Abstract:

The El Niño-Southern Oscillation (ENSO) phenomenon greatly modulates the global weather and climate conditions with great socio-economic implications.  At the meantime, ENSO provides most of the global seasonal to interannual climate forecast skill.  However, quantifying and understanding the sources of the skillful predictions and improving ENSO forecast skill at long-time leads are long-standing challenges.  We thus will briefly review the fundamental dynamics of ENSO and its multiscale-Interactions through conceptual and theoretical perspectives.  We then present a newly developed eXtended low-order nonlinear Recharge Oscillator (XRO) model which parsimoniously incorporates the core ENSO dynamics and ENSO’s seasonally modulated interactions with other climatic modes of variability in the global oceans with only about 10 prognostic key indices.  We show that XRO exhibits skillful ENSO forecasts at lead-times up to 16-18 months, better than that of the state of art comprehensive global climate models and comparable to the most skillful AI forecasts.  The XRO’s holistic treatment of ENSO’s multi-timescale interactions with other climate modes allows us to quantitatively attribute intrinsic enhancement of ENSO’s long-range forecast skill to the initial conditions of other climate modes via their memory and interactions with ENSO and to count for these modes’ contributions to forecast ENSO amplitudes.  Examples are given to demonstrate that there are some remarkable global to locality pathways which are season- and locality-dependent connections of coastal hazards to ENSO, yielding cases of potentially high predictive skills for the hazards even at final scales.  Implications of ENSO and climate predictability and its implications/utilities for impact/risk forecasts from global to coastal/island scales will be briefly discussed as well.