PUBLICATIONS
Journal of Geophysical Research: Space Physics
RESEARCH ARTICLE
10.1002/2014JA020768
Key Points:
• Correcting HWM93 neutral winds
using IPE model and F3/C hmF2
• Improving IPE electron density using
the corrected neutral winds
• Simulation of the eastward movement
of the southern MSNA/WSA
Field-aligned neutral wind bias correction scheme
for global ionospheric modeling at midlatitudes
by assimilating FORMOSAT-3/COSMIC hmF2 data
under geomagnetically quiet conditions
Yang-Yi Sun1,2,3, Tomoko Matsuo1,2, Naomi Maruyama1,2, and Jann-Yenq Liu3
1
Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Boulder, Colorado, USA,
Space Weather Prediction Center, National Oceanic and Atmospheric Administration, Boulder, Colorado, USA, 3Institute of
Space Science, National Central University, Chung-Li, Taiwan
2
Correspondence to:
J.-Y. Liu,
[email protected]
Citation:
Sun, Y.-Y., T. Matsuo, N. Maruyama, and
J.-Y. Liu (2015), Field-aligned neutral
wind bias correction scheme for global
ionospheric modeling at midlatitudes
by assimilating FORMOSAT-3/COSMIC
hmF2 data under geomagnetically quiet
conditions, J. Geophys. Res. Space
Physics, 120, 3130–3149, doi:10.1002/
2014JA020768.
Received 27 OCT 2014
Accepted 10 MAR 2015
Accepted article online 13 MAR 2015
Published online 20 APR 2015
Abstract
This study demonstrates the usage of a data assimilation procedure, which ingests the
FORMOSAT-3/COSMIC (F3/C) hmF2 observations to correct the model wind biases to enhance the capability
of the new global Ionosphere Plasmasphere Electrodynamics (IPE) model under geomagnetically quiet
conditions. The IPE model is built upon the field line interhemispheric plasma model with a realistic
geomagnetic field model and empirical model drivers. The hmF2 observed by the F3/C radio occultation
technique is utilized to adjust global thermospheric field-aligned neutral winds (i.e., a component of the
thermospheric neutral wind parallel to the magnetic field) at midlatitudes according to a linear relationship
between time differentials of the field-aligned wind and hmF2. The adjusted winds are further applied to
drive the IPE model. The comparison of the modeled electron density with the observations of F3/C and
ground-based GPS receivers at the 2012 March equinox suggests that the modeled electron density can be
significantly improved in the midlatitude regions of the Southern Hemisphere, if the wind correction scheme
is applied. Moreover, the F3/C observation, the IPE model, and the wind bias correction scheme are applied to
study the 2012 Southern Hemisphere Midlatitude Summer Nighttime Anomaly (southern MSNA)/Weddell
Sea Anomaly (WSA) event at December solstice for examining the role of the neutral winds in controlling
the longitudinal variation of the southern MSNA/WSA behavior. With the help of the wind bias correction
scheme, the IPE model better tracks the F3/C-observed eastward movement of the southern MSNA/WSA
feature. The apparent eastward movement of the southern MSNA/WSA features in the local time coordinate
is primarily caused by the longitudinal variation in the declination angle of the geomagnetic field that
controls the field-aligned projection of both geographic meridional and zonal components of the neutral
wind. Both the IPE simulations and the F3/C observations show the significant longitudinal variation in the
speed of the eastward movement of the southern MSNA/WSA.
1. Introduction
The balance between plasma production, loss, and transport processes determines the distribution of
ionospheric electron density, and thermospheric parameters such as neutral wind and composition greatly
affect these processes. The discrepancy between the modeled and observed ionospheric electron density
often results from inadequately specified thermospheric drivers. Global observations of the thermospheric
parameters remain scarce at ionospheric F region altitudes, while global electron density measurements have
become relatively abundant thanks to radio occultation (RO) missions like the FORMOSAT-3/COSMIC (F3/C).
One way to overcome this difficulty is to estimate thermospheric drivers from global electron density
observations. Luan and Solomon [2008] showed the feasibility of the estimation of the midlatitude
thermospheric meridional neutral wind from the F3/C-observed ionospheric F2 layer peak height (hmF2)
based on the servo model [Rishbeth, 1967; Rishbeth et al., 1978]. Datta-Barua et al. [2009] proposed the
Estimating Model Parameters from Ionospheric Reverse Engineering method to estimate the field-aligned
neutral wind ionospheric driver by using four-dimensional images of global electron density.
Currently, the most promising approach for ionospheric weather specification is data assimilation, which
combines physics-based models with observations. Much research effort has been spent on developing global
data assimilation models in the recent decade for specifying the ionospheric weather [e.g., Scherliess et al., 2011;
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10.1002/2014JA020768
Komjathy et al., 2012, and references therein]. Scherliess et al. [2011] suggested that failures of physics-based
ionospheric models to specify ionospheric weather are largely attributed to a lack of reliable specifications of
the ionospheric drivers, such as the thermospheric winds and composition, the equatorial and high-latitude
electric fields, and the high-latitude particle precipitation.
The objective of this study is to develop a field-aligned neutral wind bias correction scheme that is capable
of adjusting the thermospheric field-aligned neutral winds (i.e., a component of the neutral winds parallel
to the magnetic field line) in an ionosphere and plasmasphere model by assimilating the global F3/C hmF2
observations under geomagnetically quiet conditions. The scheme is expected to improve the modeled
plasma density distribution due to a better specified neutral wind driver. The ionosphere and plasmasphere
model utilized in this study is the Ionosphere Plasmasphere Electrodynamics (IPE) model [Maruyama et al.,
2014], which has been recently developed at the National Oceanic and Atmospheric Administration (NOAA)
and the Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado. The
IPE model is built upon the field line interhemispheric plasma (FLIP) model [Richards and Torr, 1996] using
magnetic apex coordinates [Richmond, 1995] with realistic geomagnetic fields (International Geomagnetic
Reference Field, IGRF; http://www.ngdc.noaa.gov/IAGA/vmod/igrf.html).
FLIP is a one-dimensional (1-D) model that calculates the plasma densities and temperatures along an entire
magnetic flux tube. Since the component of the thermospheric neutral wind along the magnetic meridional
direction is one of the key model drivers of FLIP, an algorithm has been proposed by Miller et al. [1986]
and Richards [1991] to estimate the meridional wind from hmF2 observations of ground-based ionosondes
and incoherent scatter radars (ISRs). Numerous studies showed that this algorithm performs satisfactorily
in geomagnetic midlatitudes and has greatly improved the FLIP plasma density [e.g., Richards, 2001, 2002;
Richards et al., 1994a, 1994b, 2009, 2010, and references therein] over particular locations. The wind bias
correction scheme described in this paper extends the works of Miller et al. [1986] and Richards [1991].
Not only the meridional wind but also some other key parameters have been adjusted for FLIP. For example,
Richards et al. [1998, 2010] presented the FLIP model neutral density modification algorithm to adjust the
model neutral densities and temperature according to the changes that are needed to reproduce the
electron density. In contrast to using electron density observations from individual ground-based observatories
to adjust model drivers in the 1-D FLIP model, the GPS occultation experiment on board F3/C measures the
ionospheric electron density globally, including the ocean, desert, and polar regions, where ground-based
observatories are scarce. Therefore, it enables us to modify the midlatitude meridional winds and electron
density for the global IPE model.
