Articles | Volume 42, issue 1
https://doi.org/10.5194/angeo-42-91-2024
https://doi.org/10.5194/angeo-42-91-2024
Regular paper
 | 
12 Apr 2024
Regular paper |  | 12 Apr 2024

Deep temporal convolutional networks for F10.7 radiation flux short-term forecasting

Luyao Wang, Hua Zhang, Xiaoxin Zhang, Guangshuai Peng, Zheng Li, and Xiaojun Xu

Related authors

A Time-Dependent Three-Dimensional Magnetopause Model Based on Quasi-elastodynamic Theory
Yaxin Gu, Yi Wang, Fengsi Wei, Xueshang Feng, Andrey Samsonov, Xiaojian Song, Boyi Wang, Pingbing Zuo, Chaowei Jiang, Yalan Chen, Xiaojun Xu, and Zhilu Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2024-3012,https://doi.org/10.5194/egusphere-2024-3012, 2024
Short summary
Far-ultraviolet airglow remote sensing measurements on Feng Yun 3-D meteorological satellite
Yungang Wang, Liping Fu, Fang Jiang, Xiuqing Hu, Chengbao Liu, Xiaoxin Zhang, Jiawei Li, Zhipeng Ren, Fei He, Lingfeng Sun, Ling Sun, Zhongdong Yang, Peng Zhang, Jingsong Wang, and Tian Mao
Atmos. Meas. Tech., 15, 1577–1586, https://doi.org/10.5194/amt-15-1577-2022,https://doi.org/10.5194/amt-15-1577-2022, 2022
Short summary
A new perspective and explanation for the formation of plasmaspheric shoulder structures
Hua Zhang, Guangshuai Peng, Chao Shen, and Yewen Wu
Ann. Geophys., 39, 701–707, https://doi.org/10.5194/angeo-39-701-2021,https://doi.org/10.5194/angeo-39-701-2021, 2021
Short summary
Multi-satellite simultaneous observations of magnetopause and atmospheric losses of radiation belt electrons during an intense solar wind dynamic pressure pulse
Zheng Xiang, Binbin Ni, Chen Zhou, Zhengyang Zou, Xudong Gu, Zhengyu Zhao, Xianguo Zhang, Xiaoxin Zhang, Shenyi Zhang, Xinlin Li, Pingbing Zuo, Harlan Spence, and Geoffrey Reeves
Ann. Geophys., 34, 493–509, https://doi.org/10.5194/angeo-34-493-2016,https://doi.org/10.5194/angeo-34-493-2016, 2016
Short summary

Related subject area

Subject: Space weather, climate, habitability, and life in (exo-)planetary context | Keywords: Modelling
The Lehtinen–Pirjola method modified for efficient modelling of geomagnetically induced currents in multiple voltage levels of a power network
Risto J. Pirjola, David H. Boteler, Loughlin Tuck, and Santiago Marsal
Ann. Geophys., 40, 205–215, https://doi.org/10.5194/angeo-40-205-2022,https://doi.org/10.5194/angeo-40-205-2022, 2022
Short summary
Estimation of the westward auroral electrojet current using sparse magnetometer chain data
Marina A. Evdokimova and Anatoli A. Petrukovich
Ann. Geophys., 38, 109–121, https://doi.org/10.5194/angeo-38-109-2020,https://doi.org/10.5194/angeo-38-109-2020, 2020

Cited articles

Aminalragia-Giamini, S., Jiggens, P., Anastasiadis, A., Sandberg, I., Aran, A., Vainio, R., Papadimitriou, C., Papaioannou, A., Tsigkanos, A., Paouris, E., Vasalos, G., Paassilta, M., and Dierckxsens, M.: : Prediction of Solar Proton Event Fluence spectra from their Peak flux spectra, J. Space Weather Spac., 10, 1, https://doi.org/10.1051/swsc/2019043, 2020. 
Bai, S. J., Kolter, J. Z., and Koltun, V.: An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling, ArXiv [preprint], https://doi.org/10.48550/arXiv.1803.01271, 19 April 2018. 
Dieleman, S., van den Oord, A., and Simonyan, K.: The challenge ofrealistic music generation: Modelling raw audio at scale, ArXiv [preprint], https://doi.org/10.48550/arXiv.1806.10474, 26 June 2018. 
Du, Z.: Forecasting the Daily 10.7 cm Solar Radio Flux Using an Autoregressive Model, Sol. Phys., 295, 125, https://doi.org/10.1007/s11207-020-01689-x, 2020. 
Government of Canada: Solar radio flux – archive of measurements, Government of Canada [data set], https://spaceweather.gc.ca/forecast-prevision/solar-solaire/solarflux/sx-5-en.php, last access: 9 April 2024. 
Download
Short summary
The temporal convolutional network (TCN) approach in deep learning is used to predict the daily value of F10.7. The prediction results for 1–3 d ahead during solar cycle 24 have a high correlation coefficient (R) of 0.98 and a root mean square error (RMSE) of only 5.04–5.18 sfu.