1. Effect of Tropical Biases on ENSO Simulation and Prediction Ed Schneider and Ben Kirtman George Mason University COLA

2. Overview of COLA Research Topics Related to Tropical Biases Basic problem: What causes the ITCZ? Why do coupled models have different biases? What effect do biases have on ENSO prediction?

3. What Causes the ITCZ? Kirtman and Schneider, 2000, JAS. Minimal general circulation: RCE (Radiative- Convective Equilibrium) or something else? Expect something else if the ITCZ has a dynamically preferred position (e.g. due to Ekman dynamics). –Aqua planet AGCM (T30L18) –Uniform SST everywhere –Meridionally uniform incident solar radiation Result: something else.

4. Globally Uniform Specified SST: Precipitation Response

5. Slab Mixed Layer Ocean SST Precip

6. Interpretation The ITCZ has a preferred location, which leads to a self sustaining large scale general circulation in the absence of meridional forcing. Necessary ingredients: convective instability (heating from below) + rotation. Eddy momentum fluxes play a role. In our model, the preferred location is the equator (3D) or oscillating around the equator (2D).

7. Why Do Coupled Models Have Different Tropical Biases? Compare COLA and CCM3 coupled to MOM2 (Schneider, 2002, J. Climate). Different annual mean, annual cycle, SI variability. Eliminate structural and parameterized differences between the models step by step.

8. Annual Means Precipitation SST OBS COLA CCM3 COLA minus CCM3

9. Annual Cycle of SST in the Equatorial Pacific

10. SST Anomalies in the Equatorial Pacific

11. Annual Mean SST in the Equatorial Pacific from Experiments

12. Annual Cycle of SST in the Equatorial Pacific (Experiments)

13. Standard Deviation of SST Anomalies in the Equatorial Pacific (Experiments)

14. Effect of Systematic Biases on ENSO Forecasts Schneider, DeWitt, Rosati, Kirtman, Ji, and Tribbia, 2003, Mon. Wea. Rev. (submitted). Biases in mean translate in forecasts to systematic drift of SST from initial state (obs.) to model climate + initial shock. Biases in variability lead to systematic drift in variability away from obs. and towards model climate with a time scale of several months.

15. Experiments A single 12 month forecast for each Jan. 1 and July 1 observed (ocean) initial state, 1980-1999 (40 cases) for each of 5 coupled model configurations. AGCM: COLA V2, ECHAM4.5, CCM3 at T42, 18/19 levels. OGCM: MOM3, “IRI” physics, 1  x1  L40 or 1.5  x1.5  L25, 65  S-60  N domain. GFDL ODA for ocean initial state.

16. NINO3 SSTA Correlations

17. Systematic Bias E. Pacific SST

18. Standard Deviation Simulations in the Equatorial Pacific COLA med ECHAM med CCM med

19. Systematic Bias Equatorial Pacific SST Anomalies Analysis Consensus COLA high COLA med ECHAM high ECHAM med CCM med

20. Systematic Bias Equatorial Pacific Heat Content (VAT) Anomalies Analysis Consensus COLA high COLA med ECHAM high ECHAM med CCM med