ANGEOAnnales GeophysicaeANGEOAnn. Geophys.1432-0576Copernicus GmbHGöttingen, Germany10.5194/angeo-33-697-2015The influence of solar wind variability on magnetospheric ULF wave powerPokhotelovD.d.pokhotelov@ucl.ac.ukhttps://orcid.org/0000-0002-3712-0597RaeI. J.https://orcid.org/0000-0002-2637-4786MurphyK. R.MannI. R.https://orcid.org/0000-0003-1004-7841Mullard Space Science Laboratory, UCL, Dorking, Surrey, UKNASA Goddard Space Flight Center, Greenbelt, Maryland, USADepartment of Physics, University of Alberta, Edmonton, Alberta, CanadaD. Pokhotelov (d.pokhotelov@ucl.ac.uk)8June20153366977011April20157May20158May2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://angeo.copernicus.org/articles/33/697/2015/angeo-33-697-2015.htmlThe full text article is available as a PDF file from https://angeo.copernicus.org/articles/33/697/2015/angeo-33-697-2015.pdf
Magnetospheric ultra-low frequency (ULF) oscillations in the Pc 4–5 frequency
range play an important role in the dynamics of Earth's radiation belts, both
by enhancing the radial diffusion through incoherent interactions and through
the coherent drift-resonant interactions with trapped radiation belt
electrons. The statistical distributions of magnetospheric ULF wave power are
known to be strongly dependent on solar wind parameters such as solar wind
speed and interplanetary magnetic field (IMF) orientation. Statistical characterisation of ULF wave power in
the magnetosphere traditionally relies on average solar wind–IMF conditions
over a specific time period. In this brief report, we perform an alternative
characterisation of the solar wind influence on magnetospheric ULF wave
activity through the characterisation of the solar wind driver by its
variability using the standard deviation of solar wind parameters rather than
a simple time average. We present a statistical study of nearly one solar
cycle (1996–2004) of geosynchronous observations of magnetic ULF wave power
and find that there is significant variation in ULF wave powers as a function
of the dynamic properties of the solar wind. In particular, we find that the
variability in IMF vector, rather than variabilities in other parameters
(solar wind density, bulk velocity and ion temperature), plays the strongest
role in controlling geosynchronous ULF power. We conclude that, although
time-averaged bulk properties of the solar wind are a key factor in driving
ULF powers in the magnetosphere, the solar wind variability can be an
important contributor as well. This highlights the potential importance of
including solar wind variability especially in studies of ULF wave dynamics
in order to assess the efficiency of solar wind–magnetosphere
coupling.
Magnetospheric physics (solar wind–magnetosphere interactions) – space plasma physics (waves and instabilities)Introduction
Ultra-low frequency (ULF) waves in the Pc 4–5 range (45–600 s period; 2–22 mHz;
) were theoretically described by
and originally characterised by ground-based magnetometer observations
. For instance, ULF oscillations can
act to enhance radial diffusion serving as a diffusive mechanism for the
energisation of radiation belt electrons and ions . Also the resonant interaction between azimuthally drifting
radiation belt electrons and standing Pc 4–5 ULF waves has been analysed
both theoretically and numerically , and
there is growing observational evidence that coherent drift resonance
interactions between large-amplitude ULF waves and electrons contribute to
electron acceleration in the radiation belts .
The interplanetary sources of standing ULF waves were proposed in the
original works of , and ground magnetometer studies have
confirmed the relations between solar wind parameters and the intensity of
magnetospheric ULF waves. In particular, the solar wind speed has been shown
to be the crucial parameter in controlling ULF power
,
especially in the dayside and morning sectors and peaking at magnetic shells
L=6–7 e.g.. It has also been suggested that ULF
pulsations in Pc 4–5 range could be directly driven by periodic solar wind
pressure pulses though the physical mechanism of energy
transfer across the bow shock and magnetopause remains unclear. The mechanisms
of magnetopause energy transfer in the relevant frequency range
e.g. may involve solar wind pressure pulses,
impulsive penetration, Kelvin–Helmholtz instability and flux transfer events,
with each of those mechanisms requiring distinct solar wind driving
properties. Some of those mechanisms may become dominant during specific
phases of geomagnetic disturbances, during specific solar wind regime (i.e.
slow or fast solar wind) and during specific phases of the solar cycle
dominated by slow or fast solar wind flows e.g..
In this study, we present a statistical characterisation of ULF wave power
inside the magnetosphere parametrised by the variability of solar wind rather
than by time-averaged solar wind properties. Since the magnetospheric ULF
power is typically characterised by power spectral densities, i.e. by dynamic
spectral characteristics, it seems reasonable to characterise the solar wind
flow by its dynamic characteristics rather than by simple time averages.
Earlier works outlined the importance of solar wind variability for the
geoeffectiveness of solar wind flow and for the
intensification of relativistic electron fluxes in the outer radiation belts
.
