Revisiting the Role of Atmospheric Initial Signals in Predicting ENSO

Abstract El Niño–Southern Oscillation (ENSO) provides an important source of global seasonal–interannual predictability, while its prediction encounters bottlenecks. Besides the slow-varying air–sea feedbacks, high-frequency atmospheric signals (HFASs) act on ENSO evolution. This study revisits the role of atmospheric initial signals in ENSO prediction using an atmosphere–ocean coupled model. Two sets of sensitivity hindcasts are conducted. One utilizes a pure sea surface temperature (SST) nudging for initialization so that no observed atmospheric internal signal is assimilated. The other applies a combination of the SST nudging and spectral nudging of JRA-55 reanalysis, which not only assimilates the observed atmospheric states and hence realizes skillful predictions of HFAS at the initial stage but also improves the oceanic initial conditions (ICs), especially around the thermocline. Unexpectedly, the better atmosphere–ocean ICs neither improve ENSO prediction nor overcome the spring prediction barrier. Further analysis of Bjerknes stability index suggests that underestimated negative feedbacks and insufficient responses of ocean currents and thermocline slope to atmospheric internal winds may account for the failure. Nevertheless, assimilating the atmospheric information partly improves the prediction of El Niño onset, especially for two recent extreme cases (i.e., 1997/98 and 2015/16). This improvement is associated with better representations of initial westerly wind bursts (WWBs) that excite subsequent downwelling equatorial Kelvin waves. However, due to unpredictable WWBs and underestimated wind response to the SST warming owing to the cold tongue biases in boreal summer, the zonal advective feedbacks are underestimated and thus further development of El Niño cannot be well predicted. This study suggests the importance of initial atmospheric signals despite the limitation, prompting further efforts to improve model physics.