1. Climate Modeling Research & Applications in Wales John Houghton C 3 W conference, Aberystwyth 26 April 2011

2. Computer Modeling of the Atmosphere & Climate System has revolutionized Weather Forecasting and Research Climate Prediction and Research

3. Computer Modeling of the Atmosphere & Climate System Identifies: starting conditions for weather or climate Integrates: the dynamical equations of motion the physical equations of state, energy etc algorithms describing all relevant processes NOT based on empirical or statistical information

4. Parameters & Physical Processes included in a Computer Model of the Atmosphere

5. Horizontal Grids for Global and Regional Models

6. UK Met Office jp05

7. Weather shows large variability in space and time Detailed weather forecasting only possible 10 to 30 days ahead Climate (= average weather) also shows large variability Is forecasting of human influence on climate a possibility?

8. Components of the Climate System Atmosphere Oceans Cryosphere Land Surface Biosphere All these components interact closely

9. Parameters & Physical Processes included in a Coupled Atmosphere – Ocean Global Climate Model

10. Schematic of the Climate System from IPCC Report 2007

11. Computer Modeling of the Climate an essential tool that provides the means to add together all the non-linear processes and effects including positive & negative feedbacks Essential for estimating future climate

12. Section of model grid in a typical global climate model in 1990 (a) and 2007 (b)

13. Climate (= average weather) shows large variability from month to month, year to year Global Climate (= patterns of climate averaged over globe) shows clear response to external forcing factors, e.g. Changes in Solar Radiation Volcanoes Greenhouse gases

14. Predicted & Observed changes in Global Average Temperature after the eruption of Mount Pinatubo in 1991 from IPCC Report 1996

15. Changes in Global Mean Temperature in 20 th century as observed (black) as simulated by ensemble of models (red & blue) – with natural and anthropogenic forcings (a) - with natural forcings only (b) From IPCC Report 2007

16. Patterns of Chaos

17. LORENZ ATTRACTOR A solution of set of three coupled differential equations, dx/dt = σ (y - x), dy/dt = x ( ρ - z) - y, dz/dt = x y - β z, that arise in studies of atmospheric convection

18. Lorenz Attractor distorted by External Forcing (after Palmer 1999)

19. Future Climate under increased Greenhouse Gas Emissions

20. The enhanced greenhouse effect with doubled CO 2 S, L = global average values of incoming solar & outgoing long wave radiation at top of atmosphere

21. Some main impacts of climate change More intense heat waves Sea level rise More intense hydrological cycle jp14

22. Projected changes in annual temperatures for the 2050s The MetOffice. Hadley Center for Climate Prediction and Research.

23. More rain for some; less rain for others Jun-Jul-Aug changes by 2090s Precipitation increases very likely in high latitudes Precipitation decreases likely in most subtropical land regions From Summary for Policymakers, IPCC WG1 Fourth Assessment Report

24. Increased global average surface temperature leads on average to: More evaporation of water vapour from oceans More water vapour in atmosphere More average precipitation (as now observed) More latent heat release into atmosphere* More intense hydrological cycle Increase in risk of floods and droughts * from condensation of water vapour - a large source of energy

25. Proportion of land surface in drought - 3 computer simulations under A2 Emissions Scenario (after E Burke et al, Hadley Centre)

26. Proportion of land under extreme drought (from Burke 2006) 1980 ~ 1% 2005 ~ 3% 2040 (+2 deg) ~ 8% 2070 (+3 deg) ~ 18%

27. Some Feedbacks in the Climate System Water-vapour feedback Cloud – Radiation feedback Ocean Circulation Feedback Ice – Albedo feedback CO 2 fertilization effect Climate/carbon-cycle feedback

28. Cloud -Radiation Feedback largest contributor to uncertainty in climate sensitivity to increase in greenhouse gases

29. Physical Processes associated with Clouds lead to feedbacks both +ve (high clouds) & -ve (low clouds)

30. Clouds influence average temperature + 3% High Clouds + 0.3º + 3% Low Clouds– 1.0º

31. Polluted clouds have smaller particles - leading to more reflection of sunlight from the cloud top, less radiation at the surface, less precipitation & longer cloud lifetime

32. Annual mean net Cloud Radiative Forcing (Mar 2000 - Feb 2001) CERES instrument on NASA Terra satellite from King et al Our Changing Planet

33. Ocean circulation feedback

34. Estimates of Heat Transport by the Oceans (terawatts, 10 12 W ) Note -average solar radiation on 10 6 km 2 ~ 250 terawatts,

35. How can models be validated? Comparison with Recent Climate Comparison with Past Climates Comparison with particular events

36. Sources of Climate Data Instruments, in-situ, passive & active remote sensing, mounted on satellites, aircraft, balloons, ships, buoys, land surface etc

37. Envisat - 2002 Nimbus - 1970s jp02

38. Instruments on ESA’s Earth Observation Satellite, ENVISAT Passive AATSR MIPAS MERIS SCIAMACHY MWR GOMOS Active RA-2 ASAR DORIS

39. Illustrating Data Overload

40. Examples of Climate Modeling Research Projects How well can models describe extreme weather? How well can models forecast extreme climate events e.g. floods, droughts, storms etc – timing & location? Cloud- Radiation Feedback What is its average sign & size of how do they vary? How well do models describe Ocean-Circulation Feedback on Climate? What are the influences of particles (aerosols) on climate? What is the relative influence of different greenhouse gases? How can human communities adapt to climate change? What model improvements could best help mitigation policy? What can we learn from past climates? How can models represent sub-grid-scale motions more accurately?

41. Possible Collaborations for C 3 W in Climate Modeling with Met Office with European partners etc