The El Niño–Southern Oscillation (ENSO) is inherently asymmetric, a primary characteristic where its warm phase (El Niño) and cold phase (La Niña) differ in amplitude, spatial pattern, and temporal evolution. This review synthesizes over two decades of research to provide a comprehensive overview of ENSO asymmetry. It systematically examines the observed manifestations, evaluates the competing physical mechanisms, and analyzes the ongoing challenges in climate modeling. The key findings in the literature indicate that this asymmetry is driven by complex interactions of nonlinear processes, where atmospheric mechanisms such as state-dependent westerly wind bursts and threshold responses of deep convection are now considered dominant driving factors, which are subsequently amplified and modulated by oceanic feedback. The main challenge in this field is that most of the current state-of-the-art climate models underestimate ENSO asymmetry, which is related to mean-state bias and brings uncertainty to future predictions. Furthermore, a key finding from recent projection studies is that while the asymmetry in ENSO’s sea surface temperature is expected to weaken in a warmer climate, the asymmetry of its global rainfall impacts may paradoxically be amplified. Future research should focus on balanced improvements in ocean and atmospheric model components, development of new diagnostic tools to clarify the roles of different feedbacks, or establishment of a framework that clearly links asymmetry to the full spectrum of ENSO diversity. By consolidating the current state of knowledge and highlighting key unresolved questions, this work provides an essential roadmap to improve the prediction and projection of Earth’s most far-reaching mode of climate variability.

In contrast to the historical forecast test which is temporally successive with a near-steady forecast skill, the real-time forecast made at any one moment produces a forecast time-series whose skill rapidly decreases as the forecast lead time increases; thus, only the leading section of the latter is adopted in practical applications. As compared with the intraseasonal filtered historical forecast, the real-time extended-range forecast has a lower skill in the absence of filtering. In addition, it is difficult to estimate the intraseasonal phases near the end of the real-time forecast time-series due to missed information afterward. The current work developed a simple but useful method to improve the real-time forecast skill from the above two aspects for an empirical extended-range forecast scheme. The scheme is devoted to predict the intraseasonal variabilities of Indian summer monsoon precipitation, in which the boreal summer intraseasonal oscillation acts as the precursor. The intraseasonal signals in the previous observations, the better forecast skills of shorter lead times, the implicit information regarding the intraseasonal phases in the forecast of longer lead times, and the data-adaptive intraseasonal filter are adopted in the improving method, so as to extract intraseasonal signals as much as possible from the currently available information at each forecast moment. A practical comparison shows that the forecast skills of the real-time forecast improved by this method are close to or even better than the intraseasonal filtered historical forecast. Even at the longest acceptable forecast lead time that the forecast after which is considered to be worthless, it helps extract useful information regarding the intraseasonal phases.

Northern Hemisphere storm track activities (NHSTs) not only influence the weather and climate along their paths, but they also play a crucial role in climate systems by systematically transporting heat, momentum, and moisture. Distinguish from previous studies focusing on atmospheric circulation anomalies, this study provides further evidence of wintertime NHSTs variation under the influence of strong El Niño–Southern Oscillation (ENSO) events and Pacific Decadal Oscillation (PDO) variation with ERA-20C reanalysis data, from two mathematical aspects of linear superposition and nonlinear modulation. While ENSO warm/cold events lead the entire NHSTs to a general south/north shift, the ENSO impact in two PDO phases exhibits a remarkable difference with the PDO phase. The Pacific storm track (PST) anomalies largely strengthen equatorward and downstream when both ENSO and PDO are in phase, but its anomalies tend to be weakened when ENSO and PDO are out of phase. Generally, the opposite situation occurs with Atlantic storm track (AST) anomalies, which display a strengthening dipole pattern when ENSO and PDO are out of phase. Apparently, the result is roughly a linear superposition of ENSO and PDO-only impacts. Nevertheless, further analyses indicate that the nonlinear modulation of PDO on the ENSO impact on NHSTs exists. With respect to the PST, it exhibits approximately parallel bands of south-north dipole anomalies when ENSO is in the PDO positive phase, but only the south branch remains when ENSO is in the PDO negative phase. Generally, a similar situation occurs to AST anomalies over the Atlantic Ocean. The modulation may be mainly associated with the atmospheric mean flow anomalies and the midlatitude sea surface temperature anomalies to ENSO in different PDO phases. To some extent, the results may be beneficial for understanding the variation of extreme weather events brought by NHSTs.