Artificial Intelligence in Space Weather Forecast

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The Science Partner Journal Space: Science & Technology presents the special issue Artificial Intelligence in Space Weather Forecast.


Hazardous space weather casts a shadow on space and ground-based activities and may put at risk our entire technosphere. Crucial facilities and services, such as satellite infrastructures, global navigation systems, communication, aviation, finance sector, power grids, and pipelines may all be vulnerable to space storms. Hence, this threat spawns an imperative demand of space weather forecast. Recently, artificial intelligence (AI) was introduced in many fields and has great potential for information integration, data mining, and decision making. Over the past few decades, the space science community has accumulated huge amounts of data ever since the launch of the first satellite Sputnik 1. Hence, the pre-requisite of utilizing AI technology is complied. Applications of AI technologies like machine learning and neural networks are expected to strengthen the space weather forecast capacities and capabilities, and further make ever more precise predictions. The major objective of the special issue is to demonstrate outstanding advances in the field of space weather forecasting that are related to the wide range of AI approaches.

    Guest Editors

    Prof. Dr. Bingxian Luo, National Space Science Center, Chinese Academy of Sciences

    Portrait of Dr. Bingxian LuoDr. Bingxian Luo graduated from the University of Science and Technology of China in 2003, and received the Ph.D. degree from the University of Chinese Academy of Sciences in 2012. He is currently a full professor with the National Space Science Center, Chinese Academy of Sciences, Beijing, China. He has long been engaged in the development of space weather forecasting models such as solar eruptions, CME interplanetary propagations, geomagnetic disturbances as well as their application in space mission services.

    Prof. Robertus Erdélyi, Solar Physics and Space Plasma Research Centre (SP2RC), School of Mathematics and Statistics, University of Sheffield

    Portrait of Prof. Robertus ErdélyiProf Erdélyi (1997: CSc, Hungarian Academy of Sciences; 1996: PhD, K.U.L, Belgium), is currently Head of SP2RC, a full professor at School of Mathematics and Statistics, University of Sheffield (UK) and President-Curator of the Hungarian Solar Physics Foundation. His main research interests are i) in solar physics: MHD waves, oscillations and instabilities; ii) in Space Weather: developing semi-empirical flare/CME prediction methods and instrumentation for flare/CME forecasting (see, e.g. SAMNet - Solar Activity Magnetic Monitor Network); iii) in Applied Mathematics: machine learning and the theory of non-linear waves. Over 250 papers published with over 8k citations, h-factor 46 (39 w/o self-citation), RG Score 46.73 (data from ResearchGate). OrcID: 0000-0003-3439-4127.

    Dr. Jiajia Liu, Astrophysics Research Centre (ARC), School of Mathematics and Physics, Queen’s University Belfast

    Dr. Jiajia LiuDr. Jiajia Liu obtained his PhD degree from University of Science and Technology of China in 2015 and is currently a Research Fellow at Queen’s University Belfast. His main research interest lies in the field of Solar Physics and Space Weather with more than 40 publications. Dr. Liu was invited to the STEM for Britain event by the UK House of Commons in 2018 and became the first Chinese recipient of the International Alexander Chizhevsky medal in 2019. He now serves as a member of the UK Solar Physics Council of the Royal Astronomical Society, a panel member of the European Space Week medal committee, and a reviewer of the IAU Office of Astronomy for Development.

    Dr. Marianna B. Korsós, Aberystwyth University, UK

    Portrait of Dr. Marianna B. KorsósDr. Marianna B. Korsós works at Aberystwyth University, in UK. Her main research interest is to develop solar flare prediction methods based on data analysis and applying Machine Learning to Space Weather forecasting. Furthermore, her research interest is also focusing on the solar cycle variation. She is a member and national representative in the Working Group for Diversity and Inclusion of EAS (European Astronomical Society) and is an elected member of the UK Solar Physics Council (affiliated to the Royal Astronomical Society). She is also a member of the Advisory Board of the Hungarian Solar Physics Foundation (HSPF) and representative on the Supervisory Board of the Space Weather Awareness Training Network (SWATNet).

      Table of Contents

      Accurate Solar Wind Speed Prediction with Multimodality Information

      Yanru Sun, Zongxia Xie, Yanhong Chen, Qinghua Hu

      Space: Science & Technology, vol. 2022, Article ID 9805707, 13 pages, 2022

      Impacts of CMEs on Earth Based on Logistic Regression and Recommendation Algorithm

      Yurong Shi, Jingjing Wang, Yanhong Chen, Siqing Liu, Yanmei Cui, Xianzhi Ao

      Space: Science & Technology, vol. 2022, Article ID 9852185, 12 pages, 2022

      Two-Stage Solar Flare Forecasting Based on Convolutional Neural Networks

      Jun Chen, Weifu Li, Shuxin Li, Hong Chen, Xuebin Zhao, Jiangtao Peng, Yanhong Chen, Hao Deng

      Space: Science & Technology, vol. 2022, Article ID 9761567, 10 pages, 2022