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Why climate models are the greatest feat of modern science

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The IES 2013 Burntwood Lecture given by Julia Slingo from the Met Office on the topic:Why Climate Models are the greatest feat of modern science. #BWL13

The IES 2013 Burntwood Lecture given by Julia Slingo from the Met Office on the topic:Why Climate Models are the greatest feat of modern science. #BWL13

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  • By the end of the century, the increase of global mean surface temperature above 1986-2005 levels is projected to be: 0.3-1.7˚C for a scenario with strong mitigation2.6-4.8˚C for a scenario with no mitigation
  • By the end of the century, the increase of global mean surface temperature above 1986-2005 levels is projected to be: 0.3-1.7˚C for a scenario with strong mitigation2.6-4.8˚C for a scenario with no mitigation
  • Transcript

    • 1. Why Climate Models are the Greatest Feat of Modern Science Julia Slingo, Met Office
    • 2. 28th October 2013: St Jude Storm  17 fatalities (6 in UK)  London transport shut down during peak of storm (130 Heathrow flights cancelled)  850,000 homes lost power  Dungeness B Nuclear Power station shut down  Landslip and 100+ trees uprooted over rail lines resulting in long delays  Ferries badly affected; Port of Dover closed 06:00 to 09:30
    • 3. 5 day forecast – before the storm even existed! The same model which produced this forecast is used to simulate © Crown copyright Met Office the atmosphere in the climate model
    • 4. ‘Riding on the back’ of 40 years of improvements in forecast skill Error in Mean Sea Level Pressure (mb) for the Euro-Atlantic Region Tomorrow’s weather is the same as today’s! Day 2 Day 3 Day 5 Day 4 Day 1 ‘1 Day per Decade’
    • 5. Content Divider How does the work? climate system
    • 6. Global Mean Climate System From Trenberth et al., 2009
    • 7. Role of atmosphere and ocean dynamics in energy transports Total radiative heating (Wm-2) Poleward transports (PetaWatts) required to balance radiative heating/cooling Total Atmosphere Oceans
    • 8. Atmospheric Energy Transport Energy transports achieved through planetary circulations, waves and weather systems • Fluid on a rotating sphere – conservation of angular momentum • Heated differentially between the equator and poles • Effects of land masses and mountains • Phase changes of water – moving heat around the system
    • 9. Ocean Energy Transport From S. Rahmstorf: Thermohaline Ocean Circulation. In: Encyclopedia of QuaternarySciences, Edited by S. A. Elias. Elsevier, Amsterdam 2006 (see www.pik-potsdam.de/~stefan/thc_fact_sheet.html)
    • 10. Global Water Cycle: Phase changes of water move heat around the system Units 1012 m3/year
    • 11. Global Water Cycle: Phase changes of water move heat around the system Annual Mean Precipitation (Rain and Snow: mm/day)
    • 12. Global Water Cycle: Phase changes of water move heat around the planet Annual Mean Precipitation minus Evaporation (mm/day) Precipitation = Surface Evaporation + Atmospheric Transport
    • 13. Annual Mean Sea Surface Salinity reflects the global water cycle
    • 14. How much of this did we know when I began my career in 1972? X X None of the global budgets, none of the hydrological cycle ? ? A little bit about the oceans and a little bit about global weather
    • 15. Climate Model simulation of Net Radiation and Atmospheric Transports. Ocean transports are inferred as a residual. Climate models were beginning to tell us things about the climate system that we couldn’t observe.
    • 16. Content Divider What is Climate Modelling?
    • 17. Building a Climate Model: Where to Start? Climate Models are based on fundamental equations of motion (Newton’s 2nd Law of Motion), mass continuity, moist thermodynamics and radiative transfer These govern: • Flow of air and water - winds in the atmosphere, currents in the ocean. • Exchange of heat (sensible and latent) and momentum between the atmosphere and the earth’s surface • Release of latent heat by condensation during the formation of clouds and raindrops • Absorption of solar radiation and emission of thermal (infra-red) radiation
    • 18. Fundamentals of climate (and weather) modelling  Represent the earth by a grid of squares, typically of length 100 km or smaller.  Atmosphere and oceans are divided into vertical slices of varying depths, typically 70 or more.  3-dimensional picture of the state of the atmosphere and oceans.  Integrate equations of motion and thermodynamics forward in time.
