Artificial Intelligence Revolutionises Weather Forecast, Climate Monitoring and Decadal Prediction

Abstract

Artificial Intelligence (AI) is an explosively growing field of computer technology, which is expected to transform many aspects of our society in a profound way. AI techniques are used to analyse large amounts of unstructured and heterogeneous data and discover and exploit complex and intricate relations among these data, without recourse to an explicit analytical treatment of those relations. These AI techniques are unavoidable to make sense of the rapidly increasing data deluge and to respond to the challenging new demands in Weather Forecast (WF), Climate Monitoring (CM) and Decadal Prediction (DP). The use of AI techniques can lead simultaneously to: (1) a reduction of human development effort, (2) a more efficient use of computing resources and (3) an increased forecast quality. To realise this potential, a new generation of scientists combining atmospheric science domain knowledge and state-of-the-art AI skills needs to be trained. AI should become a cornerstone of future weather and climate observation and modelling systems.

Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectives

“…It is worth mentioning that, although all the methods referenced in this paper can be used with success in many applications, some of them, for example RF, require less knowledge in the field of machine learning and are more suitable for beginners, while DL or CNN needs more experience to be used properly. We agree with [111] that artificial intelligence will be a very important technique that will help in the monitoring and forecasting of weather conditions. Independent of operational use, those methods can be also highly valuable in climate change research at spatial-and temporal scales [112], although it will depend strongly on data availability, which over recent years has been constantly improving.…”

Special-Purpose English Teaching Reform and Model Design in the Era of Artificial Intelligence

“…e purpose of introducing the sinc function is to obtain a rectangular pulse with an amplitude of 1 after the Fourier transform of the sinc function. When extracting the original speech signal, it is often combined with time domain and frequency domain information for analysis [12]. For frequency domain signals, filtering methods are often used to obtain characteristic information contained in different frequency bands.…”

End-to-End Prediction of Lightning Events from Geostationary Satellite Images

“…Our study is designed in particular to address the question of what insight can be gained from satellite images alone for short-term Cb-forecasting, and which parts of the data are most important to this end. The use of machine learning methods, and specifically deep neural networks, has been studied previously in the literature [25][26][27][28][29]. Specifically, U-Nets have been used in related studies for precipitation forecasting [30,31].…”