A leading-edge review maps path to better Asian monsoon predictions under global change

A comprehensive and innovative review, published in Advances in Atmospheric Sciences, offers an in-depth examination of the progress, challenges, and outlook for Asian monsoon climate prediction in the context of global climate change. Led by Professor Bin Wang from the University of Hawaii at Manoa, an international group of scientists synthesizes decades of research to chart a roadmap for more reliable and actionable monsoon seasonal forecasts.

The Asian monsoon is one of the world's most influential climate systems, directly impacting the weather, water resources, agriculture, and livelihoods of billions of people across Asia. Accurate seasonal prediction of the monsoon, especially rainfall, is crucial for disaster prevention, food security, and economic planning in the region. While significant progress has been reached over the past two decades, current climate models still struggle with systematic biases, and the reliability of traditional predictors is changing.

The review systematically summarizes the foundations of monsoon climate prediction, highlighting three key theoretical pillars: El Niño-Southern Oscillation (ENSO), atmospheric teleconnections, and monsoon-ocean interactions. ENSO, in particular, stands out as a major source of monsoon predictability, with different phases and types of ENSO events exerting distinct regional impacts on Asian rainfall patterns. However, the authors emphasize that ENSO is not the only factor at play. Other sources of predictability, such as the Indian Ocean Dipole, land-atmosphere interactions, and remote influences from the Atlantic, North Pacific, and polar regions, also significantly shape monsoon variability. “A comprehensive understanding of these diverse sources of predictability is essential for improving monsoon forecasts,” states Prof. Wang.

The team underscores that external forcings, including greenhouse gases and aerosols, are significantly altering the monsoon system. These factors not only alter shift rainfall patterns but also increase the frequency and intensity of extreme weather events, making the monsoon more variable and more complicated to predict.

In addition, the authors discuss recent advancements in forecasting models and methods, including dynamical models, empirical prediction models, and hybrid dynamic-empirical models. Despite these advancements, significant challenges remain. Current climate models still struggle to accurately simulate key monsoon processes, such as convection and land-sea-air interactions, resulting in systematic biases. Monsoon predictability itself is inherently unstable due to the complex interplay of internal climate variability, remote forcing, and evolving ENSO characteristics.

To overcome these challenges, the review outlines a path forward, recommending a multi-pronged approach. “The future of monsoon prediction lies in integrating cutting-edge technologies with fundamental climate science,” Prof. Wang explained. “This includes leveraging artificial intelligence to capture complex non-linear relationships, developing models that can better simulate key physical processes, and improving our sub-seasonal predictions to bridge the gap between weather and climate.” The review emphasizes that strengthening observational networks, enhancing model accuracy, integrating research and operational forecasting, and promoting international collaboration and data sharing are also critical steps forward.

“We hope that this review will inspire new research and innovation to advance monsoon prediction further, ultimately supporting better risk management and adaptation across Asia,” Prof. Wang concluded.

The review is included in a special issue "Global and regional monsoons: State of the art and perspectives" organized by World Climate Research Programme Monsoon Panel.

 

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