A formal statistical approach is taken to initially describe this solar wind
variability by the standard deviations of solar wind parameters over a certain
time interval. Quantiles of the standard deviations are then computed to
estimate which of the solar wind variability parameters has a stronger impact
on magnetospheric ULF power. The ULF power is characterised here by the power
spectral density (PSD) in the Pc 4–5 frequency range measured at the
geostationary orbit by magnetometer on-board the GOES spacecraft over a large
portion of the solar cycle 23 (years 1996–2004). This approach allows
conclusions to be made about the relative importance of different solar wind
variabilities responsible for the intensification of ULF power in the
magnetosphere. It is demonstrated that the ULF power in the magnetosphere is
most sensitive to the variability of interplanetary magnetic field (IMF) (as characterised by the hourly
standard deviation of IMF vector) and substantially less sensitive to the
variability of other basic solar wind parameters (solar wind proton
temperature, density and bulk velocity).
Data setsGOES ULF data
We use data from the GOES East spacecraft, located at geostationary orbit
around 357∘ geomagnetic longitude and 11∘ geomagnetic
latitude. The data from GOES 8 (1996–2003) and GOES 12 (2003–2004),
subsequently located at the GOES East slot, have been used. Following
the approach of , three-axis fluxgate magnetometer data at
1 min resolution have been rotated into field-aligned coordinates where
the z axis is aligned with the main magnetic field, with the x axis pointing radially
outwards from the Earth and y axis pointing eastwards.
This coordinate system was constructed using a background running mean
magnetic field estimate of 30 min, and we use the same database used in this
study, between 1996 to 2004, inclusive. Time intervals when the GOES spacecraft
may have been located near, or outside of, the magnetopause have been
excluded from this data set by estimating the magnetopause stand-off distance
using simple pressure balance relation and excluding the hourly intervals
when the magnetopause is expected to be within 8 RE radial
distance. The PSDs were calculated using a 1 h fast Fourier transform, as in
and .
ULF wave power spectral density (PSD) as a function of solar wind
variability. Median values of radial magnetic field (Bx
component) PSDs are computed between sextiles of standard deviations of
(a) interplanetary magnetic field vector, (b) solar wind
ion temperature, (c) solar wind plasma density and (d)
solar wind flow speed. The sextiles of solar wind variability are computed
for the conditions when mean solar wind speed exceeds 450 km s-1.
Dotted lines and dashed lines indicate the median values of GOES PSDs for all solar
wind conditions when the mean solar wind speed exceeds 400 and
500 km s-1, respectively. For reference, the values of median and
upper sextile of the solar wind parameters are given here: for σ(BV) are 2.5 and 4.0 nT, for σ(TSW) are 1.86×104 and 3.89×104 K, for σ(NSW) are 0.3
and 0.7 cm-3 and for σ(VSW) are 9 and
16 km s-1, for the median and the upper sextiles, respectively.
Solar wind data
We use data from the OMNI solar wind database
http://omniweb.gsfc.nasa.gov, which provides solar wind and IMF
parameters from the Advanced Composition Explorer (ACE) and Wind spacecraft,
generated from 1 to 4 min resolution data time-shifted to upstream the
Earth's bow shock . Solar wind variability is characterised
by the hourly standard deviations of IMF
vector σ(BV), solar wind ion temperature
σ(TSW), solar wind plasma density σ(NSW),
and solar wind bulk velocity σ(VSW) provided by the OMNI
database. The standard deviation of IMF vector is defined as the length of
the vector formed from the standard deviations of IMF components, i.e.
σ(BV)=(σ(Bx)2+σ(By)2+σ(Bz)2)1/2.
The parameters are chosen to represent the basic properties of solar wind
plasma without making any a priori assumptions about their relevance to
specific solar wind–magnetosphere coupling mechanisms.
Geosynchronous ULF wave power as a function of solar wind variability
The data set of GOES PSDs has been split into four magnetic local time (MLT)
sectors: midnight (21:00–03:00 MLT), dawn (03:00–09:00 MLT), noon
(09:00–15:00 MLT) and dusk (15:00–21:00 MLT). From the data set of standard deviations of
four solar wind parameters – σ(BV), σ(TSW),
σ(NSW) and σ(VSW) – the 6-quantiles
(sextiles) of the distribution of solar wind parameters have been computed.
The median values of GOES PSDs in each MLT sector are then computed in the
intervals between each of the sextile for the four solar wind parameters.
Figure 1 presents the median values of GOES PSDs computed between sextiles of
solar wind parameters, with colours in rainbow sequence (black to blue to
red, solid lines) corresponding to higher sextiles. The sextiles of solar
wind variability are computed for the conditions when mean solar wind speed
exceeds 〈VSW〉= 450 km s-1. This threshold
is chosen to separate the solar wind regimes dominated by fast and slow solar
wind . To illustrate the increase in ULF PSD power
under higher mean solar wind speed known from previous studies
, the median values of GOES PSDs for all
solar wind conditions whenever the mean solar wind speed exceeds 400 and
500 km s-1 are shown, respectively, by dotted lines and dashed lines. This
demonstrates the increase in ULF PSD during geomagnetically disturbed
periods.
