MJO prediction: Current status and future challenges

There has been a growing interest in forecasting the weather and climate within the sub-seasonal time range. The Madden-Julian oscillation (MJO), an organized envelope of tropical convection, is recognized as a primary source of sub-seasonal predictability. The MJO prediction skill in the dynamical forecast system has only recently exceeded the skill of empirical predictions. The improvement of MJO prediction in dynamical forecasting systems has been mainly due to more observations and computer resources, better data assimilation techniques, advances in theoretical understanding, and improved numerical models aided in part by multinational efforts through field campaigns and numerical model experiments. Nevertheless, estimates of the MJO predictability suggest that there is still considerable room for improvement. This paper synthesizes the progress that has been made in the past decade regarding our MJO prediction capabilities with dynamical prediction systems and our scientific understanding of its predictability, discusses the remaining challenges, and recommends new research avenues to improve the MJO prediction. This paper is a concise version of an extensive review on MJO prediction in Kim et al. (2018).