1. What is a climate model? What is a climate model? If we cannot predict weather, how can we predict climate? Jagadish Shukla CLIM 101: Weather, Climate and Global Society Lecture 11: Oct 6, 2009

2. Reading for Week 6 Lecture 11 What is a climate model? GW Chapter 5 IPCC WG1 Chapter 8, FAQ 8.1 How Reliable Are the Models Used to Make Projections of Future Climate Change?

3. IPCC has been established by WMO and UNEP to assess scientific, technical and socio- economic information relevant for the understanding of climate change, its potential impacts and options for adaptation and mitigation. Intergovernmental Panel on Climate Change (IPCC) Working Group I: The Physical Science Basis Working Group II: Impacts, Adaptation and Vulnerability Working Group III: Mitigation of Climate Change Largest number of U.S. scientists: nominated by the U.S. Govt. Highest skepticism : “U.S. Govt.”

4. Quantitative and/or qualitative representation of natural processes (may be physical or mathematical) Based on theory Suitable for testing “What if…?” hypotheses Capable of making predictions What is a Model?

5. Input DataModelOutput Data Tunable Parameters What output data might we consider for a typical climate model? What input data might we consider for a typical climate model? What are the tunable parameters of interest? What is a Model?

6. Dynamics Physical processes Climate System Modeling Atmospheric General Circulation Model Basic Equations

7. CLIMATE DYNAMICS OF THE PLANET EARTH S Ω a g T4T4 WEATHERWEATHER CLIMATE. CLIMATE. hydrodynamic instabilities of shear flows; stratification & rotation; moist thermodynamics day-to-day weather fluctuations; wavelike motions: wavelength, period, amplitude S,, a, g, Ω O 3 H 2 O CO 2 stationary waves (Q, h*), monsoons h*: mountains, oceans (SST) w*: forest, desert (soil wetness)  (albedo)

8. (approximation) Mass conservation Energy conservation Newton’s law  = p / p s

9. Equations of motions and laws of thermodynamics to predict rate of change of: T, P, V, q, etc. (A, O, L, CO 2, etc.) 10 Million Equations: 100,000 Points × 100 Levels × 10 Variables With Time Steps of: ~ 10 Minutes Use Supercomputers What is a Climate Model?

10. Discretization Atmosphere and ocean are continuous fluids … but computers can only represent discrete objects

11. Discretization Atmosphere and ocean are continuous fluids … but computers can only represent discrete objects

12. John von Neumann Seymour Cray & Cray-1 ENIAC IBM 360 Cray-2 Columbia NASA

13. Weather Prediction Future pressure = current pressure + (rate of change of pressure) x  t Future temperature = current temp. + (rate of change of temp.) x  t Current pressure & temperature: use global observations For rate of change: use mathematical equations For producing forecast: use supercomputers

14. Sea Level Pressure (mb) & Precipitation Rate (mm/12Hr) 00Z Tue 10 Nov 1998

15. Sea Level Pressure (mb) & Precipitation Rate (mm/12Hr) 12Z Tue 10 Nov 1998

16. Sea Level Pressure (mb) & Precipitation Rate (mm/12Hr) 00Z Wed 11 Nov 1998

17. Numerical Weather Prediction 1.Determine (continuous) equations to be solved –Equation of state or Ideal Gas Law (Boyle’s Law relates P  V, Charles’ Law relates V  T, Gay-Lussac’s Law relates T  P) –Conservation of mass (dry air, water) –Conservation of energy –Conservation of angular momentum –Result: set of coupled, nonlinear, partial differential equations 2.Discretize the equations for numerical solution (typically requires computer) 3.Measure current state of global atmosphere to obtain initial conditions 4.Solve the initial value problem to produce a forecast 5.Take into account uncertainty in measured atmospheric state by repeating step 4 over an ensemble of slightly different initial conditions

25. Science Predictability in the Midst of Chaos: A Scientific Basis for Climate Forecasting 23 October 1998, Volume 282, pp. 728-731 J. Shukla Soil Wetness SST Anomalies ( o C)

26. 1998 JFM SST [ o C] JFM SST Climatology [ o C] 1998 JFM SST Anomaly [ o C] El Nino/Southern Oscillation

