Climate System Models and Climate Science

1. Climate System Models and Climate Science Yuqing Wang International Pacific Research Center and Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, USA The 8th International Seminar on Climate System and Climate Change

2. Contents • Climate System and Climate Science • Climate System Models (CSMs) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

3. Contents • Climate System and Climate Science • Climate System Models (CSMs) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

4. Climate System and Climate Science – Climate System • Climate system is different from any weather system. Climate system is the system on the earth that determines climatology, climate variability, and their long-term trends at various space and time scales. • Climate system consists of atmospheric circulation, ocean circulation, terrestrial processes, and cryospheric processes. Among each system, there are many subsystems that may include weather systems which contribute to the climate system in a statistical way.

5. Climate system and interactions among components

6. Energy budget of the earth and heat conversion under different forms. Greenhouse effect of the atmosphere (IPCC AR4).

7. IR WV 14 June 2006 at 06:00 UTC

9. Climate System and Climate Science – Climate Science • Climate science is the science that deals with all aspect of climate and its changes and understand the involved physical processes and feedbacks. • Climate science aims to (1) define the climatic features and variabilities at various time scales, (2) reconstruct past climate changes, (3) predict future climate changes, (4) quantify climate feedbacks, and (5) understand various climate processes, including coupled processes among different climate systems. • Climate science also includes to study the impact of climate and its changes on societal activities, economic development, agriculture, and earth’s ecosystems.

10. Contents • Climate System and Climate Science • Climate System Models (CSMs) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

11. Climate System Models (CSMs) • A climate system model (CSM) is a mathematical system based on well-established physical principles and is solved numerically using supercomputer. • A CSM includes all individual climate components (atmosphere, ocean, biosphere, hydrosphere, land, and sea ice) and their interactions. • A CSM is expected to quantitatively reproduce observed present-day climate and past climate changes. • A CSM is expected to provide reliable projections of future climate changes

12. CSMs and Climate Science • CSMs provide quantitative description of the climate systems and their interactions; • CSMs made the finding of global warming and the subsequent climate projections possible; • CSMs contribute to the quantitative evaluation of climate processes and climate feedbacks in the climate system; • Climate science is promoting the rapid advance in the development and improvements of CSMs.

13. Climate System Models • The main task of climate modelers is to take their knowledge of local interactions of air masses, water, energy, and momentum and from that knowledge explain the climate system's large-scale features, variability, and response to external forcings. • Despite the complexity of the climate system and though far from complete, the results so far have been successful. That is why CSMs have become one of the major research tools in the climate science.

16. Processes in an atmospheric GCM

17. Dynamical Core of a CSM Each CSM has its dynamical core, which solves the adiabatic processes, such as the Navier-Stokes equations. The key is to determine how to discretize the equations of motions • Grid point models • Longitude/latitude grid • Icosahedral grid • ……..... • Two types of grid system: • Uniform grid • Stretching grid • Spectral models

18. Icosahedral grid for the horizontal mesh structure glevel-0 glevel-1 glevel-3 glevel-5 • Super computer: Earth Simulator, JAMSTEC Earth Simulator (JAMSTEC)

19. Physics in a CSM The physics in CSMs can be divided into two categories: • The first includes physics that is well known in theory, but that in practice must be approximated due to discretization of continuous equations. Examples include the transfer of radiation through the atmosphere. • The second category contains empirically known physics, such as formulas for evaporation as a function of wind speed and humidity.

20. Physics in a CSM Many small physical processes could not be resolved by the model resolution, and need to be included with the known large-scale parameters. This is called physics parameterizations. The following processes are generally parameterized in a CSM • Cumulus convection for sub-grid convective process • Cloud microphysics for grid scale moist processes • Turbulent mixing (PBL), including surface fluxes • Clouds, in particular, subgrid cloud fraction • Aerosol-cloud interaction • Land surface processes • Gravity waves due to subgrid scale orography or deep convection • Sea ice processes • So on

22. An example: Cumulus Parameterizations • How does the large-scale weather pattern control the initiation, location, and intensity of convection? • How does convection modify the environment? • What are the properties of parameterized clouds?

25. How does the large-scale weather pattern control the initiation, location, and intensity of convection? • Some convective instability (positive area on a thermodynamic diagram) in the atmosphere at a grid point so that perturbed parcels can reach their level of free convection; • The existence of low-level and/or vertically-integrated mass or moisture convergence that exceeds some threshold at a grid point; • The rate of destabilization by the environment.

