On the dependence of ENSO simulation on the coupled model mean state

On the dependence of ENSO simulation on the coupled model mean state
Technical memorandum
Date Published
Secondary Title
ECMWF Technical Memoranda
Abstract Systematic model error has been and remains a difficult problem for seasonal forecasting and climate predictions. An error in the mean state could affect the variability of the system. In this report, we investigate the impact of the mean state on the properties of ENSO. A set of long coupled integrations have been conducted, where the mean state has been modified by applying different flux correction schemes. It is shown that correcting the mean state improves the amplitude of SST inter-annual variability, the penetration of the ENSO signal into the troposphere and the spatial distribution of the ENSO teleconnections. An analysis of a multivariate PDF of ENSO shows clearly that the flux correction affects the mean, variance, skewness and tails of the distribution. The changes in the tails of the distribution are particularly noticeable in the case of precipitation, showing that without the flux correction the model is unable to reproduce the frequency of large events. These results suggest that the current practice of removing the forecast bias a-posteriori is by no means optimal, since it cannot deal with the strong nonlinear interactions. A consequence of this results is that the predictability on annual time-ranges could be higher than currently achieved. Whether or not the correction of the model mean state by some sort of flux-correction leads to better forecasts needs to be addressed. In any case, flux correction may be a powerful tool for diagnosing coupled model errors and predictability studies.
URL https://www.ecmwf.int/en/elibrary/75519-dependence-enso-simulation-coupled-model-mean-state
DOI 10.21957/hqo2435ou