28. Rainfall Anomalies

29. Vintage 2000 AGCM Model Simulation of ENSO Effects 500 hPa Height Anomalies (ACC = 0.98)

30. European Heat Wave 2003 European Heat Wave 2003

31. JJA 2003 SST Anomaly

32. JJA obs OBS.SST-CLIM.SST exp. result significant at more than 90% sig.lev.

33. 2003 Heat wave hits Europe 30,000 people die in Western Europe observations HadCM3 Medium-High (SRES A2) 2003 2040s 2060s Temperature anomaly (wrt 1961-90) °C GEC is more acute than ever GEC is more acute than ever

36. Courtesy of P. Houser (GMU)

38. 200 km

40. Computing Capability & Global Model Grid Size (km) Peak Rate:10 TFLOPS100 TFLOPS1 PFLOPS10 PFLOPS100 PFLOPS Cores (1 st year available) 1,400 (2006) 12,000 (2008) 80-100,000 (2009) 300-800,000 (2011) 6,000,000? (20xx?) Global NWP 0 : 5-10 days/hr 18 - 298.5 - 14 4.0 - 6.3 (~20X10 6 points) 1.8 - 2.90.85 - 1.4 Seasonal 1 : 50-100 days/day 17 - 288.0 - 13 3.7 - 5.9 (~20X10 6 points) 1.7 - 2.80.80 - 1.3 Decadal 1 : 5-10 yrs/day 57 - 9127 - 42 12 - 20 (~2X10 6 points) 5.7 - 9.12.7 - 4.2 Climate Change 2 : 20-50 yrs/day 120 - 20057 - 91 27 - 42 (~0.5X10 6 points) 12 - 205.7 - 9.1 Range: Assumed efficiency of 10-40% 0 - Atmospheric General Circulation Model (AGCM; 100 levels) 1 - Coupled Ocean-Atmosphere-Land Model (CGCM; ~ 2X AGCM computation with 100-level OGCM) 2 - Earth System Model (ESM; ~ 2X CGCM computation) * Core counts above O(10 4 ) are unprecedented for weather or climate codes, so the last 3 columns require getting 3 orders of magnitude in scalable parallelization (scalar processors assumed; vector processors would have lower processor counts) Thanks to Jim Abeles (IBM)

41. Geographic resolution characteristic of the generations of climate models used in the IPCC Assessment Reports: FAR (IPCC, 1990), SAR (IPCC, 1996), TAR (IPCC, 2001a), and AR4 (2007). The figures above show how successive generations of these global models increasingly resolved northern Europe. These illustrations are representative of the most detailed horizontal resolution used for short-term climate simulations. The century-long simulations cited in IPCC Assessment Reports after the FAR were typically run with the previous generation’s resolution. Vertical resolution in both atmosphere and ocean models is not shown, but it has increased comparably with the horizontal resolution, beginning typically with a single- layer slab ocean and ten atmospheric layers in the FAR and progressing to about thirty levels in both atmosphere and ocean.

49. Center of Ocean-Land- Atmosphere studies Projection of Global Warming Mean of 15 Models Surface Air Temperature Difference (Sresa1b YR 71-100) minus (20c3m 1969-98), Global Average = 2.61

50. IPCC 2007 1.0º C Increase in Surface Temperature Observations Predictions with Anthropogenic/Natural forcings Predictions with Natrual forcings

51. Center of Ocean-Land- Atmosphere studies J. Shukla, T. DelSole, M. Fennessy, J. Kinter and D. Paolino Geophys. Research Letters, 33, doi10.1029/2005GL025579, 2006 Climate Model Fidelity and Projections of Climate Change

52. Summary 1.Weather prediction depends on initial conditions (global observations). 2.Short-term climate (seasonal-decadal) depends on boundary conditions (SST, soil wetness, snow, sea ice, etc.), which depends on ocean-atmosphere interactions. (natural forcings: sun, volcanoes, etc.) 3. Long-term climate change depends on “exteranal” forcings (Human: greenhouse gases, land cover change, etc.)

53. THANK YOU! ANY QUESTIONS?

58. Using the secant approach, we can approximate the temperature equation: By reducing  t, we can obtain an increasingly accurate solution.

59. Using the secant approach, we can approximate the temperature equation: By reducing  t, we can obtain an increasingly accurate solution.

60. Numerical Weather Prediction: Data Assimilation Cycle