Climatological diagnostics and subseasonal‐to‐seasonal predictions of Madden–Julian Oscillation events

Abstract

The Madden–Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability, which serves as a primary source of subseasonal‐to‐seasonal (S2S) predictability. Noticeably, MJO is not always a regularly recurring cycle but is characterized by discrete episodes. In this study, considering the quasi‐consecutive actives and eastward propagating features, a standard metric is proposed to identify MJO events based on the real‐time multivariate MJO (RMM) index. The re‐identification of historical MJO events reveals that there were 5.4 MJO events each year since 1981, and the average duration of each event is about 31.5 days. More MJO events tend to occur in the boreal winter and spring, with stronger intensity, longer duration and faster propagating speed than those in the boreal summer. Furthermore, MJO events are more likely to initiate in Phases 2 and 5, with a longer lifetime than those initiating in other phases. The amplitude and propagation characteristics of MJO events are strongly modulated by the dominant modes of sea surface temperature interannual variability with a strong regional dependence. Based on hindcast datasets of six S2S models, the prediction skill for the MJO is evaluated in the perspective of individual events. The longest leading time of the skilful prediction for individual MJO events ranges from 11 to 17 days, far below the traditional recognition. This result could be attributed to the apparent prediction barrier of MJO initiation, that is, a rapid decrease in prediction skill when predictions are carried out before the initiation of MJO events. In addition, the prediction skills of MJO events depends on interannual variabilities, with relatively higher skills under the conditions of the El Niño and Indian Ocean basin warming. These findings may shed light on the complexity and challenges of profoundly understanding and skilfully predicting MJO events.

MJO Initiation Westward Shifted and Propagation Blocked under Indian Ocean Basin Warming during Boreal Summer

“…2). Thus, the IOBM signal has a significant regional effect on the formation of MJO convection, particularly on its initiation, as previously reported in literature (e.g., Wu et al, 2023). (f) is the same as (e), but for the RMM index.…”

Potential predictability of the Madden-Julian Oscillation in a superparameterizated model

“…The MJO in these models is more realistic and yields prediction skill of nearly 30 days with a single ensemble forecast (comparable to an 11-member ensemble ECMWF forecast). However, these models are extremely computationally expensive and can only feasibly simulate comparatively few MJO events (< 100 in the above studies), restricting their ability to assess the potentially significant differences in predictability for different MJO characteristics and background states (Wu et al, 2023). A more computationally practical alternative is to use a multiscale modeling framework that couples a coarse resolution global model to a fine resolution cloud resolving model (Randall et al, 2016;Hannah et al, 2015).…”

Potential Predictability of the Madden‐Julian Oscillation in a Superparameterized Model

“…The MJO in these models is more realistic and yields prediction skill of nearly 30 days with a single ensemble forecast (comparable to an 11‐member ensemble ECMWF forecast). However, these models are extremely computationally expensive and can only feasibly simulate comparatively few MJO events (<100 in the above studies), restricting their ability to assess the potentially significant differences in predictability for different MJO characteristics and background states (Wu et al., 2023). A more computationally practical alternative is to use a multiscale modeling framework that couples a coarse resolution global model to a fine resolution cloud resolving model (Hannah et al., 2015; Randall et al., 2016).…”