMSEIC, AAS Climate Q&A)
2. Outline
Establishing the framework
• What is synthesis?
• Why attempt it?
Examples of synthesis
• Natural sciences: Climate change
The Anthropocene
• Human sciences: Tragedy of the commons
• Contemporary challenge: Nature and humanity
A synthesis toolbox
• Traditional tools: observation, experiment, modelling
• Tools for synthesis: complexity, evolution, emergence, narratives
• Objective science and subjective values
• Synthesis as story: bridging between the objective and the subjective
4. What is synthesis?
“Seeing the big picture”
Describing, understanding and governing a complex system
• Accounting for interactions between modular system elements
=> Modularity, hierarchy
Focus on linkages more than on module-level detail
• Importance of defining the system and its boundary
=> What’s an external driver, what’s an internal response or feedback
5. What is synthesis?
“Seeing the big picture”
Describing, understanding and governing a complex system
• Accounting for interactions between modular system elements
=> Modularity, hierarchy
Focus on linkages more than on module-level detail
• Importance of defining the system and its boundary
=> What’s an external driver, what’s an internal response or feedback
The current grand challenge:
a synthesised perspective on nature and humanity as a single Earth System
6. Why attempt synthesis?
Antidote to reductionism?
• But reduction helps us modularise, so is essential for synthesis
Understanding the whole system is the challenge; understanding components is a
means to that end
Many phenomena are emergent: they exist at system level but not component level
a wave (sound, ocean, Mexican)
weather, climate
an ecosystem (structure, function)
a human being (body, mind, spirit)
a novel, poem, song, symphony, artwork
a human society: health, wellbeing
an economy
climate change, sustainability
A holistic story has power: explanative, persuasive
7. Why attempt synthesis?
Antidote to reductionism?
• But reduction helps us modularise, so is essential for synthesis
8. Why attempt synthesis?
Antidote to reductionism?
• But reduction helps us modularise, so is essential for synthesis
Understanding the whole system is the challenge; understanding components is a
means to that end
9. Why attempt synthesis?
Antidote to reductionism?
• But reduction helps us modularise, so is essential for synthesis
Understanding the whole system is the challenge; understanding components is a
means to that end
Many phenomena are emergent: they exist at system level but not component level
a wave (sound, ocean, Mexican)
weather, climate
an ecosystem (structure, function)
a human being (body, mind, spirit)
a novel, poem, song, symphony, artwork
a human society: health, wellbeing
an economy
climate change, sustainability
10. Why attempt synthesis?
Antidote to reductionism?
• But reduction helps us modularise, so is essential for synthesis
Understanding the whole system is the challenge; understanding components is a
means to that end
Many phenomena are emergent: they exist at system level but not component level
a wave (sound, ocean, Mexican)
weather, climate
an ecosystem (structure, function)
a human being (body, mind, spirit)
a novel, poem, song, symphony, artwork
a human society: health, wellbeing
an economy
climate change, sustainability
A holistic story has power: explanative, persuasive
11. Outline
Establishing the framework
• What is synthesis?
• Why attempt it?
