Related papers: Machine learning prediction of the MJO extends bey…
The Madden-Julian oscillation (MJO) is a planetary-scale, intraseasonal tropical rainfall phenomenon crucial for global weather and climate; however, its dynamics and predictability remain poorly understood. Here, we leverage deep learning…
The Madden--Julian Oscillation (MJO) is an influential climate phenomenon that plays a vital role in modulating global weather patterns. In spite of the improvement in MJO predictions made by machine learning algorithms, such as neural…
The Madden-Julian Oscillation (MJO) is the dominant mode of tropical atmospheric variability on intraseasonal timescales, and reliable MJO predictions are essential for protecting lives and mitigating impacts on societal assets. However,…
Generative Deep Learning is a powerful tool for modeling of the Madden-Julian oscillation (MJO) in the tropics, yet its relationship to traditional theoretical frameworks remains poorly understood. Here we propose a video diffusion model,…
The Madden-Julian Oscillation (MJO) is an important driver of global weather and climate extremes, but its prediction in operational dynamical models remains challenging, with skillful forecasts typically limited to 3-4 weeks. Here, we…
The Madden-Julian oscillation (MJO), a gigantic tropical weather system, is marked by eastward travel of cumulus cloud clusters over the Indo-Pacific region and often causes severe weather and climate events worldwide. The physics and…
Accurately defining the life cycle of the Madden-Julian Oscillation (MJO), the dominant mode of intraseasonal climate variability, remains a foundational challenge due to its propagating nature. The established linear-projection method (RMM…
Humid heat stress and heatwaves pose significant risks for living organisms, from humans and wildlife to insects. These threats have wide-ranging health, ecological, and socio-economic impacts that are expected to worsen with climate…
The Madden-Julian oscillation (MJO) is a tropical weather system having important influence in the tropics and beyond; however, many of its characteristics are poorly understood, including their initiation and completion. Here we define…
The seamless forecast approach of subseasonal to seasonal scale variability has been succeeding in the forecast of multiple meteorological scales in a uniform framework. In this paradigm, it is hypothesized that reduction in initial error…
The MaddenJulian oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics. Despite its primary importance, a generally accepted theory that accounts for fundamental features of the MJO, including its propagation…
Recent observations have indicated significant modulation of the Madden Julian Oscillation (MJO) by the phase of the stratospheric Quasi-Biennial Oscillation (QBO) during boreal winter. Composites of the MJO show that upper tropospheric ice…
The Madden-Julian Oscillation (MJO) has been studied using its daily RMM1, RMM2 and VPM1, VPM2 principal components' indices. A spectral analysis of the raw indices indicates presence of a noise presumably contributed by the random…
We discuss a simple three layer model of the tropical atmosphere. The rainfall variance of the model is dominated by a rainfall mode moving parallel to the equator having the approximate size and propagation speed of the Madden-Julian…
The influence of the Madden Julian Oscillation (MJO) on the precipitation extremes in Indonesia during the rainy season (October to April) has been evaluated using the daily station rain gauge data and the gridded Asian Precipitation Highly…
Weather is a phenomenon that affects everything and everyone around us on a daily basis. Weather prediction has been an important point of study for decades as researchers have tried to predict the weather and climatic changes using…
We test the reliability of two neural network interpretation techniques, backward optimization and layerwise relevance propagation, within geoscientific applications by applying them to a commonly studied geophysical phenomenon, the…
This study examines the evolution of extreme Madden-Julian Oscillation (MJO) events and their impacts on South America during the austral summer. Furthermore, the study explores how the different ENSO phases modulate extreme MJO events, and…
This study examines the influence of Madden-Julian Oscillation (MJO) on Indonesian precipitation during the extended boreal summer (May to September). The MJO is one of the dominant intraseasonal variabilities that influence the extreme…
The midlatitude climate and weather are shaped by storms, yet the factors governing their predictability remain insufficiently understood. Here, we use a Convolutional Neural Network (CNN) to predict and quantify uncertainty in the…