Forecasting of Global Ionosphere Maps With Multi‐Day Lead Time Using Transformer‐Based Neural Networks

Forecasting of Global Ionosphere Maps With Multi‐Day Lead Time Using Transformer‐Based Neural Networks

Abstract Ionospheric total electron content (TEC) is a key indicator of the space environment. Geophysical forcing from above and below drives its spatial and temporal variations. A full understanding of physical and chemical principles, available and well‐representable driving inputs, and capable c...

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Bibliographic Details
Main Authors: Chung‐Yu Shih, Cissi Ying‐tsen Lin, Shu‐Yu Lin, Cheng‐Hung Yeh, Yu‐Ming Huang, Feng‐Nan Hwang, Chia‐Hui Chang
Format: Article
Language:English
Published: Wiley 2024-02-01
Series:Space Weather
Subjects:
TEC prediction
neural network
Transformer
Online Access:https://doi.org/10.1029/2023SW003579
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https://doi.org/10.1029/2023SW003579

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