Barrier Effect of the Indo-Pacific Maritime Continent on MJO Propagation in Observations and CMIP5 Models

Abstract

This study explores possible mechanisms for the barrier effect of the Indo-Pacific Maritime Continent (MC) on MJO propagation. In particular, this study examines whether similar mechanisms can be found in both observations and CMIP5 simulations. All models simulate individual MJO events but underestimate the percentage of MJO events propagating into the MC. The simulations are grouped into the top and bottom 50% based on their capability of reproducing the MJO spectral signal. When compared with the observations, the bottom 50% of the simulations significantly underestimate the MJO strength and exaggerate the barrier effect intensity, whereas these discrepancies are not significant in the top 50% of the simulations. From the top 50% of the simulations, the MJO strength, moisture processes, and surface evaporation in the MC all play important roles in constituting the barrier effect. No such evidence is found in observations. The discrepancies may come from small observed sample size and/or misrepresentations of key physical processes in the models. A consistent result is found in the observations and simulations: Whether MJO events can cross the MC depends on the degree to which dominant precipitation over land shifts to over water in the MC as MJO convection centers approach the MC and cross it. This result emphasizes the critical role of precipitation over water in carrying convective signals of the MJO through the MC. The results suggest that diagnosing the model alone on mechanisms for the barrier effect could be misleading; further investigations using a combination of observations, global gridded data, and high-resolution models are needed.

The MJO From CMIP5 to CMIP6: Perspectives From Tracking MJO Precipitation

“…The barrier effect of the MC on MJO propagation is usually exaggerated in the models (Chen et al., 2020; Inness et al., 2003; Kim et al., 2009; Seo et al., 2009). To quantify whether the exaggerated barrier effect is reduced in CMIP6, we use the “MJO‐C ratio” metric to quantify the barrier effect.…”

“…When the MJO propagates over the Maritime Continent (MC), it usually gets weak and fails to propagate into the western Pacific, known as the barrier effect of the MC on the MJO propagation (Hsu & Lee, 2005; Rui & Wang, 1990; Zhang & Ling, 2017). Through identifying individual MJO events, it has been suggested that the lack of statistical signals of the MJO propagation in the models is reflected by the underestimated MJO occurrence frequency and exaggerated barrier effect of the MC on MJO propagation (Chen et al., 2020; Ling et al., 2017; Ling, Zhao, & Chen, 2019). The systematic errors of the models in the mean states (Gonzalez & Jiang, 2017; Inness et al., 2003; Kang et al., 2020; Ling et al., 2017), precipitation and its dependence on moisture (Kim et al., 2009) are considered to limit the MJO simulation skills.…”

Influence of the North Pacific Victoria Mode on the Madden–Julian Oscillation

“…To further confirm that there is a fundamental connection between the FMA VM over the extratropical region and following MJO activity in the tropics over the ECWP, we analyzed individual models from CMIP5. It should be noted that the simulation results of VM and MJO in the CMIP5 (Chen et al, 2020) are not perfectly in the same mode. Therefore, the following two modes, which can certainly simulate MJO and VM, are selected in this study (Table 1).…”

Comparison of forecasting accuracy for Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) using Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim precipitation forecast data for Indonesia

“…On the other hand, Liu et al (2017) suggested that the Indian Ocean Dipole (IOD) is strongly correlated rather than ENSO against the MJO forecast skill. Nevertheless, due to the barrier effect constraint of the MJO during passing the Indo-Pacific Maritime Continent (Zhang and Ling, 2017;Chen et al, 2020) that has a significant connection with IOD (Liu et al,2017), thus, the calculation in this paper accounts solely for the ENSO influence. A 13-year weekly Nino3.4 index from the National Oceanic and Atmospheric Administration was used to apply daily regression against daily precipitation of 3B42 and ERA-Interim reanalysis and forecast models.…”