The geomagnetic semiannual anomaly on the four Dst‐fundamental observatories: Dependences with Sun‐Earth physical parameters

Abstract

[1] The semiannual anomaly (also known as semiannual variation) on the magnetic activity is a phenomenon that produces clear minima during March and September and maxima in June and December on the horizontal components of the geomagnetic field. This phenomenon has been known since the middle of the nineteenth century, but in spite of the accumulation of measurements and the development of three theoretical models, a conclusive physical explanation for it has not been developed. The usual approach to study the semiannual anomaly is by means of geomagnetic indices like the disturbance storm time, Dst, which is based on combining measurements registered on four magnetic observatories. This work follows a different approach based on the raw horizontal components registered at the four observatories. The analyses performed aimed to study and assess the impact of several external parameters, characteristics of the Sun-Earth environment, on the semiannual anomaly. The influence of the global geomagnetic activity level, the solar activity level, the solar magnetic polarity, and the rising/declining phase of the solar radiation cycle is analyzed in detail. The most important finding is that the semiannual anomaly is always present and that none of the previously mentioned parameters significantly favor the development of it. A second result is the presence of a 27 day signal superposed to the semiannual anomaly which is significantly affected by the solar activity level.

A different interpretation of the annual and semiannual anomalies on the magnetic activity over the Earth

“…The data series for the 112 observatories were processed following the technique described in Azpilicueta et al [2012]. The basic steps behind this technique are: i) daily mean values are computed reducing the database to one value per day; ii) for each year of data, a linear trend is adjusted and subtracted thus obtaining for each observatory a series of deviations of the H‐component (H‐deviations) from the value expected according to the linear trend; iii) finally an annual characteristic pattern for each observatory is obtained by computing the mean deviation for each DOY (day of the year).…”