In this paper, the improved electron density in the IPE simulations is first compared with the F3/C-observed
electron density and the ground-based GPS total electron content (TEC, 1 TEC unit = 1016 el m2) observations
at the March equinox. To verify the reliability of the wind bias correction scheme for modifying the
thermospheric field-aligned neutral winds and electron density at midlatitudes in the IPE model, we further
study an ionospheric weather event—the 2012 Southern Hemisphere Midlatitude Summer Nighttime
Anomaly (southern MSNA)/Weddell Sea Anomaly (WSA). The WSA is a midlatitude ionospheric phenomenon,
which is characterized by a greater nighttime electron density than during daytime values near the Weddell
Sea [e.g., Bellchambers and Piggott, 1958]. Recent studies suggested that the component of thermospheric
neutral winds projected on the geomagnetic field greatly controls the formation of the WSA [e.g., Horvath
and Essex, 2003; Horvath, 2006; Lin et al., 2009; Jee et al., 2009; Liu et al., 2010a; Chen et al., 2011]. Ren et al.
[2012] successfully simulated the global MSNA (including WSA) using the three-dimensional (3-D) Theoretical
Ionospheric Model of the Earth at the Institute of Geology and Geophysics, Chinese Academy of Sciences,
with the magnetic apex coordinates, and showed the importance of the realistic geomagnetic field in the
model simulation. Jee et al. [2009] examined TOPEX TEC measurements at various global fixed local times and
found that the TEC enhancements of the WSA at night initially form over the whole Pacific sector in the
evening but gradually taper to the far eastern Pacific region near midnight and move slightly eastward over
nighttime. The cross-comparison of the 3-D F3/C electron density with horizontal wind model 93 (HWM93)
[Hedin et al., 1996] field-aligned winds by Liu et al. [2013] shows the agreement between the eastward
movements of the MSNA and that of the peak value of the field-aligned winds. They concluded that the
meridional and vertical plasma flow caused by neutral winds play important roles in the eastward
propagation of the southern MSNA/WSA feature. Chen et al. [2013] employed a 3-D ionosphere model,
SAMI3, with the thermospheric neutral winds provided by the National Center for Atmospheric Research
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Table 1. Locations of the Ground-Based GPS Stations and the RMS of the Differences Between the Observed and
a
Modeled TECs With and Without the Wind Bias Correction
GPS Station
acu5
artu
pets
palm
marn
hob2
Geographic
Longitude
Geographic
Latitude
Geomagnetic
Latitude
RMSGPS
RMSGPS
(With Correction)
RMSF3/C
RMSF3/C
(With Correction)
70.89°W
58.56°E
158.65°E
64.05°W
37.86°E
147.44°E
41.74°N
56.43°N
53.02°N
64.78°S
46.68°S
42.80°S
51.42°N
49.18°N
46.05°N
54.84°S
49.58°S
49.81°S
5.01
2.44
2.78
6.03
3.28
3.20
6.60
2.13
4.40
1.63
3.47
3.65
3.79
3.11
2.71
5.51
4.05
3.75
4.56
2.89
3.72
1.38
3.12
4.01
a
The RMS values are computed from the TEC differences at a given location over the whole 24 h period.
Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) and global scale wave
model (GSWM) to simulate MSNA structures, including the eastward drift feature of the southern MSNA/WSA.
They suggested that the tidal waves from the mesosphere and lower thermosphere (MLT) region can
affect the formation of the eastward movement of the southern MSNA/WSA. Xiong and Lühr [2014] analyzed
the Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment electron
density observations and suggested that the WSA is caused by a simultaneous constructive interference
of the diurnal standing (D0), westward wave number 2 (DW2), and stationary planetary wave number 1
(SPW1) components in electron density. Chang et al. [2015] reported that the features of the WSA can be
reconstructed as the result of superposition between the D0, eastward wave number 1, DW2, and SPW1
components in F3/C TECs, producing the characteristic midnight WSA peak. According to these studies, we
investigate the cause of the southern MSNA/WSA feature by using the IPE model with the magnetic apex
coordinates and the better specified thermospheric field-aligned neutral winds inferred from the global F3/C
hmF2 observations by using the wind bias correction scheme.
2. Data
The hmF2 observation from each F3/C radio occultation (RO) electron density profile is the primary data set to
be used in the wind bias correction scheme. The F3/C mission consists of six microsatellites in the different
mission planes, which provide around 1000–2500 daily ionospheric electron density profiles globally by using
the RO observation technique. RO observations, particularly from F3/C, have significantly improved our
capability of monitoring the global ionosphere [e.g., Schreiner et al., 2007]. The F3/C RO electron density
profiles are adopted from the ionPrf file in the second data level, which is processed by the COSMIC Data
Analysis and Archive Center (http://cosmic-io.cosmic.ucar.edu/cdaac/index.html), using the Abel inversion
technique from TEC along LEO-GPS (Low Earth Orbit–Global Positioning System) rays since May 2006. Yue
et al. [2010] and Liu et al. [2010b] reported that the ionospheric F2 layer peak height (hmF2) and peak density
(NmF2) from the RO measurements are reliable after the Abel inversion although the electron density profiles
obtained by the Abel inversion have large errors below about 200 km. Also the works by Lei et al. [2007]
and Krankowski et al. [2011] showed that the RO technique-retrieved hmF2 are generally in good agreement
with those from ISR and ionosonde observations. Since the IPE model with the field-aligned wind bias
correction scheme shown in this study is designed and appropriate for geomagnetically quiet conditions, the
F3/C and ground-based GPS observations for Kp > 3+ were eliminated. Because the F3/C data observed in
a short period are sparse, this study accumulates the data over 1 month to demonstrate the technique.
We use the F3/C electron density observations from 5 March to 4 April 2012 (day of year (DOY) 80 ± 15 days)
and from 6 December 2012 to 5 January 2013 (DOY 356 ± 15 days) for Kp ≦ 3+ to examine the method capability
and the southern MSNA/WSA event. Extreme values of F3/C hmF2, below 200 km and above 500 km, were
eliminated from the data set because they may result from transiently fluctuated electron density profiles.
We also compare the modeled TEC with the ground-based GPS TEC from six midlatitude locations at
the March equinox in 2012. Measurements from the ground-based GPS receivers located at acu5, artu,
pets, marn, hob2, and palm stations (Table 1) are obtained from the International Global Navigation
Satellite Systems (GNSS) Service database. Each GPS satellite transmits radio signals in two frequencies
(f1 = 1575.42 MHz and f2 = 1227.60 MHz). Since the ionosphere is a dispersive medium, electron density
information can be retrieved from modulations on carrier phases and code phases recorded by dual-frequency
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receivers [Sardón et al., 1994; Liu et al., 1996]. The slant TEC is the integration of electron density along the
ray path from a ground-based GPS receiver to a GPS satellite (~20,200 km). From recorded broadcast ephemeris
and given a sub-ionospheric height (300 km), the slant TEC along the ray path can be converted to the vertical
TEC at its associated longitude and latitude [Tsai and Liu, 1999].
3. Model
We use the new, time-dependent, 3-D, global Ionosphere Plasmasphere Electrodynamics (IPE) model
[Maruyama et al., 2014] for the purpose of developing the field-aligned neutral wind bias correction scheme.
