Vertical structure and physical processes of the Madden‐Julian oscillation: Exploring key model physics in climate simulations

Abstract

Aimed at reducing deficiencies in representing the Madden-Julian oscillation (MJO) in general circulation models (GCMs), a global model evaluation project on vertical structure and physical processes of the MJO was coordinated. In this paper, results from the climate simulation component of this project are reported. It is shown that the MJO remains a great challenge in these latest generation GCMs. The systematic eastward propagation of the MJO is only well simulated in about one fourth of the total participating models. The observed vertical westward tilt with altitude of the MJO is well simulated in good MJO models but not in the poor ones. Damped Kelvin wave responses to the east of convection in the lower troposphere could be responsible for the missing MJO preconditioning process in these poor MJO models. Several process-oriented diagnostics were conducted to discriminate key processes for realistic MJO simulations. While large-scale rainfall partition and low-level mean zonal winds over the Indo-Pacific in a model are not found to be closely associated with its MJO skill, two metrics, including the low-level relative humidity difference between high-and low-rain events and seasonal mean gross moist stability, exhibit statistically significant correlations with the MJO performance. It is further indicated that increased cloud-radiative feedback tends to be associated with reduced amplitude of intraseasonal variability, which is incompatible with the radiative instability theory previously proposed for the MJO. Results in this study confirm that inclusion of air-sea interaction can lead to significant improvement in simulating the MJO.

A general theoretical framework for understanding essential dynamics of Madden–Julian oscillation

“…1c), so that both lead the major precipitation (and the mid-level maximum upward motion). This vertical backward structure is consistent with many previous observational studies (e.g., Sperber 2003;Tian et al 2006;Jiang et al 2015).…”

“…1). We examined 24 GCMs participated in MJOTF/GASS Global Model Evaluation Project (Jiang et al 2015). Figure 1 (upper panels) shows propagation and structure of the observed MJO.…”

“…The models-simulated MJOs were categorized into two groups: good (middle panels) and poor (lower panels). These two groups of composite maps were made by 7 best propagating models and 7 worst propagating models selected from the 24 GCMs that participate in the MJOTS/GASS global model assessment project (Jiang et al 2015) (Nakazawa 1988), remarkable seasonal variations (Wang and Rui 1990b), coupling with ocean mixed layer (Krishnamurti et al 1988), and irregularities (Zhang 2005) should also be explained as higher-level theoretical targets, which require models with higher-level complexity.…”

Validity of parameter optimization in improving MJO simulation and prediction using the sub-seasonal to seasonal forecast model of Beijing Climate Center

“…Sperber et al (2005) indicated that realistic description of mean state is important for better simulation of MJO, while Kim et al (2011), Benedict et al (2013) and Boyle et al (2015) found that improved representation of MJO may corresponds to degraded mean state in one or more aspects in models. By comparing several models, Jiang et al (2015) showed an insignificant link between model MJO fidelity and mean state, which suggests that some factors other than the mean state are critical for realistic simulation of MJO. Klingaman et al (2015a, b) further showed that there is little correspondence between the MJO fidelity in model simulation and the MJO skill in initialized forecasts.…”

“…(2) To what extent can the MJO prediction skill be enhanced by reducing the error in MJO simulation? Studies by Jiang et al (2015), Klingaman et al (2015a, b), and Xavier et al (2015) characterized the key features in MJO physics and further examined how these features were related to models' MJO simulation and forecast skills. They showed weak and statistically insignificant relationships between MJO fidelity in the free-run simulations and initialized hindcasts.…”