The median spectral power presented in Fig. 1 is computed over the dayside
MLT sector of the magnetosphere (MLT = 09:00–15:00). This MLT sector is
chosen because earlier studies of the solar wind control
e.g. demonstrated the solar wind control to be most
effective in the dayside and morning sectors. Other MLT sectors (analysed in
this study but not shown here) demonstrate similar dependencies on solar wind
variability. We only show the dependence of radial (Bx) magnetic
component corresponding to the poloidal Alfvén waves expected to be the
most relevant to drift resonance interactions with radiation belt electrons
. The other two magnetic components (azimuthal
By and compressional Bz) demonstrate similar solar
wind dependencies supporting the conclusions below.
Discussion and summary
As summarised in Fig. 1, the higher solar wind variability corresponds to the
higher values of ULF spectral power in the magnetosphere. It is also clear
that the ULF power substantially increases during the periods of higher mean
solar wind. This study is not aimed at quantifying the relative importance of mean
solar wind parameters vs. their variabilities for the control of
magnetospheric ULF power. However from the comparison of sextiles in Fig. 1
and the median PSD values above 〈VSW〉= 400 and
500 km s-1, we can conclude that the solar wind variability has a
pronounced effect on ULF power. It has to be pointed out that earlier studies
e.g. used a substantially wider range of mean solar
wind values (with the highest bin above 700 km s-1) – thus showing
higher values of ULF PSDs under extreme solar wind conditions compared to
those in Fig. 1. The ULF PSDs shown in Fig. 1 do not demonstrate a clear peak
at the fundamental harmonic of field line resonances that is consistent with
earlier studies at the geostationary orbit.
presented mean electric and magnetic field PSDs calculated from 6 months of
GEOS-2 data showing a broad peak in the electric field PSD around 3 mHz (the
fundamental harmonic of field line resonances) with no clear peak in the
magnetic field PSD. Recent studies of the magnetic ULF PSDs using GOES data
e.g. also showed magnetic PSDs close
to the power law, similar to those in Fig. 1. The small deviations from the
power law around 1.5–2 mHz seen in Fig. 1 are unlikely to be related to a
field resonance frequency and could be either a feature of the magnetopause
penetration or solar wind driving.
The data set presented here does not show particularly strong
interdependencies, with the linear Pearson correlation coefficients between
solar wind hourly means and standard deviations being in the range of
0.5–0.6. However the interdependence between mean solar wind parameters and
their variabilities can further complicate the analysis and needs to be
addressed carefully.
The formal statistical approach used in this study allows one to assess the
magnetospheric response to variability of different solar wind parameters
without making an a priori assumptions about the physical mechanisms driving
the magnetospheric ULF power. As seen from Figure 1, the response of ULF
spectral power to the variability of different solar wind parameters differs
dramatically, with the response to the variability in IMF vector being the
most pronounced. Stronger ULF response to the variability of IMF
BV relative to other solar wind parameters suggests the
importance of quasi-periodic IMF variations, such as those carried by high-speed solar wind streams . This outlines the
necessity of analysing the nature of variability of the solar wind under
different solar wind conditions, such as fast and slow solar wind regime, as
well as during different phases of interplanetary coronal mass ejections,
such as sheath and ejecta, characterised by different levels of fluctuations
. A more comprehensive approach to the problem would be
to characterise the solar wind variability by cross-correlations between
different solar wind parameters thus allowing one to deduce the nature of solar
wind variability, leading to the solar wind characteristics such as
compressiveness or Alfvénicity . Moreover
this is important to analyse the impact of solar wind driving and variability
on the azimuthal structure of excited ULF waves as the azimuthal wave number
(m) will strongly impact the resonance interactions with radiation belt
particles e.g. and the high-m number waves may
significantly contribute to the statistics .
This study represents a first attempt to characterise the ULF power by
variability of solar wind drivers rather than by average values of solar wind
parameters over a certain interval. This demonstrates that the solar wind
variability plays a noticeable role in the control of magnetospheric ULF power
and this needs to be taken into account when considering the impact of different
types of solar wind forcing, though the relative importance of solar wind
mean parameters vs. their variabilities for the control of ULF power needs to
addressed in a separate study.
Acknowledgements
D. Pokhotelov and I. J. Rae are supported by Science and Technology
Facilities Council (STFC) grant ST/L000563/1; I. J. Rae is also supported by
Natural Environment Research Council (NERC) grants NE/M00886X/1 and
NE/L007495/1. K. R. Murphy is funded by a Canadian NSERC Postdoctoral Fellowship. We
thank H. Singer and NOAA for the use of GOES magnetometer data, obtained from
NASA CDAWeb (http://cdaweb.gsfc.nasa.gov/). Solar wind data were obtained
from NASA OMNIWeb (http://omniweb.gsfc.nasa.gov/). The topical editor L. Blomberg thanks K. Takahashi for
help in evaluating this paper.
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