    • 19. Representing Unresolved Processes: Parametrization Boundary layer turbulence and mixing Radiation Cumulus convection Precipitation Clouds and microphysics Effects of mountains Atmospheric composition
    • 20. Evolution of climate models over time: Resolution 1990 1996 © Crown copyright Met Office 2001 2007
    • 21. Evolution of climate models over time: Complexity
    • 22. Earth Observation – giving the planet a ‘health check’! We know an immense amount about what is happening to the planet – but we don’t necessarily know why
    • 23. Climate Models as the Content Divider ‘Laboratories’ of Climate Science
    • 24. Does soil moisture affect the behaviour of the West African Monsoon? Climate models were beginning to tell us things about how the climate system works and what’s important Wet Soil Dry Soil
    • 25. Predicting Winter Climate: Understanding the drivers of the North Atlantic Oscillation
    • 26. Understanding WHY the world is warming ‘Extremely likely (95-100%) that most of observed increase in global surface © Crown copyright Met Office temperature since 1951 has been caused by human influence.’ – IPCC 2013
    • 27. ‘Hiatus’ in global surface warming
    • 28. Spatial Pattern of the ‘Hiatus’ hints at the oceans Sea Surface Temperature 2000-2012 minus 1990-1999
    • 29. Pacific Ocean implicated in the ‘hiatus’ in models From Meehl et al. 2013
    • 30. Models suggest that heat is sequestered into the deep ocean during a ‘hiatus’ From Meehl et al. 2013
    • 31. Content Divider Climate modelling: A modern Renaissance Science?
    • 32. Mathematics c pd v  Dr u uv tan   uw    2 sin  v      2 cos  w   S u Dt r r cos    r  c pd  Dr v u 2 tan   vw    2 sin  u     Sv  Dt r r  r      u 2  v 2   2 cos  u  S w Dr w    c pd v   Dt r r r  g    u    v  w  Dr 2 2   y r cos    y r cos    r cos     r   r   0 Dt       Dr  S Dt Met Office Unified Model makes neither hydrostatic or shallow atmosphere approximations
    • 33. Mathematics How to solve these equations numerically on a grid:  Accuracy and Conservation of fundamental properties  Efficient and Scalable code  Robust and Stable code v Icosahedral-triangles Icosahedral-hexagons Cubed Sphere
    • 34. Mathematics, Computer Science Some of the Machines that I’ve worked on! 1980s: NCAR Cray 1 2000s: Japanese Earth Simulator Original weather forecasts so simple that they can run on a mobile phone in fractions of a second 2010s: Met Office IBM Power 7 Met Office’s current IBM Power7 machine has peak speed of ≈ 1Petaflop (1,000,000,000,000,000 sums per second)
    • 35. Mathematics, Computer Science, Newtonian Physics Geophysical flows: Newton’s Laws of Motion on a Rotating Sphere Ocean surface temperatures simulated by 2km ocean model. Image courtesy of the Mercator Ocean Project, France
    • 36. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics Climate Model (HADGEM2-ES) precipitation
    • 37. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer Gases absorb and emit infrared radiation in distinct spectral bands
    • 38. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics Source: Tollefson, Nature News, 2012
    • 39. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry © Crown copyright Met Office
    • 40. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology How water moves through a tree Microbial structuring of marine ecosystems
    • 41. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology, Meteorology Screenshot from a Met Office Climate Model simulation at 12km THE VIDEO HAS BEEN REMOVED FROM THIS SLIDE IN ORDER TO MAKE THE PRESENTATION AVAILABLE ONLINE. © Crown copyright Met Office
    • 42. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology, Meteorology, Oceanography Gulf Stream meanders in 1/40 ocean model Met Office Climate Model Met Office Ocean Model with no ocean-atmosphere interaction
    • 43. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology, Meteorology, Oceanography, Terrestrial Ecosystems Modelling the Carbon Cycle From O’Connor et al. 2011 (Met Office Hadley Centre) Future Methane Emissions
    • 44. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology, Meteorology, Oceanography, Terrestrial Ecosystems, Marine Ecosystems Chlorophyll (April 2008) Phytoplankton (algal) blooms around the UK Image from Western Channel Observatory Chlorophyll from the Met Office’s NEMOShelfERSEM operational model. The yellow and orange regions show areas of algal blooms.
    • 45. Mathematics, Computer Science, Newtonian Physics, Moist Thermodynamics, Radiative Transfer, Particle Microphysics, Chemistry, Biology, Meteorology, Oceanography, Terrestrial Ecosystems, Marine Ecosystems, Cryosphere....... 2012 1980 Loss of Arctic Summer Sea Ice Met Office Climate Model: Understanding the Arctic energy budget
