Geomagnetic Secular Variation Forecast with Ensemble Kalman-filter Data Assimilation System
Nikolaos Pavlis, National Geospatial-Intelligence Agency
Usage Details
Nikolaos Pavlis, Weijia Kuang, Andrew TangbornThe Earth’s time-varying geomagnetic field, fundamental to studying the interior structure and evolution of the Earth, and vital for navigation and protection from solar particle radiation, is challenging to simulate. Models must account for time scales ranging from less than a year to billions of years and spatial scales ranging from centimeters to thousands of kilometers, requiring extremely high temporal and spatial resolution. Accurate prediction of secular variation (SV), or changes in time, can be achieved via large-ensemble assimilation of geomagnetic observations and theoretical geodynamo models, but requires petascale computational resources to reduce research time to weeks instead of years.
The main objective of this project is to investigate the convergence of assimilation with different ensemble sizes and simulation resolutions for given physical parameters. In two months of work, the research team found that the ensemble size of approximately 256 is optimal for assimilation, based on the computational needs and the forecast accuracies. This result is very important as it establishes a quantitative correlation among the forecast accuracy requirements, computational resource needs, and time periods for progress. Optimal ensemble sizes can greatly reduce the computational expense and research time without compromising research objectives.