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SAGES Scottish Alliance for Geoscience, Environment & Society

SAGES Scottish Alliance for Geoscience, Environment & Society. Climate Change: Observing and Simulating the Past; Predicting the Future Simon Tett, Chair of Earth System Dynamics & Modelling

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SAGES Scottish Alliance for Geoscience, Environment & Society

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  1. SAGESScottish Alliance for Geoscience, Environment & Society Climate Change: Observing and Simulating the Past; Predicting the Future Simon Tett, Chair of Earth System Dynamics & Modelling With thanks to Gabi Hegerl, Ben Santer, Phil Jones, Keith Briffa, Peter Thorne, Philip Brohan, Nick Rayner, John Kennedy, Peter Stott, Myles Allen, Gareth Jones, John Mitchell, Geoff Jenkins, Chris Folland, David Parker, Jonathan Gregory, Bob Harwood, Richard Kenway and Claire Jones

  2. What are we trying to understand? How might the earth system evolve in the future? How and why did it evolve in the past? Image created by Reto Stockli with the help of Alan Nelson, under the leadership of Fritz Hasler

  3. What are we modelling? From Space Science and Engineering Center, University of Wisconsin-Madison

  4. Overview • Basic physics • Modelling the climate system • Observations of climate change • Using climate models • Understanding 20th century climate change • Role of natural drivers in natural variability • Predictions of future change • Importance of external drivers • Concluding thoughts

  5. Radiation – the driver of the climate system • Key ideas • Lots of incoming shortwave radiation (“Visible”) from sun • Same total energy going out from Earth but peaks in Infra-red. (“Heat”) • Surface is warmer than you’d expect from simple radiation budget. • The bit of the climate system that radiates energy to space is high up (where it is cooler). • Atmosphere cools with height • So surface is warmer the “greenhouse” effect • Changing the height of the atmosphere where energy gets to space will then affect the surface temperature

  6. Lapse Rate Tropical Pacific lapse rate Temperature falls with height From http://tamino.wordpress.com/

  7. Feedbacks • Act to amplify (or decrease) warming from changes in CO2, other greenhouse gases and other climate drivers. • Blackbody – warmer planet emits more radiation and so cools. (Negative feedback) • Water vapour – warmer atmosphere can store more water vapour. Water vapour absorbs “heat” radiation so is a Greenhouse gas. • Most important in the upper troposphere • Warmer world will have more moisture in the atmosphere and so will trap more heat. Positive feedback. • Clouds • Positive feedback – “trap” “heat” radiation. Particularly true for high clouds • Negative feedback – reflect back solar radiation. Particularly true for low clouds • Ice/Albedo feedback. • Ice is white and reflects lots of solar energy back to space. • Melt ice and more solar radiation absorbed which in turn warms the climate..

  8. Snow/Ice Feedback Image courtesy NASA/GSFC/JPL, MISR Team. See http://visibleearth.nasa.gov/ Summer Winter

  9. Climate Modelling • Atmospheric modelling has long history – first attempts, using computers, made in 1950’s. • General Circulation Models (GCM’s) developed from numerical weather prediction models • Take physical laws and apply them to atmospheric and oceanic motions. • Key is that GCM’s are built bottom up. • Interested in “Emergent Phenomenon”, such as statistics of data, rather than detailed evolution. • Other approaches but not covered in this lecture.

  10. Modelling the Climate System Main Message: Lots of things going on! Karl and Trenberth 2003

  11. General Circulation Models • 3-D model of the circulation of the atmosphere and ocean • Fundamental equations: • Conservation of momentum • Conservation of mass • Conservation of energy • Equation of state

  12. Parameterized Processes • Unresolved motions and processes affect the large scale flow so their effect needs to be parameterized. Slingo From Kevin E. Trenberth, NCAR

  13. What are we trying to parameterize? How we parameterise What is there…

  14. Numerical Modelling Cray Y-MP ~ 1990 L. F. Richardson circa 1920 Since the 1960’s super-computer computational power increased by factor of 16 every decade. Over my career increased 200-300 fold HECToR –2008