Examples of synthesis
• Natural sciences: Climate change
The Anthropocene
• Human sciences: Tragedy of the commons
• Contemporary challenge: Nature and humanity
A synthesis toolbox
• Traditional tools: observation, experiment, modelling
• Tools for synthesis: complexity, evolution, emergence, narratives
• Objective science and subjective values
• Synthesis as story: bridging between the objective and the subjective
12. Climate in the distant past (800,000 years)
Hansen et al. (2008)
Target atmospheric CO2
13. Climate in the distant past (800,000 years)
Hansen et al. (2008)
Target atmospheric CO2
14. Climate in the distant past (800,000 years)
Present CO2
Hansen et al. (2008)
Target atmospheric CO2
15. Climate in the
last 200 years
Greenhouse gas
emissions
Greenhouse gas
concentrations
Warming and other
climate changes
0
2
4
6
8
10
1850 1890 1930 1970 2010
FFemissions(PgC/y)
280
300
320
340
360
380
400
1850 1890 1930 1970 2010AtmosphericCO2(ppm)
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1850 1890 1930 1970 2010
Temperature(degC)
Cause
Effect 1
Effect 2
17. The climate system
Climate
(temperature)
Adapted from: Australian Academy of Science (2010)
The science of climate change: questions and answers
Solar
radiation
Heat
radiation
Aerosols
Water
vapour,
clouds
Ice
sheets
GHGs
(CO2, …)
Oceans
Biosphere
Human
activities
18. The climate system
Climate
(temperature)
Adapted from: Australian Academy of Science (2010)
The science of climate change: questions and answers
Solar
radiation
Heat
radiation
Aerosols
Water
vapour,
clouds
Ice
sheets
GHGs
(CO2, …)
Oceans
Biosphere
Orbital
variations
Volcanoes
Human
activities
19. Many changes
in climate
IPCC AR5 FOD TS Fig TS.1
Measures of
changing global
climate from
1850 to present
10 quantities
All available
datasets are
shown
Air temperature
(land)
Air temperature (ocean)
Sea level
Arctic sea-
ice extent
20. Climate outlook: temperature
Warming of 2 to 5 degrees above preindustrial (strong to minimal mitigation)
IPCC (2013) Fifth Assessment, Working Group 1
21. Climate models: future global warming and precipitation
Diffenbaugh and Field (2013) Science 341, 486-492
Warming
More warming in high latitudes
(polar amplification) – already
observed
Change in precipitation
Increase in global precipitation
(and global evaporation)
Changes are highly non-uniform:
predicted drying in mid-latitudes
22. IPCC (2013) AR5 WG2 SPM
Food security
Climate change will reduce wheat and maize yields by 1-2% per decade
23. PMSEIC 2010) Australia and food security
Target
Trend
Food security
Implications of climate change for global cereal production
Projected global cereal production
• 10% below target without climate change
• 15-25% below target with climate change
24. IPCC (2013) AR5 WG2 SPM
Ecosystem changes
Marine organisms are moving into previously colder waters
25. IPCC (2013) AR5 WG2 SPM
Ecosystem changes
Climate zones will faster than many land species can shift habitat
26. Future emissions scenarios and their consequences
To have a 50% chance of keeping warming below 2 deg (relative to preindustrial),
global emissions must be halved by 2050 (relative to 2000)
RCP2.6
RCP4.5
RCP6.0
RCP8.5
1800 1900 2000 2100 2200
0
5
10
15
20
25
30
FossilFuelCO2emissionsPgCy
FossilFuelCO2emissionsPgCy
> 4 deg
2 deg
27. Global CO2 emissions from fossil fuels are tracking the highest scenario
RCP2.6
RCP4.5
RCP6.0
RCP8.5
1990 1995 2000 2005 2010 2015 2020
5
6
7
8
9
10
11
FossilFuelCO2emissionsPgCyFossilfuelCO2emissions[PgC/y]
Scenarios: IPCC
Representative
Concentration Pathways
Observation uncertainty band
(± 1 standard deviation)
Data: Global Carbon Project 2014 (Le Quéré et al 2014)
29. Warming is approximately proportional to cumulative CO2 emissions
Reinforcing feedbacks:
• Ice-albedo
• Carbon cycle
• Ecosystem collapse
Stabilising feedbacks:
• Heat loss (Planck)
• CO2 removal by carbon sinks
• Logarithmic response to CO2
30. Sharing the cumulative emissions pie
w=0.0
USA
Europe
Japan
D1
FSU
China
India
D2
D3
Inertia:
share by current or
historic emissions
Sharei
=
Emisi
EmisGlobal
USADeveloping
China
31. Sharing the cumulative emissions pie
w=0.0
USA
Europe
Japan
D1
FSU
China
India
D2
D3
w=1.0
USA
Europe
Japan
D1
FSU
China
India
D2
D3
Inertia:
share by current or
historic emissions
Equity:
share by
population
Sharei
=
Emisi
EmisGlobal
Sharei
=
Popi
PopGlobal
USADeveloping USA
Developing
China China
32. Sharing the cumulative emissions pie
