Weijia Zhan
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Articles (6)
Year:
2023
Precise prediction of the global spatial–temporal distribution of total electron content (TEC) is a challenge in space weather. Existing models are generally able to provide rather good prediction results at the cost of a large amount of computing resources. This limits the application of the method. A lightweight and highly accurate global TEC prediction model was developed in this study. Our model is capable of forecasting the global TEC map up to 12 h in advance with a step of one hour. The predicted results during geomagnetic quiet periods were consistent with measurements, with a maximum and average mean error (ME) of 1.5 TECU and −0.04 TECU under conditions of high solar activity, respectively. Our model also performed well during geomagnetic disturbed periods, with a maximum ME of 4.5 TECU and 2.5 TECU under conditions of high and low solar activities, respectively. Our model significantly reduces the training time (47%) and basic requirement of memory (60%) relative to the model of Liu et al. (2022) with no remarkable loss of model accuracy.
Year:
2023
Year:
2022
Year:
2022
Year:
2021
Year:
2021
Collaborators (7)
Miguel F. Larsen
-
Xing Meng
California Institute of Technology
Alex Chartier
Senior Professional Staff II
Johns Hopkins University Applied Physics Laboratory
Robert A. Marshall
-
Roger Varney
Assistant Professor
University of California, Los Angeles
Stephen Kaeppler
Assistant Professor
Clemson University
Gareth Perry
Assistant Professor
New Jersey Institute of Technology
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