The 81^st edition of CLIVAR Exchanges, themed “Advances in Climate Prediction Using Artificial Intelligence”, has been released. The two guest editors of this special issue are Dr Jing-Jia Luo, Director of the Institute for Climate and Application Research (ICAR) at Nanjing University of Information (NUIST) and member of the CLIVAR Pacific Region Panel, and Dr Swadhin Behera, Director of the Application Laboratory at Japanese Agency for Marine-Earth Science and Technology (JAMSTEC).

Accurate climate forecasts are essential for disaster preparedness, socio-economic development, and ecosystem management. Meanwhile, with the rapid increase of model-simulated data as well as observational data collected from various in situ and remote techniques, we are heading towards a new era in the use of big data in climate science, which calls for an innovative way to effectively deal with these big data and correctly dig out the complex relations/physics hidden in them. As Artificial Intelligence (AI) attracting more and more attention to improving weather and climate forecasts in recent years, however, compared to weather forecasts, building AI models for climate forecasts has been very challenging, as rather limited records of climate observations available for training the AI models.

The first world competition on “2021 AI Earth” prize competition: “Artificial Intelligence Innovation Challenge--AI Helps Accurate Weather and Ocean Forecast” was successfully organized in China, with joint support from research institutes, universities, government agencies and private sector, and with data supported by ICAR. It attracted 2849 teams from 19 countries and encouraged the endeavors in improving AI-based prediction of climate phenomena like ENSO.

This special issue overviews studies from the top teams of this competition, as well as the practical use on AI in operational ocean and climate forecasts and existing studies and new results on the application of AI to Earth Science from invited international scientists. The recent advances in the application of AI to ENSO forecast, numerical weather forecast correction and downscaling, heavy precipitation forecast, ocean wave height forecast, and ocean modeling are reported in this issue.

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