The IPE model is based on the field line interhemispheric plasma (FLIP) model [Richards and Torr, 1996] for the
parallel plasma transport. The additional features have been included to FLIP for an improved prediction
of the global dynamic of the ionosphere and plasmasphere, such as including the global seamless plasma
transport in the direction perpendicular to the magnetic field, the self-consistent electrodynamic solver
[Richmond and Maute, 2014], and the IGRF geomagnetic field model using the apex coordinate [Richmond,
1995]. The version of IPE with empirical model drivers was employed in this study in order to simplify the
implementation of the bias correction schemes. Both HWM93 and HWM07 neutral winds were inputted
into IPE to simulate the WSA before this wind bias correction study. The simulation using HWM93 is better
than that using HWM07 at midlatitude. Accordingly, initial specification of the neutral wind in this study is
obtained from HWM93. The meridional (UM) and zonal (UZ) winds in the geographic frame obtained from
HWM93 have been projected onto the geomagnetic field lines (U∥) through Equation 5.6 in Richmond [1995]:
⇀
⇀
⇀
U∥ ¼ d 3 U M þ U Z ;
(1)
⇀
where d3 is the base vector, which is parallel to the geomagnetic field lines. The field-aligned winds are further
passed to the parallel transport solver for the ion continuity and momentum equations [Torr et al., 1990].
Other drivers specified by empirical models are held unchanged throughout the entire numerical
experiments used in this study. Specification of thermospheric densities and temperature is obtained from
the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar model (NRLMSISE-00) [Picone
et al., 2002]. The empirical models are used in this study with regard to the specification of global
climatological electric field, although the IPE model can also calculate the electric field self-consistently. The
low-latitude and midlatitude vertical drifts and high-latitude convection electric fields are computed from
the empirical models of Scherliess and Fejer [1999] and Weimer [1996], respectively.
The IPE model simulates nine global ion species O+, H+, He+, N+, NO+, O2+, N2+, O+(2D), and O+(2P) as well
as electron and ion temperatures and parallel plasma drift velocities for the major ions every time step
(usually 5 min). The electron density used in this study is the summation of the densities of the nine ion
species. The spatial resolution of the IPE model is very flexible. The version used in this study consists
of 80 grid points in magnetic longitude (resolution is 4.5°). Each meridian consists of 170 closed field
lines covering within ±88.12° magnetic latitude. The spatial resolution is variable in latitude: average
resolutions are 1.26° and 0.24° beyond and within ±30 magnetic latitudes, respectively. The finer
resolution within ±30° magnetic latitudes is optimized to resolve the dynamical feature of the equatorial
ionization anomaly. The number of grid points along a field line ranges from 11 to 1115 from the dip
equator to the highest latitude. The height increment varies from 2 to 10 km below 600 km altitude.
The following monthly values of F10.7, Ap, and Kp indices are given as model inputs to drive empirical
models such as HWM, Mass Spectrometer Incoherent Scatter (MSIS), and empirical electric field models.
Since the current version of the wind bias correction scheme is designed for geomagnetically quiet
conditions, the observational data for Kp ≦ 3+ are used in this study. The mean values of the observed F10.7
(http://omniweb.gsfc.nasa.gov/) during the data periods of 5 March to 4 April 2012 (±15 days centered on
20 March 2012) and 6 December 2012 to 5 January 2013 (±15 days centered on 21 December 2012) for
Kp ≦ 3+ are 110 (1022 W m2 Hz1). The median values of Ap are 6 and 3 during the two data periods for
Kp ≦ 3+, and the corresponding median values of Kp are 2 and 1.
The Burnside factor [Anderson et al., 1998] for the collision frequency is given as 1.7 [Richards and Torr, 1996;
Richards et al., 2009] in this study. Richards et al. [2009] have adopted the Burnside factors of 1.3 and 1.7 for
calculations of FLIP and stated that using a lower Burnside factor could be considered a problem for the hmF2
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calculated using the HWM wind models because these models are partly based on old Poker Flat and Millstone
Hill radar data that were analyzed using a Burnside factor of 1.7. Their calculations indicate that the lower
Burnside factor 1.3 causes hmF2 to be 10–15 km lower at night when the FLIP model uses the HWM winds. The
IPE model has been shown to reproduce a climatological behavior of the electron density and temperature
at midlatitude and low-latitude from CHAMP [Maruyama et al., 2012] and from F3/C [Maruyama et al., 2014].
Furthermore, it has been applied to the examination of the ionospheric response to a terrestrial weather event,
such as sudden stratospheric warming in January 2009 [Millholland et al., 2013].
4. Methodology
A detailed description of the field-aligned neutral wind bias correction scheme developed for the IPE is
presented in this section, along with the earlier work of Miller et al. [1986] and Richards [1991], which serves as
both motivation and foundation of our study. At midlatitude, variations of the hmF2 (Δhm) are primarily
controlled by the variations of the neutral wind component in the magnetic meridian ΔU [e.g., Rishbeth, 1967;
Rishbeth et al., 1978] under geomagnetically quiet conditions. Richards and Torr [1996] suggested that the
wind uncertainty can be greatly reduced by using the algorithm for FLIP proposed by Miller et al. [1986] and
Richards [1991] when hmF2 measurements are available. Numerous studies have shown that the component
of the projected wind in the magnetic meridional direction derived from this algorithm agrees well with the
wind observations in the midlatitude regions, and the modeled plasma density is closer to the observed
value [e.g., Richards, 2001; Richards, 2002; Richards et al., 1994a, 1994b, 2009, 2010, and references therein].
This simple but efficient approach motivated us to develop a field-aligned neutral wind bias correction scheme
for global ionospheric modeling.
4.1. Relationship Between hmF2 and Meridional Wind at Midlatitude
The relationship between the hmF2 (hm) and the component of the neutral wind parallel to the magnetic
meridian ΔU can be represented linearly [Miller et al., 1986] as
α¼
Δhm
:
ΔU
(2)
The equivalent meridional neutral wind is then estimated from hmF2 measurements as
Uðt þ Δt Þ ¼
hm F 2 ðt þ Δt Þ hm ’ðt Þ
þ u’ðtÞ;
αðtÞ
(3)
where hm′(t) and U′(t) are the calculated hmF2 and the equivalent wind at time t [Richards, 1991]. Δt is the
model time step.
To account for the dip angle I effect on α, Miller et al. [1989] introduced the field-aligned relationship α‖
between variations of the position of hmF2 along the field line Δh‖ and field-aligned wind ΔU‖, which is the
projection of meridional and zonal winds on the magnetic field line
αk ¼
Δhk
:
ΔUk
(4)
The relationship between the vertical and field-aligned hmF2 is
Δhm ¼ Δh∥ sinðIÞ:
(5)
The hmF2 observation used in this study is the vertical layer height hm, and the IPE model uses the field-aligned
wind U∥ as an input. Therefore, the relationship αIPE between the hmF2 and field-aligned neutral wind is defined as
αIPE ¼
Δhm
¼ α∥ sinðIÞ
ΔU∥
(6)
for the wind bias correction scheme.