w=0.0
USA
Europe
Japan
D1
FSU
China
India
D2
D3
w=1.0
USA
Europe
Japan
D1
FSU
China
India
D2
D3
w=0.5
USA
Europe
Japan
D1
FSU
China
India
D2
D3
Inertia:
share by current or
historic emissions
Equity:
share by
population
Compromise:
share by mixture of
emissions and population
Sharei
=
Emisi
EmisGlobal
Sharei
=
Popi
PopGlobal
weight w (0 to 1) is a “sharing index"w=0 w=1
USADeveloping USA
Developing
China China
Sharei
=
mean of Emis
and Pop shares,
with weight w
æ
è
ç
ç
ç
ö
ø
÷
÷
÷
33. Tragedy of the commons, and beyond
Hardin (1968) - model of herders on a common pasture
- problem has no purely technical fix
Dietz, Ostrom and Stern (2003):
• Tragedy-of-commons problems can be solved with
adaptive governance in complex systems
• Requires: Information
Conflict resolution
Rule compliance
Infrastructure
Readiness for change
• These factors need to act at compatible scales
Pretty (2003):
• natural, physical, financial, human, social capital
• social capital is a prerequisite for collective resource
management
Hardin G (1968) The
tragedy of the commons.
Science 162, 1243.
Dietz T, Ostrom E, Stern
PC (2003) The struggle
to govern the commons.
Science 302.
Pretty J (2003) Social
capital and the collective
mangement of resources.
Science 302.
Reprinted in Kennedy D
et al. (2006) Science
Magazine's State of the
Planet 2006-2007. Island
Press, Washington DC.
34. Outline
Establishing the framework
• What is synthesis?
• Why attempt it?
Examples of synthesis
• Natural sciences: Climate change
The Anthropocene
• Human sciences: Tragedy of the commons
• Contemporary challenge: Nature and humanity
A synthesis toolbox
• Traditional tools: observation, experiment, modelling
• Tools for synthesis: complexity, evolution, emergence, narratives
• Objective science and subjective values
• Synthesis as story: bridging between the objective and the subjective
Editor's Notes
Figure SPM.7, Panel aCompletecaptionofFigure SPM.7:Figure SPM.7 | CMIP5 multi-model simulated time series from 1950 to 2100 for (a) change in global annual mean surface temperature relative to 1986–2005, (b) Northern Hemisphere September sea ice extent (5-year running mean), and (c) global mean ocean surface pH. Time series of projections and a measure of uncertainty (shading) are shown for scenarios RCP2.6 (blue) and RCP8.5 (red). Black (grey shading) is the modelled historical evolution using historical reconstructed forcings. The mean and associated uncertainties averaged over 2081−2100 are given for all RCP scenarios as colored vertical bars. The numbers of CMIP5 models used to calculate the multi-model mean is indicated. For sea ice extent (b), the projected mean and uncertainty (minimum-maximum range) of the subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea ice is given (number of models given in brackets). For completeness, the CMIP5 multi-model mean is also indicated with dotted lines. The dashed line represents nearly ice-free conditions (i.e., when sea ice extent is less than 106 km2 for at least five consecutive years). For further technical details see the Technical Summary Supplementary Material {Figures 6.28, 12.5, and 12.28–12.31; Figures TS.15, TS.17, and TS.20}
Diffenbaugh NS, Field CB (2013) Changes in Ecologically Critical Terrestrial Climate Conditions. Science 341, 486-492Fig. 1. Observed and projected changes in annual temperature and precipitation. (Top) Climatic Research Unit (CRU) observations (which are available only over land), calculated as 1986–2005 minus 1956–1975. (Mid- dle) Differences in the mid-21st-century period of the CMIP5 RCP8.5 en- semble, calculated as 2046–2065 minus 1986–2005. (Bottom) Differences in the late-21st-century period of the CMIP5 RCP8.5 ensemble, calculated as 2081–2100 minus 1986–2005. We show the multi-model mean, using the model aggregation of Diffenbaugh and Giorgi (65). This presentation does not indicate significant differences from background variability, nor does it reflect many other potentially important sources of uncertainty, including level of emissions, Earth system feedbacks, or model structure. The values at the left and right extremes of the color bars give the minimum and maximum values (respectively) that occur across all of the periods. The minimum temperature, minimum precipitation, and maximum precipitation extreme changes are all in the CRU observations. Further details are provided in the supplementary materials.
