Effect of Tropical Biases on ENSO Simulation and Prediction

Effect of Tropical Biases on ENSO Simulation and

PredictionEd Schneider and Ben Kirtman

George Mason University

COLA

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?

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.

Globally Uniform Specified SST:Precipitation Response

Slab Mixed Layer Ocean

SST

Precip

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).

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.

Annual Means

Precipitation

SST

OBS

COLA

CCM3

COLA minus CCM3

Annual Cycle of SST in the Equatorial Pacific

SST Anomalies in the Equatorial Pacific

Annual Mean SST in the Equatorial Pacific from Experiments

A1 A2 A3 A4

A5 A6 A7 A8

A9 B1 B2 B3 CAC Analysis

Annual Cycle of SST in the Equatorial Pacific (Experiments)

Standard Deviation of SST Anomalies in the Equatorial Pacific

(Experiments)

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.

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, 1x1 L40 or 1.5x1.5 L25, 65S-60N domain.

• GFDL ODA for ocean initial state.

NINO3 SSTA Correlations

Systematic Bias E. Pacific SST

Standard Deviation Simulations in the Equatorial Pacific

COLA med

ECHAM med

CCM med

Systematic Bias Equatorial Pacific SST Anomalies

Analysis

Consensus

COLA high

COLA med

ECHAM high

ECHAM med

CCM med

Systematic Bias Equatorial Pacific Heat Content (VAT) Anomalies

Analysis

Consensus

COLA high

COLA med

ECHAM high

ECHAM med

CCM med