4.2. Field-Aligned Neutral Wind Bias Correction Scheme
The field-aligned neutral wind bias correction scheme is required to ingest global F3/C hmF2 observation into
the IPE model. A wind adjustment is computed at each location from the adjusted hmF2 values. The flowchart
of the wind bias correction scheme shown in Figure 1 describes the flow of algorithm elements executed
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Journal of Geophysical Research: Space Physics
10.1002/2014JA020768
Figure 1. Flowchart of the field-aligned neutral wind (U∥) bias correction scheme for adjusting U∥ at midlatitude by
assimilating the F3/C hmF2 observations.
along with model simulations. The labels “t” and “t + Δt” in the upper and lower sections denote the two time
steps of model simulation. The time interval between two time steps (Δt) is 5 min. The main element of the
scheme is to compute the adjustment to the field-aligned wind according to the global hmF2 distribution,
which is obtained from an assimilative analysis by combining F3/C hmF2 observations with the model
prediction of hmF2. The next step is to feed the adjusted wind back to the model as a driver to modify the
global electron density distribution. The kernel equation of the scheme is
adjU∥hm ðt þ Δt Þ ¼
ashm F 2 ðt þ Δt Þ hm F 2m ðt Þ
þ U∥hm ðtÞ;
αIPE ðtÞ
(7)
in which U∥hm is the modeled field-aligned wind at the hmF2 altitude; hm F 2m is the modeled hmF2; ashm F 2m
is the hmF2 obtained from assimilation analysis of the F3/C hmF2; and adjU∥hm is the adjusted field-aligned
wind at the hmF2 altitude. To spread the wind adjustment information in altitude, a wind normalization
algorithm is employed and will be discussed in the end of this section.
The F3/C provides a fairly global observation of hmF2, although its temporal resolution is inadequate over a
particular location. To obtain a complete map of hmF2 at each model time step, we combine the F3/C hmF2
observations with the IPE hmF2 by using the Kalman filter update formula [Welch and Bishop, 1995]. In the
Kalman filter update formula, the a posteriori state estimate x+ is given by
in which
x þ ¼ x þ K ðz Hx Þ;
(8)
1
K ¼ PHT HPHT þ R ;
(9)
where K is the Kalman gain; z and x are hmF2 obtained from the F3/C observation and the IPE simulation,
respectively. The a priori model error covariance P is parameterized by a Gaussian function. The measurement
error covariance R and the H operator are diagonal matrixes. In order to allow the observed hmF2 to impact
the assimilation analysis of hmF2 as much as possible, the model error is assumed to be much larger than
the measurement error by 5 times. Since observations are accumulated over multiple days in this study,
observations taken further away from the assimilation time could be given larger errors when specifying the
measurement covariance R.
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Figure 2. The observations and simulations in the (top row) Northern and (bottom row) Southern Hemispheres. (fourth and fifth columns) An example of the correction
to the field-aligned winds is shown using the F3/C hmF2 observations at midlatitude. Positive values denote northward winds. (first column) The F3/C hmF2 has been
assimilated with (second column) the IPE hmF2 on the geomagnetic coordinate within 17°–60° geomagnetic latitudes to yield (third column) the assimilative hmF2.
The reasons that the hmF2 and the wind are only being updated within 17°–60° are as follows: (1) the α is a function of sin(I)cos(I) [Miller et al., 1989], which approaches
zero at low- and high latitudes; and (2) the electric field effects are significant at low- and high-latitude regions. Note that only the hmF2 observations within the
+
values of 200–500 km for Kp ≦ 3 are included in the data assimilation procedure.
The F3/C hmF2 observations within ±15 days of a given model day are accumulated and sorted according to the
location and universal time to form a monthly data set for a given model day. For the field-aligned wind
estimation at the model time step t + Δt, the data averaged from t + Δt 60 min to t + Δt are used. In Figure 2
(first column), F3/C hmF2 observations accumulated over DOY 80 ± 15 days within 2300–0000 UT are shown on
the model geomagnetic grid. Figure 2 (top) is for the Northern Hemisphere, and Figure 2 (bottom) is for the
Southern Hemisphere. This particular data set is utilized for the assimilation at 0000 UT model time step.
Accumulation of the F3/C hmF2 observations in this manner provides a better spatial coverage of observations,
even though it obscures the temporal information. The reason for the appearance of sparse data distribution
within ±30°N geomagnetic latitude is an artifact of the irregular model grid resolution, with a higher latitudinal
resolution within the ±30°N geomagnetic latitude region. Figures 2 (second column) and 2 (third column)
show the model and assimilative hmF2 corresponding to 0000 UT on DOY 80. Figures 2 (fourth column) and 2
(fifth column) show the distribution of field-aligned wind at hmF2 (U∥hm ) without and with the wind bias correction
scheme. The impact of the hmF2 changes on the field-aligned wind distribution is evident. Positive values
mean northward field-aligned winds, which blow upward and toward the equator and lift the F2 layer up in the
Southern Hemisphere. Note that the reasons that the hmF2 and the wind are only being updated within 17°–60°
are as follows: (1) the α is a function of sin(I)cos(I) [Miller et al., 1989], which approaches zero at low and high
latitudes; and (2) the electric field effects are significant at low- and high-latitude regions.
The correction shown in Figure 2 is only valid at the hmF2 altitude; however, corresponding wind information
must also be provided to the model at other altitudes in the ionosphere. Therefore, the scheme had to be
developed to enable the wind information to be extended to altitudes other than hmF2. Figure 3 shows an
example of how the wind normalization algorithm has been used to spread the wind adjustment information
(ΔU∥hm ) in altitude.
ΔU∥hm ðt þ ΔtÞ ¼ adjU∥hm ðt þ ΔtÞ U∥hm ðt þ Δt Þ;
(10)
which is only available at hmF2, vertically along the magnetic field line using a stationary correction given by
the following Gaussian function (G) as
GðlÞ ¼ exp
ðl hm F 2 Þ2
:
2c2
(11)
G is computed along the field line (l), and the center of G is located at hmF2. Since the major empirical
orthonormal functions computed from density profiles of the International Reference Ionosphere model
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Figure 3. (a–c) The altitudinal and magnetic longitudinal distributions of field-aligned winds and (d–f) the responding model electron density and hmF2 at 40°S
geomagnetic latitude. The white and black lines are the modeled hmF2 before and after correcting the wind bias. In Figure 3b, we apply the Gaussian function to
spread the value of the differences of field-aligned winds (at hmF2 altitude) before and after correcting the wind bias along the field line (i.e., the wind normalization
algorithm in Figure 1). In Figure 3f, the decrease of the density above and the increase below hmF2 within 60°W–30°E result from the obvious enhancement of the
south and downward wind.
show that the width of the ionospheric main layer is about 200 km [Lin et al., 2015], c is given as 100 km. U∥ is
modified by U∥hm mainly within the F2 layer at the time step t + Δt. The 3-D adjusted field-aligned wind (adjU∥)
is expressed as
adjU∥ ðt þ Δt; lÞ ¼ U∥ ðt þ Δt; l Þ þ Gðl ÞΔU∥hm ðt þ Δt Þ:
(12)
As shown in Figure 3, U∥ is obviously changed by this approach within 30°W and 40°E. The model hmF2
was slightly pulled down, and the electron density was increased below the hmF2 height, and decreased
above. The small difference between the electron density and hmF2 simulations before and after wind bias
correction is due to the fact that this result occurs at the beginning of the model run. The IPE model with the
wind bias correction scheme has been run for 3 days to reach the equilibrium state in this study.