Figure SPM.2C and Figure TS.2EFigure SPM.2: Widespread impacts in a changing world. (A) Global patterns of impacts in recent decades attributed to climate change, based on studies since the AR4. Impacts are shown at a range of geographic scales. Symbols indicate categories of attributed impacts, the relative contribution of climate change (major or minor) to the observed impact, and confidence in attribution. See supplementary Table SPM.A1 for descriptions of the impacts (B) Average rates of change in distribution (km per decade) for marine taxonomic groups based on observations over 1900-2010. Positive distribution changes are consistent with warming (moving into previously cooler waters, generally poleward). The number of responses analyzed is given within parentheses for each category. (C) Summary of estimated impacts of observed climate changes on yields over 1960-2013 for four major crops in temperate and tropical regions, with the number of data points analyzed given within parentheses for each category. [Figures 7-2, 18-3, and MB-2]
PMSEIC (2010) Australia and food security in a changing world. Prime Minister's Science, Engineering and Innovation Council (PMSEIC), Australian Government, Canberra, Australia.Figure 2.13 Global cereal production – past and future. The trend lines represent the World Food Summit target (green), an extrapolation of the current rate of productivity increase (blue) and two possible scenarios resulting from climate change – a five per cent decline (red) or 15 per cent decline (black) over the next 40 years (Based on data from FAOSTAT, 2010).
Figure SPM.2B and Figure TS.2DFigure SPM.2: Widespread impacts in a changing world. (A) Global patterns of impacts in recent decades attributed to climate change, based on studies since the AR4. Impacts are shown at a range of geographic scales. Symbols indicate categories of attributed impacts, the relative contribution of climate change (major or minor) to the observed impact, and confidence in attribution. See supplementary Table SPM.A1 for descriptions of the impacts (B) Average rates of change in distribution (km per decade) for marine taxonomic groups based on observations over 1900-2010. Positive distribution changes are consistent with warming (moving into previously cooler waters, generally poleward). The number of responses analyzed is given within parentheses for each category. (C) Summary of estimated impacts of observed climate changes on yields over 1960-2013 for four major crops in temperate and tropical regions, with the number of data points analyzed given within parentheses for each category. [Figures 7-2, 18-3, and MB-2]
Figure SPM.5: Maximum speeds at which species can move across landscapes (based on observations and models; vertical axis on left), compared with speeds at which temperatures are projected to move across landscapes (climate velocities for temperature; vertical axis on right). Human interventions, such as transport or habitat fragmentation, can greatly increase or decrease speeds of movement. White boxes with black bars indicate ranges and medians of maximum movement speeds for trees, plants, mammals, plant-feeding insects (median not estimated), and freshwater mollusks. For RCP2.6, 4.5, 6.0, and 8.5 for 2050-2090, horizontal lines show climate velocity for the global-land-area average and for large flat regions. Species with maximum speeds below each line are expected to be unable to track warming in the absence of human intervention. [Figure 4-5]
