A Statistical Study of Polar Cap Patch Occurrence and IMF Dependence Using GNSS TEC Maps

Abstract

In this paper, we present an automated algorithm for identifying the two‐dimensional distribution of polar cap patches from GNSS Total Electron Content (TEC) maps, combining dynamic thresholding with a set of physical constraints. The performance of the algorithm is validated using a well‐documented event, showing close agreement with manual identification in both timing and spatial morphology. Using GNSS TEC data from 2020 to 2024, we analyze the seasonal, universal time (UT), and Interplanetary Magnetic Field (IMF) dependencies of patch occurrence in the northern polar cap. The statistical analysis mainly focuses on solar‐maximum years, during which the algorithm performs more reliably because the higher background TEC facilitates the separation of classical polar cap patches from relatively weak precipitation‐related structures. The resulting occurrence patterns are generally consistent with previous studies. For the year 2023, we further examine the relationship between patch formation and the preceding IMF variations. The statistical analysis reveals that both rapid and large‐amplitude variations in the IMF By and Bz components are closely associated with patch formation. This suggests that IMF‐driven modulation of the convection pattern plays an important role in polar cap patch formation. These results provide new statistical evidence linking IMF variations to patch formation and demonstrate the capability of TEC‐based methods for statistical patch studies. However, the algorithm may underestimate patch occurrence near the dayside source region because newly formed patches may be excluded by the adopted identification criteria, although this does not affect the statistical conclusions of this study.