5. Comparison of Model Simulations With Observations
To evaluate the ability of the model wind bias correction scheme, the global model density is compared with
the F3/C and ground-based GPS observations at the March equinox in 2012. Furthermore, a midlatitude
ionospheric weather event—the 2012 southern MSNA/WSA—is examined in detail using the wind bias
correction scheme.
5.1. The 2012 March Equinox
Before presenting the results of the bias correction scheme, an overall agreement of the IPE model and
the F3/C observations is first presented in terms of TEC. Figure 4 is an example of the global comparison of
the F3/C-observed and IPE-simulated TECs at the 2012 March equinox. For a fair comparison of TEC over the
range of F3/C electron density profile data, the modeled TEC is vertically integrated from 90 to 800 km.
Figure 4 (top row) show the F3/C TEC accumulated over a month (DOY 80 ± 15 days) for a given hour range.
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+
Figure 4. (top row) Examples of hourly global distributions of the F3/C vertical TEC observed within DOY 80 ± 15, 2012 for Kp ≦ 3 . The colored dots denote TEC
values and locations of the F3/C ionospheric radio occultation (RO) soundings. The black contour lines sketch the global TEC structure, which is constructed from
the F3/C TEC observations (colored dots) by using a two-dimensional cubic spline interpolation and smoothed by a 3 × 3 moving average window. The spatial
resolution of the contour of F3/C TEC and the color maps (middle and bottom panels) are 5° in longitude by 2.5° in latitude. (middle row) Comparisons of IPE-simulated
and F3/C-observed TEC at the March equinox. (bottom row) Comparisons of the F3/C and IPE TECs after correcting the wind bias. Note that all the black contour
lines shown in this study are F3/C observations. The structure and value of the IPE TEC are generally consistent with that of the F3/C TEC. IPE overestimates the TEC at the
Southern America and Southern India Ocean regions in the morning sector. The modeled TEC becomes closer to the observed TEC if the wind correction scheme was
applied.
Note that all the black contour lines superimposed on TEC maps, shown throughout this paper, are the ones
for the F3/C observations. Figures 4 (middle row) and 4 (bottom row) illustrate a global comparison of the
F3/C and IPE TECs without and with the use of the wind bias correction scheme. Figure 4 (middle row)
suggests that the modeled TEC generally agrees with the observed TEC. However, the model obviously
overestimates the TEC in the midlatitude Southern India Ocean and Southern America regions at 0800 and
1400 UT, respectively. In Figure 4 (bottom row), the modeled TEC is reduced in the two regions after the wind
bias correction scheme is implemented. In Figure 5, the global distribution of the root-mean-square (RMS)
of the differences between the IPE and F3/C TECs has been applied to quantify the change of the IPE
simulation with and without the wind bias correction scheme. The RMS values are computed from the 24 h TEC
differences over each grid point at the March equinox. Figure 5a shows that the difference between the IPE and
F3/C TECs are pronounced in low latitudes and at the southwest side of South America. In Figure 5b, the RMS
values are reduced obviously at the southwest side of South America if the wind bias correction scheme was
applied. In Figure 5c, the difference between the two RMS maps (Figures 5a and 5b) reveals that the wind bias
correction scheme significantly improves the IPE TEC at the southwest of South America and southeast of Africa.
The two Southern Hemisphere midlatitude areas, indicated as regions A (40°–80°E, 20°–60°S) and B (70°–110°W,
35°–75°S) in Figure 5c, where the presence of the model bias is particularly evident, are examined in detail.
Figure 6 shows a comparison of the 3-D electron density from IPE and F3/C over the two midlatitude regions. The
wind bias correction scheme reduces the model electron density bias up to about 50% (1–7.15 × 1010/1.45 × 1011)
and 67% (1–7.39 × 1010/2.26 × 1011) at regions A and B, respectively, improving the agreement of both the
modeled 3-D density and hmF2 distributions with the F3/C observations.
Figure 7 presents a comparison of the F3/C and IPE TECs with an independent TEC data set recorded at
six ground-based GPS stations. Diurnal variations in the TEC observed by the ground-based GPS receivers
and F3/C are similar over the six GPS stations, and the amplitude of the former is generally higher than or equal
to the latter. The difference may result from the electron density distribution from the plasmasphere. While
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the ground-based GPS TEC is the
integration of electron density from
the ground to the GPS satellite
altitude (~20,200 km), the F3/C TEC is
the integration of electron density
from the ground to the LEO satellite
altitude (~800 km).
The modeled and observed TECs
exhibit similar diurnal variations over
the GPS stations except for palm. The
IPE TEC is lower than the ground-based
GPS TEC and even lower than the F3/C
TEC at acu5 from 1100 to 2000 UT, at
pets from 1800 to 0100 UT, at marn
from 0300 to 0600 UT, and at hob2 from
2000 to 0700 UT. The increases in the
differences between modeled and
observed TECs show that the wind bias
correction scheme worsens the TEC
values at the four stations during the
particular periods. By contrast, the IPE
TEC is higher than the F3/C TEC and
even higher than the ground-based
GPS TEC at artu from 0800 to 1600 UT,
at palm from 0000 to 1700 UT, and at
marn from 0900 to 1300 UT. The
reductions in the differences between
modeled and observed TECs reveal that
the wind bias correction scheme
Figure 5. (a, b) Global distributions of the RMS of the differences between improves the modeled TEC at the three
the IPE and F3/C TECs. The RMS values were computed from the 24 h TEC
stations during the particular periods.
differences at each grid point. In Figure 5a, the model bias is significant at
Table 1 shows the RMS of the
low-latitudes and the southwest side of South America. In Figures 5b and
differences between the observed and
5c, the bias is reduced especially at the southwest of South America and
modeled TECs at the six ground-based
southeast of Africa if the wind bias correction scheme was applied. (c)
GPS stations on the March equinox in
The F3/C and IPE electron density profiles are collected within regions A
(40°–80°E, 20°–60°S) and B (70°–110°W, 35°–75°S) to show the improvement 2012. The decrease in the RMS at palm
of the model’s vertical density structures in Figure 6. The ground-based GPS and artu suggests that a general
TEC recorded by six midlatitude stations: acu5, artu, pets, marn, and hob2,
agreement between modeled and
and palm (Table 1) are validated with the IPE TEC in Figure 7. The longitudinal
observed TECs was improved, and the
and temporal variations in TEC within the southern geomagnetic latitude
improvement is particularly significant
area from 40° to 60°S (white lines) is analyzed in detail to elucidate the
evolution of the Southern Hemisphere Midlatitude Summer Nighttime
at palm. The slightly increased RMS
Anomaly (MSNA)/Weddell Sea Anomaly (WSA).
values at acu5, pets, marn, and hob2
indicate that the wind bias correction
scheme could deteriorate the agreement between modeled and observed TECs. The agreement of modeled
TEC with F3/C TEC is improved at marn.
