Abstract
Geomagnetic storm-detection algorithms are important for space-weather-warning services to provide reliable warnings (e.g., ionospheric disturbances). For that reason, a new approach using an adaptive filter (least mean squares algorithm) for the detection of geomagnetic storms based on the volatility of the north–south interplanetary magnetic field Bz is presented. The adaptive filter is not dependent on solar wind plasma measurements, which are more frequently affected by data gaps than Bz, and is less dependent on the magnitude of Bz disturbances compared with other detection algorithms (e.g., static thresholds). The configuration of the filter is discussed in detail with three geomagnetic storm events, and required optimization as well as possible extensions are discussed. However, the proposed configuration performs satisfactorily without further improvements, and good correlations are observed with geomagnetic indices. Long-term changes are also reflected by the filter (solar cycles 23 and 24), and thus the performance is not affected by different solar wind conditions during the solar minimum and maximum. Conclusively, the proposed filter provides a good solution when more complex approaches (e.g., solar-wind–magnetosphere coupling functions) that rely on solar wind plasma measurements are not available.
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