An ENSO prediction approach based on ocean conditions and ocean–atmosphere coupling
Dr. Yu‑heng Tseng
Department of Atmospheric Sciences, National Taiwan University
A simple statistical model for the El Niño–SouthernOscillation (ENSO) prediction is derived based on the evolution of the ocean heat condition and the oceanic Kelvinwave propagation associated with westerly wind events(WWEs) and easterly wind surges (EWSs) in the tropical Pacific. The multivariate linear regression model solely relies on the pentad thermocline depth anomaly evolution in 25 days along with the zonal surface wind modulation. It successfully hindcasts all ENSOs except for the 2000/01 La Niña, using the pentad (or monthly) mean tropical atmosphere ocean array data since 1994 with an averaged skill(measured by anomaly correlation) of 0.62 (or 0.67) with a6-month lead. The exception is mainly due to the long-lasting cold sea surface temperature anomalies in the subtropics resulting from the strong 1998/99 La Niña, even though the tropical warm water volume (WWV) had rebounded and turned phases after 2000. We also note that the hindcast skill is comparable using pentad or monthly mean NCEP global ocean data assimilation system data for the same time period. The hindcast skill of the proposed statistical model is better than that based on the WWV index in terms.