5.2. Event Study: 2012 Southern MSNA/WSA
In Figures 8–10, the longitudinal and temporal (both universal and local times) variations in TEC, hmF2, and
field-aligned wind within the southern geomagnetic latitude area from 40° to 60°S are analyzed in detail to
elucidate the evolution of southern MSNA/WSA features. See Figure 5 for the geomagnetic latitude area
from 40° to 60°S, which includes the Weddell Sea region. Figure 8 illustrates the longitudinal and universal
time variations in the F3/C-observed (black line contours) and the IPE-simulated TECs (color contours),
before and after correcting the wind bias, at the March equinox (Figures 8a, 8c, 8e, and 8g) and the
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Figure 6. The IPE electron density and hmF2 are greatly reduced in regions (left) A and (right) B by using the wind bias
correction scheme. Blue and red lines are the IPE hmF2 before and after correcting the wind bias, respectively. The black
+
line with error bars (standard deviation) is the F3/C hmF2 averaged within DOY 80 ± 15 days in 2012 for Kp ≦ 3 .
December solstice (Figures 8b, 8d, 8f, and 8h) in 2012. Note that the F3/C data for the December solstice is
averaged within DOY 356 ± 15 days for Kp ≦ 3+. The TEC is averaged over 40° to 60°S geomagnetic latitudes
for each geographical longitude in a given hour. At the March equinox, both the F3/C and IPE TECs show the
clear diurnal variation (Figure 8a). The reduction in the RMS values of the differences between the IPE and
F3/C TECs (Figures 8e and 8g) reveals that the modeled TEC is adjusted and closer to the observed TEC after
correcting the wind bias. The diurnal variation in TEC is less evident at the December solstice (Figures 8b
and 8d), since the southern MSNA/WSA feature is known to be most intense near the December solstice
[e.g., Jee et al., 2009; He et al., 2009]. At the December solstice, the RMS value of the differences between the IPE
and F3/C TECs is increased if the wind bias correction scheme was applied (Figures 8f and 8h). By contrast,
the RMS values of the differences between the IPE and F3/C hmF2 show that the IPE hmF2 approaches the F3/C
hmF2 at both the March equinox and the December solstice if the wind bias correction scheme was applied
(Figure 9). The discrepancy between the results of TEC and hmF2 at the December solstice suggests that, except
for the neutral wind, some other factors, such as neutral composition, electric fields, and production and loss
rates, may also account for some differences between the modeled and observed TECs.
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Figure 7. Comparisons of the diurnal variations in TEC observed by F3/C and ground-based GPS receivers with those of the IPE-simulated TEC before and after
+
correcting the wind bias at six midlatitude locations. The ground-based GPS TEC is averaged within DOY 80 ± 15 days in 2012 for Kp ≦ 3 , and the error bars
denote the standard deviation during the month. The F3/C data are averaged during the same period and within ±10° of the longitude and latitude of the
ground-based GPS stations. Black and red indicate the IPE simulation with and without the wind bias correction. The modeled TEC improvement is most
significant at palm.
The southern MSNA/WSA features in both TEC and field-aligned winds at the December solstice are
further examined in Figures 10–12. Figures 10a and 10c illustrate for the December solstice the
longitudinal and local time evolutions of the southern MSNA/WSA features in TEC, and Figures 10b and
10d compare them with the corresponding field-aligned winds at 300 km altitude. Figures 10a and 10b
and Figures 10c and 10d are the simulation results before and after correcting the wind bias, respectively.
As shown in Figures 10a and 10c, both the F3/C and IPE TECs exhibit a clear diurnal variation and
eastward movement of the southern MSNA/WSA in the local time coordinate. To examine the behavior of
the southern MSNA/WSA feature in the longitude and local time coordinates in more detail, the locations
(longitudes) of maximum values of TEC or wind for a given local time are highlighted by blue triangles
for F3/C TEC, by white dots for IPE TEC, and by gray diamonds for wind. The locations of the wind and
TEC maxima in Figure 10 shows a clear eastward movement over the local time starting from around
1900 LT and even from 1600 LT. A time delay seems to exist between the wind and TEC features of the
southern MSNA/WSA movement.
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Figure 8. Time evolution of the longitudinal variation in the TEC of F3/C and IPE (a, b) before and (c, d) after correcting the wind bias. The TEC values are
adopted from 40°–60°S geomagnetic latitude (see Figure 5) at the March equinox (Figures 8a, 8c, 8e, and 8g) and the December solstice (Figures 8b, 8d, 8f,
and 8h). The overlaid black contours are the F3/C TEC observations. (e–h) The RMS values of the differences between the IPE and F3/C TECs suggest that
the wind bias correction scheme significantly improves the modeled TEC at the March equinox. The IPE model with the wind bias correction scheme underestimates the
modeled TEC at the December solstice.
Figure 9. Time evolution of the longitudinal variation in the hmF2 of F3/C and IPE (a, b) before and (c, d) after correcting the wind bias. The hmF2 values are adopted
from 40°–60°S geomagnetic latitude at the March equinox (Figures 9a, 9c, 9e, and 9g) and the December solstice (Figures 9b, 9d, 9f, and 9h). The overlaid black
contours are the F3/C hmF2 observations. (e–h) The RMS values of the differences between the IPE and F3/C hmF2 show that the wind bias correction scheme
significantly improves the modeled hmF2 at both the March equinox and the December solstice.
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Figure 10. Eastward movement of southern MSNA/WSA features in the local time coordinate. Comparisons of the F3/C
TEC with the IPE TEC (a) before and (c) after correcting the wind bias. Comparisons between the locations of the
maxima of TEC and that of the field-aligned wind (b) before and (d) after correcting the wind bias. The blue triangles,
white dots, and gray diamonds denote the locations of the maxima of the F3/C TEC, IPE TEC, and field-aligned winds,
respectively. The agreement between distributions of the maxima of TEC and field-aligned winds suggests that the
field-aligned neutral wind is one of the major factors controlling the eastward movement of the southern MSNA/WSA
feature in TEC.
The locations of the maxima of the F3/C TEC are nearly linear between 1900 and 1600 LT (130°W to 100°E).
The speed of the eastward movement of the southern MSNA/WSA feature is about 11.5°/h or about
351 m/s. However, the locations of the maxima of the IPE TEC without the wind bias correction are
separated into three clusters: 1900–0100 LT, 0200–1100 LT, and 1200–1800 LT, which roughly correspond
to the maxima locations of the HWM93 field-aligned wind (Figure 10b). After correcting the wind bias
(bottom panels), such discontinuity is nearly eliminated from both modeled TEC and field-aligned wind.
The speed of the eastward movement of the southern MSNA/WSA feature simulated by IPE (white dots)
with the wind bias correction scheme is about 9.3°/h or about 285 m/s within 130°W to 100°E. Moreover,
the speed of the southern MSNA/WSA eastward movement feature in the F3/C TEC (blue triangles) is
about 43°/h or about 1324 m/s between 1600 and 1900 LT (100°E to 130°W, wrapping around the Earth),
which is much faster than the speed between 1900 and 1600 LT (130°W to 100°E).
Figure 11a shows the correlation between the longitudinal locations of the local time maxima of the IPE
(before and after the wind bias correction) and F3/C TECs. The high correlation (correlation coefficient = 0.95)
between the pure model simulation and the observation suggests that the model captures the movement of
southern MSNA/WSA, and the model’s capability is improved even more by the use of the wind bias correction
scheme as indicated by the higher correlation (correlation coefficient = 0.97) between the observation and the
model simulation with the wind bias correction. The reduction in the RMSE (root-mean-square error) of the
locations of the IPE TEC maxima reveals that the wind bias correction scheme helps the IPE model to better
track the eastward movement of the southern MSNA/WSA.
