1. What is a climate model?

2. Substitutes for reality Closely mimics some essential elements Omits or poorly mimics non-essential elements What is a Model?

3. 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

4. 1.Energy from the Sun (energy from the interior) 2.Planetary Albedo 3.Speed of Planet’s Rotation 4.Mass of the Planet 5.Radius of the Planet 6.Atmospheric Composition 7.Ocean-Land, Topography S (depends on Sun itself and distance from Sun)   M a H 2 O, CO 2, O 3, clouds h* The Climate of a Planet Depends On …

5. Example: Energy Balance Model Solar Radiation S = 1361 Wm -2 (plane, parallel) In equilibrium, INCOMING ENERGY = OUTGOING ENERGY (1 -  ) S  a 2 = E (4  a 2 ) E = 1/4 (1 -  ) S Measured albedo (  ) = 0.30 Measured planetary E = 238 Wm -2 Implied T E = 255 K (Note: Water freezes at 273 K) Planetary Emission This is a VSCM: Very Simple Climate Model Experts prefer a GCM: Global Climate Model (General Circulation Model)

6. Earth’s Energy Balance Solar Radiation S = 1361 Wm -2 (plane, parallel) Assume radiative equilibrium, so that INCOMING ENERGY = OUTGOING ENERGY (1 -  ) S  a 2 = E (4  a 2 ) E = 1/4 (1 -  ) S Measured albedo (  ) = 0.30 Measured planetary E = 238 Wm -2 Implied T E = 255 K Planetary Emission Measured surface E s = 390 Wm -2 Atmosphere absorbs 152 Wm -2 Measured T s = 288 K WHY?? The Greenhouse Effect

7. … But it’s a little more complicated than that …

8. CLIMATE DYNAMICS OF THE PLANET EARTH S Ω a g T4T4 WEATHERWEATHER C LI M A T E. 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)

9. Climate System Theory Discretization

10. Climate System Theory Discretization

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

12. Climate System Theory Discretization Equations of motions and laws of thermodynamics predict rate of change of: T, P, V, q, etc. (A, O, L, CO 2, etc.)

13. Climate System Theory Discretization Equations of motions and laws of thermodynamics predict rate of change of: T, P, V, q, etc. (A, O, L, CO 2, etc.)

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

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

16. 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?

17. Moore’s “Law” IPCC-1 IPCC-2 IPCC-3 IPCC-4 10 3 -fold jump since 1st IPCC 10 6 -fold jump in last 30 years Latest advance due to dual-core chips Near-term advance w/quad-core chips

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

19. Climate Models circa early 1990s Global coupled climate models in 2007 and new ESMs New decadal prediction models Global coupled models in 5 yrs post-AR5 ~500 km~100 – 200 km ~50 km~10 km

20. We ran 7-km grid on 640 nodes (2560 cores), because constrained by memory per core on Athena … more grid bisections means more “ghost rows” means more memory demand NICAM Domain Decomposition

25. 19901996 20012007 The complexity of global climate models has increased enormously over the last 20 years, as shown in this flow chart. Beneath each time period is a list of the components included in state-of-the-art models such as the NCAR-based Community Climate System Model (Warren Washington, NCAR)

26. Ultimate: all physico-biogeochemical Earth System

27. Balancing future demands on computing power Duration and/or Ensemble size Resolution Computing Resources Complexity 1/12 0 EO, Data Assimilation

28. Model Grid Size (km) & Computing Capability Peak Rate:10 TFLOPS100 TFLOPS1 PFLOPS10 PFLOPS100 PFLOPS Cores 1,400 (2005) 12,000 (2007) 80-100,000 (2009) 300-800,000 (2011) 6,000,000? (20xx?) Global NWP 0 : 5-10 days/hr 18 - 298.5 - 144.0 - 6.31.8 - 2.90.85 - 1.4 Seasonal 1 : 50-100 days/day 17 - 288.0 - 133.7 - 5.91.7 - 2.80.80 - 1.3 Decadal 1 : 5-10 yrs/day 57 - 9127 - 4212 - 205.7 - 9.12.7 - 4.2 Climate Change 2 : 20-50 yrs/day 120 - 20057 - 9127 - 4212 - 205.7 - 9.1 Range: Assumed efficiency of 10-40% 0 - Atmospheric General Circulation Model (AGCM; 100 vertical levels) 1 - Coupled Ocean-Atmosphere-Land Model (CGCM; ~ 2X AGCM) 2 - Earth System Model (with biogeochemical cycles) (ESM; ~ 2X CGCM) * 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 Thanks to Jim Abeles (IBM)