MET 112 Global Climate Change - Lecture 11 Future Predictions Craig Clements San Jose State University.
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MET 112 Global Climate Change - Lecture 11 Future Predictions Craig Clements San Jose State University
Climate Change and humans Anthropogenic increases in –greenhouse-gas concentrations –sulfate aerosols due to anthropogenic emissions Emission scenarios have been developed Changes in solar irradiance and volcanic aerosols –Unpredictable and difficult to model
Q: How do we predict what the future climate will be like? A: We use global models of the earth system Global Climate Models (GCMs)
Sequence of Steps 1. Estimate future GHGs concentration 2.Using future GHG levels, calculate what future climate (e.g. temp, precip) will be like. 3.Assess the uncertainty of the predictions
Calculation of Future CO 2 Concentrations Carbon Cycle Model – Simulates atmosphere-biosphere and atmosphere-ocean interactions CO 2 Emissions -How much is going into atmosphere CO 2 Concentration - How much remains in atmosphere
Carbon Cycle Models Atmosphere/ocean and atmosphere/biosphere interactions not well understood Model calculations contain uncertainty; the largest uncertainty: –Future uptake of carbon by the biosphere –Future uptake of carbon by the oceans
Past and Projected Future CO 2 Concentrations (Back-Up) (ppm) Parts per million Observations Model projections
Global Population Type of energy generation –Fossil intensive –Renewable energy Growth of Economy Type of Economy –Material based –Service and information based Cooperation among countries –More homogeneous - share technologies –More isolated - larger divide between rich/poor countries What factors affect future CO 2 levels?
The IPCC based its projections on six emission scenarios, running each one through sophisticated climate simulation programs. Governance Development Local Global EnvironmentalEconomic A1B1 B2A2 Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20 A1B A1FI A1T
Gross Domestic Product Growth at 2100 Governance Development Local Global EnvironmentalEconomic A1B1 B2A2 Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20
Energy Use at 2100 Governance Development Local Global EnvironmentalEconomic A1B1 B2A2 Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20
Governance Development Local Global EnvironmentalEconomic B1 B2A2 Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20 A1B A1FI A1T Technological Change at 2100 Country A Country B Country C
Scenarios (2) A1 storyline –World of rapid economic growth –Population peaks 2050 –Different branches dependent on energy type/use A1FI – Fossil intensive – continued dependence on coal/oil A1T – Non-fossil intensive energy use (Technology) A1B – Balance between fossil and non-fossil A2 storyline –Heteorogenous world –technologies are not shared across borders, –population continues to increase
Scenarios (3) B1 storyline –Similar population as A1 –Global exchange/cooperation –Change in economic structures from product oriented to service oriented. –Focus on social and economic sustainability B2 storyline –Population like A2 –Similar environmental and social focus –More regionally oriented (not as much exchange between countries).
CO 2 emissions for various scenarios Note: global population peaks in 2050 and declines in some scenarios Why a peak around 2050?
Projected CO 2 Concentrations for Various Scenarios Note that even the low-emission scenarios result in greatly increased CO 2 concentrations by the year 2100 –Max concentration (of scenarios shown): 970 ppm –Min concentration (of scenarios shown): 550 ppm – (Compare with current value: 370 ppm)
Climate Model A climate model is a mathematical representation of the physical processes that control climate –Basically everything that affects climate –Sun, atmosphere (greenhouse gases, aerosols), hydrosphere, land surface, cryosphere Equations are very complicated –Some of the world’s largest supercomputers are running climate models
Climate Modeling: Super Computers One frame of an IBM Power5-575 series system. NCAR's “Blue Vista” will have 16 frames. Blue Vista will need over 250 kilowatts of power to operate. The average personal computer consumes 0.12 kilowatts. 78 IBM POWER5 nodes. Each node will have eight POWER5 simultaneous multithreading (SMT) processors 16 gigabytes of memory.
Model Schematic Climate Model Changes in greenhouse-gas concentrations and changes in albedo due to aerosols Climate change (i.e. temperature, precipitation etc.)
Model Sensitivity Models (like the atmosphere) are sensitive systems. They can respond differently to the same radiative forcing, e.g., a doubling of CO 2 –This means that different models give different answers to the same problem –Thus, we use a range of models to determine the range of possible future scenarios.
Model Verification: Can it be done? Before you can trust any of these models, they must be verified. –We can use past climate as a test. If your model can simulate the past climate, then there is a reasonable chance that the model can accurately predict future climate.
Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers. Global Average Surface Temperature
Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers.
These experiments demonstrate that 1.The warming of the entire 20 th century is largely due to humans 2.The warming of the last 50 years is largely due to humans. 3.Natural factors are largely responsible for the warming of the 20 th century 4.Natural factors are not important in the early 20 th century, but more important in the last part of the 20 th century.
Climate models 1.Are not useful for predicting the temperature changes observed during the 20 th century. 2.Show that volcanic eruptions and changes in sunlight are responsible for most of the changes observed over the 20 th century. 3.Can predict the 20 th century observed temperature changes with natural factors only. 4.Can only predict the 20 th century observed temperature changes when they include both human and natural contributions.
What conclusions can you infer from these model experiments? 1.Models can reasonably predict temperature variations over the last 150 years. 2.Most of the observed warming in the past 50 years is attributable to human activities.
Notes on Temperature Projections Projected Warming: 2000 – 2100 ranges from ~1.4°C to ~5.8°C. Curves represent warming produced for seven scenarios by a model with average sensitivity. Each bar on the right represents a range of warming produced –by models of differing sensitivies for a specific scenario.
Land areas are projected to warm more than the oceans with the greatest warming at high latitudes Annual mean temperature change, 2071 to 2100 relative to 1990: Global Average in 2085 = 3.1 o C
Some areas are projected to become wetter, others drier with an overall increase projected Annual mean precipitation change: 2071 to 2100 Relative to 1990
Future predictions: main changes in climate Higher temperatures - especially on land –Arctic shows the largest warming Hydrological cycle more intense –More rain overall Sea levels rise –Why? Changes at regional level –hard to predict More intense weather (extremes) –Floods, droughts etc.
Questions 1.Based on the A1FI scenario, what is the predicted CO 2 concentration, temperature change and sea level change in 2100? 2.Based on the B1 scenario, what is the predicted CO 2 concentration, temperature change and sea level change in 2100? 3.Explain the differences.