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Figure 11. (a) Correlations between the locations (longitudes) of the TEC maxima of F3/C and IPE before (blue circles and
dotted blue line) and after (red dots and solid red line) correcting the wind bias (obtained from Figures 10a and 10c). The
high correlation suggests that the IPE model nicely reproduces the eastward movement of the southern MSNA/WSA feature
observed by F3/C. The reduction in the RMSE of the locations of the IPE TEC maxima reveals that the wind bias correction
scheme helps the IPE model to better track the eastward movement of the southern MSNA/WSA. (b) The time-lag correlation
between the locations (longitudes) of the maxima of TEC and adjusted field-aligned wind (obtained from Figure 10d) indicate
that the southern MSNA/WSA eastward movement feature in TEC takes about 3 h to respond to that of the neutral wind.
As shown in Figure 10, the time of the TEC maxima is generally delayed by a few hours from the wind maxima
for a given longitude. To quantify this time delay, the time-lag correlation coefficients between the maxima
of the wind and that of TEC, shown in Figure 11b, are computed by shifting the time of the wind maxima
for a given longitude along the local time axis toward the time of the TEC maxima displayed in Figure 10d.
Figure 11b indicates that the southern MSNA/WSA eastward movement in TEC takes about 3 h to respond
to that in field-aligned winds. The origin of the eastward movement of the southern MSNA/WSA feature
in the field-aligned wind is further examined next.
Horizontal neutral winds and their projection in the magnetic field direction are analyzed to examine a
possible cause of the eastward movement of southern MSNA/WSA features. As we focus on the MSNA/WSA
within a certain geomagnetic latitudinal belt (40°–60°S), the dip angle of the geomagnetic field line is
constant over all the longitudes. Therefore, the longitudinal variation (or the apparent eastward movement)
of the field-aligned wind is likely to be associated with the longitudinal variation in the declination angle
(Figures 12g and 12h). Figure 12 shows the geographically zonal UZ and meridional UM components of
HWM93 winds at the December solstice as well as the projection of UZ and UM in magnetic meridional
direction at 300 km altitude. The winds and declination angle shown in Figure 12 are averaged values over
40°–60°S geomagnetic latitudes for a given geographic longitude and local time. Positive and negative
declination angles denote the northeast and northwest tilts of geomagnetic field lines, respectively. Both UZ
and UM exhibit a clear diurnal variation, although no strong longitudinal variations can be seen in comparison
to the field-aligned wind in the longitude and local time coordinates (Figures 10a and 10c).
The declination angle (dec) close to 0° is preferable for the northward wind to uplift the ionospheric layer
along magnetic fields in the Southern Hemisphere. The positive and negative declination angles are
preferable for the eastward and westward winds, respectively. By multiplying the values of UM and UZ with
the cosine and sine of declination angles, the components parallel to the magnetic field can be derived
and are shown in Figures 12b and 12d. Magnitudes of UM cos(dec) are equal (if dec = 0°) and slightly lower
than that of UM. Figures 12b and 12d also show that there are several peaks of the projected wind at a
given time over all longitudes. Two peaks of UM cos(dec) are located near 1900 LT and 130°W (peak A) and
near 0400 LT and 35°W (peak B). UZ sin(dec) shows a more distinct longitudinal variation. Two peak values of
the UZ sin(dec) are located near 1800 LT and 125°W (peak C) and near 0800 LT and 50°E (peak D). These peaks
correspond to peaks in UZ and UM except for peak D.
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Figure 12. Effects of the declination angle (dec) on the component of zonal and meridional neutral winds projected in
the geomagnetic meridional direction at 300 km altitude within 40°–60°S magnetic latitude. UZ and UM are the zonal
(eastward positive) and meridional (equatorward positive) components of the horizontal winds obtained from the
22
2
1
HWM93 model for F10.7 = 110 (10
W m Hz ) at the December solstice. The locations of these peaks (blue crosses)
correspond to the presence of the three clusters of the field-aligned wind maxima locations shown in Figure 10b.
Peaks A and C are almost colocated in both local time and longitude. Peaks A and C occurred at the earliest
local time on the western side; peak D occurred at the latest local time on the eastern side; and peak B is
located between them. The locations of the three peaks directly correspond to the presence of the three
clusters of the HWM93 field-aligned wind maxima locations (Figure 10b). The similar clusters can also be
found in the IPE TEC (Figure 10a). It is evident that the eastward movement of the southern MSNA/WSA
feature in TEC is mainly controlled by the components of the zonal and meridional winds projected in the
magnetic meridional direction, which originally result from the longitudinal variation of the
declination angle.
6. Discussion
In comparison with the meridional neutral winds UM, the zonal neutral winds UZ are not efficient at lifting
the ionosphere layer up along field lines at midlatitude. Therefore, the zonal winds should play a lesser role in
the formation of MSNA/WSA features. However, our study suggests an exception. Burns et al. [2008] pointed
out that neutral winds are mainly zonal at dusk in geomagnetically quiet periods [e.g., Dickinson et al., 1981;
Burns et al., 1995] but that zonal neutral winds are unlikely to contribute to driving electrons up field lines.
Figures 12e and 12f show that at dusk (near 1800 LT), UZ is stronger than UM, but UZ sin(dec) is much weaker
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than UM cos(dec). This is consistent with the report of Burns et al. [2008]. It means that the field-aligned wind
is mainly constituted by the meridional winds near dusk. In the morning the neutral wind is mainly zonal
because the meridional wind switches its direction from north to south near 1000 LT. When UM cos(dec)
is nearly zero, the zonal wind can contribute considerably to the total field-aligned wind. UZ sin(dec) is
prominent at about 50°E near 0800 LT (peak D) and corresponds to the existence of the MSNA/WSA feature
in the Southern Hemisphere shown in Figure 10a. It suggests that UZ sin(dec) can dominate the formation
of the southern MSNA/WSA TEC feature (i.e., near 1000 LT, at about 50°E) if UM cos(dec) is much weaker.
At first glance at Figures 8 and 10, it seems that the wind bias correction scheme changes the absolute
magnitude of the modeled TEC and field-aligned wind but affects their space-time distribution pattern
very little. By carefully tracking the location of the TEC and wind maxima, the change of the pattern can,
however, be detected. After correcting the wind bias, the locations of the IPE TEC and the HWM93 field-aligned
wind maxima are more linear and are in better agreement with the F3/C TEC maxima (Figure 11a). We
concluded that the eastward movement of the southern MSNA/WSA TEC feature is primarily controlled by the
neutral winds and the way in which the longitudinal variation of declination angles contributes to the
projection of neutral winds in the magnetic meridional direction.
Most of previous studies mainly applied the thermospheric field-aligned neutral wind to explain the
formation of WSA over the Weddell Sea region [e.g., Horvath and Essex, 2003; Horvath, 2006; Lin et al.,
2009; Jee et al., 2009; Liu et al., 2010a; Chen et al., 2011]. The recent studies described the formation of the
MSNA/WSA and its eastward movement feature by means of tidal wave analysis [e.g., Chen et al., 2013;
Xiong and Lühr, 2014; Chang et al., 2015]. The high correlation between the southern MSNA/WSA eastward
movement feature in the TECs and the locations of the field-aligned neutral wind maxima (Figure 11b), which
is originally controlled by the declination angle, reveals that the major tidal components decomposed
from the electron density observations [Xiong and Lühr, 2014; Chang et al., 2015] should be heavily influenced
by the neutral wind direction and the longitudinal variation in the declination angle (Figure 12). Chen et al.