    • 46. Putting it all together: Holistic Earth System Basic Constraints: Energy Input from the Sun, Rotation Rate of the Planet, (Atmospheric Composition) It works! Fundamental constraints. AR5 model biases or HadGEM2-ES results? © Crown copyright Met Office
    • 47. It Works! Sea Surface Temperature biases in Met Office Earth System Model (HadGEM2-ES) Observations HadGEM2-ES Storm Tracks in observations and HadGEM2-ES
    • 48. Climate modelling: A Predictive Science
    • 49. Taking the Earth into uncharted territory?
    • 50. Human Perturbations to the Carbon Cycle
    • 51. Results from my first study on CO2: The effects of doubling CO2 concentration on Radiative-Convective equilibrium Effect of doubling CO2 based on two cumulus convection schemes NO CLOUDS T(K) 270 280 290 300 DT(PC) 1.52 1.57 1.65 1.70 DT(CA) 1.56 1.68 1.92 2.46 WITH CLOUDS T(K) 270 280 290 300 DT(PC) 1.40 1.44 1.40 1.40 DT(CA) - 1.64 1.88 2.20 © Crown copyright Met Office
    • 52. Projections of future temperature rise • Global warming >2˚C is likely for scenarios with little mitigation of emissions. No mitigation leads to a world more than 4˚C warmer than pre-industrial times Inter-Governmental Panel on Climate Change (2013)
    • 53. Projections of future sea level rise Long Term Commitment to Climate Change • Global average sea level will rise during the 21st century; it is very likely that it will rise faster than it has during the last 40 years. Inter-Governmental Panel on Climate Change (2013)
    • 54. There will be large geographical variations Inter-Governmental Panel on Climate Change (2013)
    • 55. So if climate models are such an achievement, why are we still uncertain? Relative importance of each source of uncertainty in decadal mean surface air temperature predictions VARIABILITY Uncertainty comes from: • Natural variability • Model uncertainty • Scenario uncertainty SCENARIO MODEL © Crown copyright Met Office From Hawkins and Sutton (2009)
    • 56. Representing Unresolved Processes: Parametrization Boundary layer turbulence and mixing Radiation Cumulus convection Precipitation Clouds and microphysics Effects of mountains Atmospheric composition
    • 57. Climate modelling: Helping us Plan for a Safe and Sustainable Future
    • 58. „Circle of Securities‟ Water Migration Economic Climate Variability and Change Health Urbanisation Population growth Political Energy Food
    • 59. Climate Service UK Working together to prepare for tomorrow • Saving lives and livelihoods • Delivering resilience and preparedness • Making wise choices for future adaptation • Avoiding dangerous climate change • Supporting growth and the green economy © Crown copyright Met Office © Crown copyright Met Office
    • 60. • 1953 East coast storm surge killed 307 in the UK and flooded 32,000 industrial facilities • Estimated £200bn value of property in Thames floodplain, 1.1 million employees, 55,000 properties • TE2100 science avoided up to £20bn capital expenditure through more robust predictions and scenarios © Crown copyright Met Office
    • 61. To Recap • Based on fundamental and immutable laws • Include many science disciplines – ‘renaissance’ science • Arguably the largest and most complex codes ever written • Simulate the wealth of processes and phenomena in the climate system • Enable us to understand how the climate system works • Enable us understand why climate is changing • Enable us to ‘see into the future’ and take action Scale of the Enterprise to match the Scale of
    • 62. ‘For the Relief of Man’s Estate’ “For men have entered into a desire of learning and knowledge, sometimes upon a natural curiosity and inquisitive appetite; sometimes to entertain their minds with variety and delight; sometimes for ornament and reputation; and sometimes to enable them to victory of wit and contradiction; and most times for lucre and profession; and seldom sincerely to give a true account of their gift of reason, to the benefit and use of men: …… a rich storehouse, for the glory of the Creator and the relief of man's estate. “ Francis Bacon, The Advancement of Learning (1605)
    • 63. “I do not know what I may appear to the world, but to myself I seem to have been only like a boy playing on the seashore, and diverting myself in now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me.” Isaac Newton Climate Modelling – Work in Progress
    • 64. Why Climate Models are the Greatest Feat of Modern Science Have I convinced you?

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