26. Tiedtke (1989)

27. Another example: A new development - the thermals in the PBL • Small-scale isotropic turbulence → turbulent mixing‏ • Atmospheric Turbulence: • “meso-scale”, organized eddy mixing « Thermal plumes model » Each atmospheric column is separated into two parts: one ascending from the surface and another descending around the plume. We try to represent an average plume and an average cloud, not individual ones. 20 km 200 km

28. Unresolved processes: transport and chemistry model The 1991 eruption of Mount Pinatubo in the Philippines produced sulfate aerosols that affected climate for years and offered climate modelers an unprecedented opportunity to compare models with observations.

30. Evolution of climate models (1990) (1996) (2001) (2007) Courtesy IPCC

31. Observation vs. NICAM MTSAT-1R NICAM MJO-organized clouds MJO-organized clouds TS Isobel TS Isobel Dec. 29 2006 Dec. 29 2006

32. Observation vs. NICAM MTSAT 0000UTC 2 Jan. NICAM 0000UTC 2 Jan. MJO-organized clouds MJO-organized clouds TS Isobel TS Isobel Surface rain rate (mm hour-1) by TRMM-TMI Surface rain rate (mm hour-1) by NICAM 0920 UTC 2 Jan. Latitude 2230 UTC 2 Jan. Longitude Longitude NICAM reasonably produced not only the large-scale circulation, such as the MJO, but also the embedded mesoscale convective systems, such as TC rainbands.

33. Output from High Resolution Model (Earth Simulator)

34. Global warmingGreenhouse gases in the atmosphere (mostly water vapor, clouds, carbon dioxide, and methane) exert strong controls over how fast the Earth loses IR energy to outer space

35. Contents • Introduction • Climate System Models (CSM) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

36. Evaluation of CSMs • A CSM should reproduce observed present-day climate, including mean and variabilities on various time scales and past climate changes • Attention needs to be paid to the scale equivalence in the model evaluation • Evaluation should include the realistic reproduction of feedbacks and sensitivities and also include the uncertainties-variances of various model fields

37. Frequency (%) of daily precipitation rate over land between 20oN and 20oS from GPCP and TRMM observations (1999-2008), from 20th century runs of CCSM4 at 1o and 2o, and CCSM3 at T85, all (1990-1999). All data are interpolated to the 2o CAM4 grid

38. Mean SST along the equation in the Pacific, and annual cycle of SST from observation and from CCSM4 and CCSM3 runs

39. Difference in mean soil water content (mm) between MAM and SON

41. Time series of Arctic sea ice extent (106 km2) in September from observation for 1979-2009 and CCSM4 ensemble runs.

42. Contents • Introduction • Climate System Models (CSM) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

43. Uncertainties in CSMs • The CSM equations are only approximations of the physical processes that occur in the climate system. • While some of those approximations are highly accurate, some of the most important ones are unavoidably crude. • This is because the real processes are either • too complex to include in the model and still have the model run fast on a computer, or • our understanding of those processes is still too poor to accurately model them with equations.

44. Uncertainties in CSMs • Unrealistic representation of physical processes • Uncertainty in model physics parameterizations • Uncertainty in the measured quantities (atmospheric compositions, for instance) • Uncertainty in the convergence of the model solutions • Intrinsic chaotic nature of the climate system itself • Ensemble mean based on individual model or multiple models can reduce the uncertainty considerably and help measure the uncertainty as well

46. Global mean surface air temperature from observations (black) and from simulations produced by 14 GCMs driven by both natural and human-caused factors (red).

47. Uncertainties in Climate Model Cloud and Water Vapor Processes

48. Contents • Introduction • Climate System Models (CSM) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments

49. Reliability of CSMs • There is considerable confidence that CSMs provide credible quantitative estimates of future climate change, particularly at continental scales and above. • This confidence comes from the foundation of CSMs in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes. • Confidence in model estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). • Over several decades of development, models have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases.

50. Contents • Introduction • Climate System Models (CSM) • Evaluation of CSMs • Uncertainties in CSMs • Reliability of CSMs • Applications of CSMs to Climate Science • Prospectus for Future Developments