Influence of different data selection criteria on internal geomagnetic field modeling

Earth’s internal core and crustal magnetic fields, as measured by geomagnetic satellites like MSS-1 (Macau Science Satellite-1) and Swarm, are vital for understanding core dynamics and tectonic evolution. To model these internal magnetic fields accurately, data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere. However, the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood. This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models. First, we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling. Second, we briefly describe the method to co-estimate the core, crustal, and large-scale magnetospheric fields using satellite magnetic data. Finally, we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence. Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times, the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla (nT). Additionally, we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites. These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.