  15. Observing Climate Change • Observing system not stable • Climate changes slowly compared to observing system.

  16. Global Mean Temperature From Brohan et al, 2006

  17. The longer perspective Recent warming unprecedented

  18. Changes in Upper Ocean temperatures The upper ocean is warming at, when looked one way, at roughly the same rate everywhere From Palmer et al, 2007

  19. Changes in the free atmosphere: Large Observational Uncertainty Left plot shows cooling in the tropical atmosphere. Contradicts climate models which predict largest warming in the tropics. From Thorne et al, 2005 & Titchner et al, 2008 Right hand plot shows range of possible temperature changes in tropical free atmosphere due to uncertainties in observations. Sometimes models are more reliable than observations!

  20. Model Applications • Understanding 20th century climate change • The role of natural and human drivers in climate variability • Future scenarios • Summary: external drivers important in explaining observed climate variability and future climate change

  21. What might cause observed change?

  22. Internal variability – variability generated within the climate system Recent tropical Pacific ocean temperatures from IRI The North Atlantic Oscillation source http://www.ldeo.columbia.edu/NAO by Martin Visbeck

  23. Natural Factors that might effect climate: Volcanoes Volcanic Aerosol depth 0.2 0 2000 1850 Large tropical volcanoes inject sulphur dioxide into the Stratosphere where it stays for 2-3 years. Effect is to make an aerosol that scatters light and so cools climate.

  24. Natural Factors that might effect climate: Solar Irradiance Sunspot Number 200 0 1700 2000 Solar activity (sunspots etc) & irradiance changes with 11-year solar cycle. There are long term changes in solar activity – the Maunder Minimum being one example. Converting this to changes in solar irradiance can be done though very uncertain. “Sun-like” starts which show activity variations have been used to estimate irradiance changes. Recent work (astronomical) and modelling (Lean et al) suggests there may be no significant long term variation in solar irradiance.

  25. Human Factors that might affect climate: Aerosols Thanks to Met Office

  26. Human Factors that might affect climate: Greenhouse gases CO2 MMR*106 CH4 MMR*109 380 1800 Flasks Mauna Loa Observatory 360 1600 1400 340 1200 320 1000 300 Ice cores 280 800 Ice cores 260 600 1700 1800 1900 2000 1700 1800 1900 2000 Year Year Greenhouse gas concentrations have changed over the last century. Their effect is to decrease the transmission of heat radiation by the atmosphere. So should warm climate.

  27. Understanding and Attributing Climate Change in the 4th Assessment Globe, Land, Ocean and individual continents all likely show human induced warming. Warming effect of greenhouses gases likely offset by other human and natural drivers

  28. Modelling the last 500 years • How important are external drivers compared to internal climate variability? • Simulation with fixed drivers – “internal” variability alone. • Simulation with only natural drivers • Sun & Volcanic eruptions • Simulation with human and natural drivers • Natural + changes in greenhouse gases, aerosols, and land-surface properties

  29. Natural Drivers Annual: Slow changes with large negative forcings (from volcanoes) Solar 25-year Gaussian filter. Solar and Volcanic forcing as important as one another. “Maunder Minimum” includes volcanic contribution. Tambora is largest eruption of last 500 years. Late 20th century is also a volcanically active period. Volcanic

  30. Effect of natural drivers SH has less variability (as more ocean) than does NH Both hemispheres change together as does the land & ocean though there are some differences. Natural variability is about ±0.3K compared to “internal” variability of ±0.1K. So Natural forcings are an important driver of global-scale temperature variability

  31. Naturally driven variability Effect of natural drivers is to increase variability in the tropics

  32. Adding human drivers Aerosols and volcanoes offset some GHG and solar warming Greenhouse gases Total Human Sun Tot. Natural Volcanoes Aerosols

  33. Temperature Changes with human drivers included Effect of human drivers is to warm climate so that it warms outside envelope of natural variability by mid-late 19th century in southern hemisphere land and by mid 20th century in northern hemisphere

