Advances in Earth Science ›› 2020, Vol. 35 ›› Issue (6): 551-560. doi: 10.11867/j.issn.1001-8166.2020.053

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Development of Artificial Intelligence Technology in Weather Forecast

Leiming Ma( )   

  1. Shanghai Central Meteorological Observatory, Shanghai 200030, China
  • Received:2020-04-12 Revised:2020-05-19 Online:2020-06-10 Published:2020-07-06
  • About author:Ma Leiming (1975-), male, Shihezi City, Xinjiang Uygur Autonomous Region, Professor. Research areas include typhoon, numerical prediction, artificial intelligence technology. E-mail:
  • Supported by:
    the National Natural Science Foundation of China "The mechanism influencing deep convection intensity variation associated with PBL top and closure scheme for convective parameterization"(41975069);The Key Project of Shanghai Science and Technology Commission "Disaster weather (strong convection) digital simulator key technology research and application"(18DZ1200400)

Leiming Ma. Development of Artificial Intelligence Technology in Weather Forecast[J]. Advances in Earth Science, 2020, 35(6): 551-560.

Numerical weather prediction, which is the major basis of current weather forecast, has some shortcomings, such as the understanding of the law of atmospheric motion, the assimilation and application of observation data, the expression of model physics, etc., leading to the forecast error of weather. The rapid development of artificial intelligence technology in recent years provides a new possibility for the advancement and innovation of weather forecast. In this paper, the background of the development of artificial intelligence, the current situation of the application of artificial intelligence technology to weather forecast and the future development trend are mainly described to account for this possibility. After that, the idea for development of weather forecast technology based on the integration of artificial intelligence and numerical forecast is put forward. Particularly, this study stresses that, in order to advance the AI algorithm of weather forecast in the future, it is requested to focus on the nonlinear and chaotic characteristics of atmospheric motion leading to the uncertainty of forecast. Starting from the essence of mathematics and physics, we need to realize the hybrid modeling of mathematics and physics, not only to establish the framework of input-output mapping, but also to provide solutions to the bottleneck problems of weather forecast.

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