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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
- 3. What is synthesis? “Seeing the big picture”
- 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
- 16. The climate system Climate (temperature) Adapted from: Australian Academy of Science (2010) The science of climate change: questions and answers Solar radiation Heat radiation
- 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)
- 28. Warming is approximately proportional to cumulative CO2 emissions
- 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]