  34. Effect of human drivers of climate Shows impact of human drivers on zonal-average temperature. Tropics warm first and warming is significant by mid 19th century. Northern hemisphere warming delayed by aerosol cooling in simulation

  35. Predicting the Future Material in this section from IPCC 4th assessment report. Results based on multi-model archive. Typically show average across all model simulations with uncertainties from range Scenarios used to drive models. Self-consistent atmospheric concentrations of CO2 and other greenhouse gases. Based on different human development paths

  36. Projections of Future Changes in Climate Best estimate for low scenario (B1) is 1.8°C (likely range is 1.1°C to 2.9°C), and for high scenario (A1FI) is 4.0°C (likely range is 2.4°C to 6.4°C).

  37. Projections of Future Changes in Climate Projected warming in 21st century expected to be greatest over land and at most high northern latitudes and least over the Southern Ocean and parts of the North Atlantic Ocean

  38. Projections of Future Changes in Climate Precipitation increases very likely in high latitudes Decreases likely in most subtropical land regions

  39. Is climate changing faster than we thought it would? • Lot of argument has been about reality of climate change • Are observations good? • Is the sun responsible for warming? • Feedbacks are weak so that future warming not likely to be a great threat? • General consensus (see 4th Assessment report) is that climate is changing, likely due to human influences and agreement between different models as to likely warming. • But could models be underestimating future climate change?

  40. What does the future hold? Climate Sensitivity – measure of feedbacks. “Long tail” suggests there may be strong feedbacks. Ensemble of “perturbed physics” models showing large uncertainty range of future warming. Which are right?

  41. Sea-ice (its ½ what is should be) Is this unexpected? Are we missing something fundamental in our understanding of the Earth system?

  42. Sea-Ice NASA/GODDARD SPACE FLIGHT CENTER SCIENTIFIC VISUALIZATION STUDIO; (DATA) ROB GERSTON, GSFC

  43. Circulation change important for regional changes Human influence detected on Sea Level Pressure BUT magnitude under-simulated in Northern Hemisphere (e.g. Gillett et al., 2005) These problems will affect regional model simulations and regional predictions Observations Model mean NH SH Multi-model archive From Gabi Hegerl

  44. UK Extreme events Tewkesbury 2007Photograph: Daniel Berehulak/GettyImages Met Office figures show that May to July in the England and Wales Precipitation is the wettest in a record that began in 1766. We must learn from the events of recent days. These rains were unprecedented, but it would be wrong to suppose that such an event could never happen again…. (Hazel Blears, House of Commons, July 2007) Is it human induced climate change or natural variability?

  45. UK changes Precipitation (blue) and temperature (red) for 1931-80 and 1981-date (dashed) High summer drying and warming. Rest warming and moistening

  46. Change over last century Observations distinct from zero, consistent with all and inconsistent with natural. Implies human influence on UK climate. Natural All Obs Does model underestimate high summer changes?

  47. Summary & Conclusions • Basic understanding of the climate system explains greenhouse effect and why would expect warming in response to changing atmospheric composition • Details of response come from feedbacks • Climate models are built “bottom up” not top down. Uncertainties arise from need to parameterize unresolved phenomenon • Interested in the emergent behaviour which is not easily predictable from basic physics in model. • Instrumental observations of surface temperature back to mid 19th century • This, and other observations, show clear evidence of warming and climate change.

  48. Summary & Conclusions • Using models and observations to establish that: • 20th century climate change is likely to be human driven with greenhouse gas warming being offset by natural and other human drivers • That external drivers are an important driver of natural climate variability • That humans might have affected 19th century tropical climate. • Climate change has already happened and will continue to happen regardless of what we do. • But will be large if emissions are not reduced. • Models may be underestimating changes to come particularly those related to changes in atmospheric circulation. • This has important consequences for regional (i.e. UK) climate change.

  49. The End! Thanks for listening Any Questions?

  50. Extra Material

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