[2013] applied SAMI3 with the thermospheric neutral winds including tidal effects provided by TIEGCM
and GSWM to successfully reproduce the eastward drift feature of the southern MSNA/WSA, which is not
reproduced by the default SAMI3 runs using the neutral winds provided by the empirical HWM93 model.
By contrast, IPE with HWM93 successfully reproduced the F3/C-observed eastward movement of the
southern MSNA/WSA. This may be due to the fact that the SAMI3 model uses the tilted dipole coordinate,
whereas the IPE model uses the apex coordinate with realistic geomagnetic fields.
This study for the first time shows the significant longitudinal variation in the speed of the eastward
movement of the southern MSNA/WSA from both observation and simulation. The F3/C observation and the
IPE simulation show that the southern MSNA/WSA moves eastward with a speed of about 300 m/s from 130°W
to 100°E at the December solstice. The speed mainly agrees with that reported by Liu et al. [2013]. In
addition, our results further indicate the speed of the eastward movement feature exceeding 1300 m/s
between 100°E and 130°W. It seems that the field-aligned wind dominates the eastward movement of the
southern MSNA/WSA from 130°W to 100°E, and some other factors may also play a role in the eastward
movement feature from 100°E to 130°W and need to be further investigated.
The wind bias correction scheme can improve the IPE TEC, but it can also actually make the simulated density
worse at some regions and some times. In addition to the neutral wind, effects of some other processes
should also be considered. For example, Miller et al. [1989] and Richards [1991] reported that the zonal electric
field could induce the error in the winds derived from hmF2. Horvath [2006] also suggested that at higher
middle and high geomagnetic latitudes the electric field, or E × B drifts, can play a greater role in the
formation of MSNA/WSA than the field-aligned wind. Observed F3/C hmF2 variations may be caused by
electric fields and tidal waves [e.g., Pancheva and Mukhtarov, 2010; Liu et al., 2011]. It is, however, difficult to
clearly distinguish how much of the variation in the observed hmF2 is caused by neutral winds and how much
by electric fields or other factors.
It has been known that during geomagnetically active periods, some factors like the electric fields [e.g., Blanc
and Richmond, 1980; Spiro et al., 1988] and neutral composition [e.g., Fuller-Rowell et al., 1994] play important
roles in altering the ionospheric plasma at low latitude to midlatitude. The purpose of this study at the current
stage is to develop the wind bias correction scheme for geomagnetically quiet conditions. But there is
actually a possibility to improve the scheme so that it could also work for geomagnetically active periods.
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Richards et al. [1998, 2010] introduced the FLIP model neutral density modification algorithm to bring the
measured and modeled NmF2 into better agreement by adjusting the MSIS neutral densities and temperature
during the geomagnetic storms. The application of this technique may be suitable for the IPE model to yield
better densities in the geomagnetically active periods in the future.
Numerous studies have shown that the component of the wind projected in the magnetic meridional
direction derived from the algorithm of FLIP agrees well with the wind observed by the Fabry-Pérot
interferometer and incoherent scatter radar over certain locations [e.g., Dyson et al., 1997; Richards, 2002;
Richards et al., 2009, 2010, and references therein]. However, it is difficult to validate comprehensively the
global wind obtained in this paper because of the lack of global F region neutral wind observations. At the
current stage, we show that the winds estimated in the bias correction scheme are likely to be closer to
reality, because the scheme improves the agreement of the model electron density with the observation at
the March equinox, and the model hmF2 with the observations at both the March equinox and the December
solstice. The larger discrepancy between the modeled and observed electron densities in the Southern
Hemisphere indicates that wind observations are less available in the Southern Hemisphere when
developing the HWM empirical model. The advantage of this bias correction scheme is that it will reduce
such discrepancy by using the global F3/C hmF2 observations. This paper demonstrates the validity and
usefulness of the wind bias correction scheme using the best available data set (monthly F3/C observation),
and it can be expected that more data provided by the future missions like FORMOSAT-7/COSMIC-2 (F7/C2)
(up to 12,000 RO profiles per day) will be available to perform this analysis on shorter time periods.
7. Conclusions
A field-aligned neutral wind bias correction scheme has been developed to improve the performance of a
global ionosphere and plasmasphere model at midlatitudes under geomagnetically quiet conditions by
using the F3/C hmF2 observations. The thermospheric neutral wind is one of the major factors controlling the
ionospheric electron density distribution at midlatitudes. The scheme has been successfully implemented for
IPE built upon the flux-tube FLIP model and shown to improve the model’s capability to reproduce the
observed hmF2 and electron density features at midlatitudes.
Acknowledgments
This study is supported by the NASA
awards NNX09AJ83G and NNX11AD70G
to University of Colorado at Boulder, and
the Taiwan National Science Council
(NSC) grant NSC 102-2628-M-008-001.
Yang-Yi Sun sincerely thanks Karen Fay
O’Loughlin, Phil Richards, Tzu-Wei Fang,
and Tim Fuller-Rowell for useful discussions and valuable assistance with the
paper. The authors gratefully acknowledge the International GNSS Service (IGS)
for providing GPS data. The GPS data for
this paper are available at the Scripps
Orbit and Permanent Array Center
(SOPAC). Data set: acu5ddd0.yyd,
artuddd0.yyd, petsddd0.yyd, palmddd0.
yyd, marnddd0.yyd, and hob2ddd0.yyd.
The authors thank COSMIC Data Analysis
and Archival Center (CDAAC) and Taiwan
Analysis Center for COSMIC (TACC) for
making the F3/C data available online.
Data set: post-processing ionPrf. The
authors would like to thank the reviewers
for their comments that help improve
this paper.
Alan Rodger thanks the reviewers for
their assistance in evaluating this paper.
SUN ET AL.
Global TEC structures simulated by IPE with empirical model drivers generally agree with that of the F3/C TEC
observations at the March equinox in 2012. However, the model overestimates the TEC in the midlatitudes of
the Southern Hemisphere. A close comparison between the IPE and F3/C vertical electron density distribution in
the two midlatitude Southern Hemisphere regions supports our results that the modeled TEC and electron
density profiles are greatly improved with the help of the wind bias correction scheme. The wind bias correction
scheme reduces the model electron density bias up to about 50% and 67% at the two regions of the
southwest of South America and southeast of Africa areas, respectively. Validation using the independent
data set, ground-based GPS TEC, also confirms this improvement.
IPE with empirical model drivers can simulate the general feature of the MSNA/WSA eastward movement in
the Southern Hemisphere at the December solstice, and the wind bias correction scheme helps the IPE model
to better reproduce the evolution of the southern MSNA/WSA. The southern MSNA/WSA feature in TEC
with a speed of about 300 m/s moves eastward from 130°W to 100°E and with an extreme speed (more than
1300 m/s) from 100°E to 130°W. The model simulations prove that the eastward movement of the southern
MSNA/WSA feature in TEC is primarily controlled by the eastward movement of the field-aligned wind
maxima, with a 3 h delay, which results from the longitudinal variation in the declination angle of the
geomagnetic field line.
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