1 / 20

Effect of Tropical Biases on ENSO Simulation and Prediction

Effect of Tropical Biases on ENSO Simulation and Prediction. Ed 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?

kylar
Download Presentation

Effect of Tropical Biases on ENSO Simulation and Prediction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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 Precip SST

  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 COLA minus CCM3 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

More Related