Using Data and Intermediate Coupled Models for Seasonal-to-Interannual Forecasts

Abstract

This paper provides a detailed illustration that it is beneficial for ENSO forecasting to improve in priority the model parameterizations, instead of increasing only the consistency of the initial conditions with the coupled model. Moreover it is shown that the latter can lead to misleading results. Using sea level data in addition to wind to initialize the Cane and Zebiak model does not improve El Niño forecasts. Nudging the observed wind to the model one to initialize the forecasts as proposed by Chen et al. also fails to correct the model deficiencies and degrades the initial conditions of the ocean and atmosphere. These failures are explained by large model errors in the off-equatorial sea level and wind anomalies that play a key role in the coupled behavior. The use of data to estimate new model parameterizations allows for significantly improving both the initial conditions and the forecasts up to 6-month lead time. This success holds for all the various initialization procedures used in this study. Because of erroneous winds simulated by the atmospheric component in the eastern Pacific, errors grow fast though. Replacing the atmospheric model by a statistical one results in more reliable predictions over 1980?98. For lead times up to 1 yr, the model predicts well the observed anomalies between 1984 and 1993, including the sea level rises along the ITCZ after warm events and their subsequent equatorward migration. This success is attributed to the consistency between the observed anomalies over this period and the mechanisms involved in maintaining the oscillatory behavior of the model, including the off-equatorial meridional wind anomalies.