Weijia Zhan

University of Colorado Boulder
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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

-

UNITED STATES
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Xing Meng

California Institute of Technology

UNITED STATES
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Alex Chartier

Senior Professional Staff II

Johns Hopkins University Applied Physics Laboratory

UNITED STATES
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Robert A. Marshall

-

UNITED STATES
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Roger Varney

Assistant Professor

University of California, Los Angeles

UNITED STATES
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Stephen Kaeppler

Assistant Professor

Clemson University

UNITED STATES
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Gareth Perry

Assistant Professor

New Jersey Institute of Technology

UNITED STATES
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