Coincident 1.3-year Periodicities in the ap Geomagnetic Index and the Solar Wind

Recent observations show an approximately 1.3-year period in the speed of the solar wind detected by the IMP 8 and Voyager 2 spacecraft. A similar period is also seen in the north-south (GSE) component of the magnetic field observed by IMP 8. Since both parameters are commonly used as input to models of geomagnetic activity, the 'ap' index (a measure of geomagnetic disturbance) is examined to look for this periodicity. The Lomb-Scargle periodogram method is used on the ap, plasma, and magnetic field data during the 1973-1994 time range. A dynamic FFT periodogram method is also used to analyze the ap data during this time, as well as to look for periods present between 1932 and 1972. A clear 1.3-year periodicity is present in the post-1986 data when the same period is observed in the plasma and field data. The V(2)B(zsm) and V(2)B(s) proxies for geomagnetic activity also show this periodicity. However, the southward (GSM) component of the magnetic field does not have a 1.3-year period, and neither do solar wind or ap data from 1973-1985. This demonstrates that the ap geomagnetic index can act as a proxy for solar wind periodicities at this time scale. Historic ap data are examined, and show that a similar periodicity in ap exists around 1942. Since auroral data show a 1.4-year periodicity, all these similar periods may result from a common underlying solar mechanism

The Scientific Foundations of Forecasting Magnetospheric Space Weather

The magnetosphere is the lens through which solar space weather phenomena are focused and directed towards the Earth. In particular, the non-linear interaction of the solar wind with the Earth's magnetic field leads to the formation of highly inhomogenous electrical currents in the ionosphere which can ultimately result in damage to and problems with the operation of power distribution networks. Since electric power is the fundamental cornerstone of modern life, the interruption of power is the primary pathway by which space weather has impact on human activity and technology. Consequently, in the context of space weather, it is the ability to predict geomagnetic activity that is of key importance. This is usually stated in terms of geomagnetic storms, but we argue that in fact it is the substorm phenomenon which contains the crucial physics, and therefore prediction of substorm occurrence, severity and duration, either within the context of a longer-lasting geomagnetic storm, but potentially also as an isolated event, is of critical importance. Here we review the physics of the magnetosphere in the frame of space weather forecasting, focusing on recent results, current understanding, and an assessment of probable future developments.Peer reviewe

The Orientation of Plasma Structure in the Solar Wind

. Data from the ISEE 3# IMP 8# and WIND spacecraft are used to #nd the average east#west orientation of plasma structures in the solar wind. We determine the lags which# after radial propagation e#ects are removed# give the best correlations between data sets. These lags# when combined with the spacecraft positions and solar wind speeds# are then used to calculate the front angles of the propagating plasma. The average front normals are neither radial nor perpendicular to the magnetic #eld# but are roughly halfwaybetween. Front angle distributions peak at lower angles near solar maximum than at solar minimum. These results may indicate that time#dependentchanges in the solar wind source are as important as longitudinal variations of the source in producing the solar wind structure observed near Earth. 1. Introduction The interplanetary magnetic #eld #IMF# direction at Earth is determined by the Sun#s rotation# the speed of the solar wind which carries the #eld outward# stream interac..

A Comparison of Solar Wind Parameters from t Experiments on the IMP 8 and Wind Spacecraf

This paper compares solar wind speeds and densities derived fr

Meridional Flow in the Solar Wind

8 a We look for evidence of meridional flow in the solar wind using data from IMP nd Voyager 2. Magnetic field data are used to separate the plasma data according to - d whether the spacecraft is above or below the heliospheric current sheet. IMP 8 meri ional velocities are predominately poleward, with an average poleward flow of 1 km/s f e in each hemisphere. Voyager 2 velocities are also generally poleward, but regions o quatorward flow are also observed; the largest poleward speeds (4 km/s) occur near t f solar minimum. The magnitude of the poleward flow is not large enough to accoun or the magnetic flux deficits observed by Pioneer 10. T Introduction he concept that meridional plasma flows are implied by Parker's [1958] spiral field e t approximation was first developed by Winge and Coleman [1972]. They generaliz he Weber-Davis model of the solar wind [Weber and Davis, 1967] to include latitudil p nal effects and find that the resulting equations predict that the sola..

Solar wind correlations: Statistical and case studies

Recent work on solar wind plasma correlations using data from several widely-separated spacecraft (IMP 8, INTERBALL-I, WIND, and ISEE-3) has shown that, for 6-hour periods, the average plasma correlation is 0.7. The focus of these studies has been directed toward a statistical understanding of gross solar wind correlation behavior. In all correlations examined, lower average correlations are caused by the presence of many points from the low correlation subpopulation; nevertheless, data points from the high correlation population are still present. No single organizational factor has yet been found which adequately separates low-correlation periods from high-correlation periods. Some of the spread in correlations is due to the spatial orientations and dimensions of solar wind structures, and thus to the locatiohal alignments of the spacecraft being correlated, but this does not adequately explain all the good or poor correlations since sometimes three nearby spacecraft show poor correlations, while sometimes three widely-separated spacecraft show good correlations. Thus, in order to understand the underlying physics, detailed investigation of individual cases has been undertaken. These results will be important in assigning quality measures to space weather predictions using satellite measurements taken at L1, for example