Background

1. Background • WGOMD is about to discuss experimental setup to asses ocean model performance in the representation of the inter-annual variability. Possibility of X-Panel interaction and feedback. • The GCMS have large errors in the Pacific basin and ENSO, and large uncertainty about the causes. • Suggestion: to conduct, in addition to the “MAIN” experiment, a series of sensitivity ocean-only experiment that could give guidance on which elements are key for improvement of the Pacific climate simulations. • As additional information: • Seasonal forecasts is an ideal test bed to asses the quality of the GCMS used in future climate projections: • Need ocean initial conditions to carry out experiments • Not all the groups have ocean data assimilation systems in place. => The “MAIN” experiment may be used as initial conditions in coupled model forecasts.

2. Questions from the Pacific Panel • There are known model deficiencies in the representation of the Pacific climate: • Upwelling off the South American Coast (winds, resolution…?) • Cold tongue penetrating too far west (winds? momentum mixing…?) • Too weak/too strong east-west slope of the thermocline • Equatorial heat content (IT/meridional transport, vertical mixing) • … • Is it possible to say which are the dominant source of error? • Forcing fields? • Model parameterizations/configuration? • Model resolution? • Parameterization of air-sea interaction?

3. Suggestion • Conduct a long ocean model simulation (20-40 years) with a variety of models, using inter-annually varying atmospheric forcing. This will be the “MAIN” integration, long integration can be used as: • a reference experiment to diagnose and answer some of the above questions (see later) • To provide initial conditions for concerted seasonal forecast experiments.? • Conduct additional integrations with each model if possible (no compulsory), to test sensitivities. • Different forcing fields • Different resolution • Different parameterization, bulk formulae, …. It could be good to see these sensitivities from more than one model.

4. Sensitivities: Compute and Compare • Sensitivity to Forcing fluxes: • Sensitivity to Resolution: • Sensitivity to Model: • Sensitivity to Bulk Formula: • Sensitivity to P-parameterization:

5. Example: • Diagnosing the sources of uncertainties in the Ocean Analysis intercomparison project organized by GSOP. • Analyses with and without data assimilation • Different analyses use different forcing fields • Different analyses use different models • Models have different resolutions • The analyses are clustered according to some criteria, and the standard deviation of the cluster is used as a measure of uncertainty.

6. Sources of Uncertainty in GSOP ocean analsysis intercomparison All Forcing is ERA40 ERA40-No data assimilation ERA40-With data assimilation

7. EQPAC EQATL EQIND TRPAC TRATL NPAC NATL GLOBAL Assimilation and Uncertainty T300 Sources of Uncertainty in GSOP ocean analysis intercomparison Long period 1956-2005: A large source of uncertainty are the forcing fluxes. 1956-2005 ALL ERA40 as FORCING OCEAN MODEL ASSIMILATION SCHEME FORCING~ ALL–ERA40

8. The sensitivity experiments can be done and diagnosed within each group without need of big volumes of “data” transfers. • Not all the groups need to carry “all” and the same the sensitivity experiments. • It would be interesting to measure the sensitivities both in in the mean state and in the interannual variability. • Other basin panels will be interested in the outcome,