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Geomagnetic secular variation forecast using the NASA GEMS ensemble Kalman filter: A candidate SV model for IGRF-13
Andrew Tangborn1, Weijia Kuang2, Terence J Sabaka2
1Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD USA.
Earth, Planets, and Space : EPS
|February 25, 2021
Summary
Scientists forecast geomagnetic field secular variation (SV) for 2020-2025 using NASA
Area of Science:
- Geophysics
- Earth Sciences
- Geomagnetism
Background:
- The geomagnetic field exhibits secular variation (SV), a key indicator of Earth's core dynamics.
- Accurate SV prediction is crucial for navigation, satellite operations, and understanding geodynamo processes.
Purpose of the Study:
- To generate a 5-year mean secular variation (SV) forecast of the geomagnetic field for 2020-2025.
- To provide a candidate predictive model for the International Geomagnetic Reference Field (IGRF-13).
Main Methods:
- Utilized the NASA Geomagnetic Ensemble Modeling System (GEMS), integrating a geodynamo model with an ensemble Kalman filter (EnKF).
- Employed historical geomagnetic field models (gufm1, CM4, CM6) for data assimilation.
- Implemented a bias correction scheme assuming long-timescale model bias changes.
Main Results:
- Produced a 5-year mean secular variation (SV) forecast for the geomagnetic field (2020-2025).
- Validated the forecasting algorithm on the 2010-2015 period against the CM6 model.
- Submitted the forecast as a candidate for IGRF-13.
Conclusions:
- The GEMS model provides a robust method for geomagnetic field forecasting.
- The forecast contributes to the ongoing effort to model and predict Earth's magnetic field behavior.
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