ANGEOAnnales GeophysicaeANGEOAnn. Geophys.1432-0576Copernicus PublicationsGöttingen, Germany10.5194/angeo-34-751-2016An evaluation of International Reference Ionosphere electron density in the polar cap and cusp using EISCAT Svalbard radar measurementsBjolandLindis Meretelindis.m.bjoland@uit.noBelyeyVasylLøvhaugUnni PiaLa HozCesarDepartment of Physics and Technology, University of Tromsø – The
Arctic University of Norway, Tromsø, NorwayLindis Merete Bjoland (lindis.m.bjoland@uit.no)13September201634975175822June201622August201630August2016This 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/34/751/2016/angeo-34-751-2016.htmlThe full text article is available as a PDF file from https://angeo.copernicus.org/articles/34/751/2016/angeo-34-751-2016.pdf
Incoherent scatter radar measurements are an important source for studies of
ionospheric plasma parameters. In this paper the EISCAT Svalbard radar (ESR)
long-term database is used to evaluate the International Reference Ionosphere
(IRI) model. The ESR started operations in 1996, and the accumulated database
up to 2012 thus covers 16 years, giving an overview of the ionosphere in the
polar cap and cusp during more than one solar cycle. Data from ESR can be
used to obtain information about primary plasma parameters: electron density,
electron and ion temperature, and line-of-sight plasma velocity from an
altitude of about 50 and up to 1600 km. Monthly averages of electron
density and temperature and ion temperature and composition are also provided
by the IRI model from an altitude of 50 to 2000 km. We have compared electron
density data obtained from the ESR with the predicted electron density from
the IRI-2016 model. Our results show that the IRI model in general fits the
ESR data well around the F2 peak height. However, the model seems to
underestimate the electron density at lower altitudes, particularly during
winter months. During solar minimum the model is also less accurate at higher
altitudes. The purpose of this study is to validate the IRI model at polar
latitudes.
Ionosphere (polar ionosphere)Introduction
Electron density in the polar cap F-region ionosphere is produced by solar
extreme ultraviolet radiation, transport of plasma density structures from lower latitudes
and particle precipitation and is reduced by recombination and transport to
lower latitudes. The solar wind has a significant influence on the dynamics
of the high-latitude ionosphere as it controls the electrodynamics and
therefore transport by E×B
plasma drift and by particle precipitation. Thus the high-latitude ionosphere
is a highly variable region where structures form, recombine and are
transported in and out in response to transient changes in the solar wind
and/or the interplanetary magnetic field.
Plasma density structures in the high-latitude F region are
transported anti-sunward across the polar cap and sunward in the auroral zone
due to electric convection e.g.,. This transport can
increase the electron density in the nightside significantly when structures
produced by solar extreme ultraviolet radiation in the sunlit ionosphere follow the convection lines
into the polar cap. As an example, plasma originating at midlatitudes can be
transported to high latitudes and into the polar cap in a form of a tongue of
ionization which greatly enhances the plasma density in the polar
cap, cusp and auroral zone e.g.,. Tongues of
ionization can also be
segmented into 100–1000 km sized islands of enhanced electron density, called
polar cap patches e.g.,. The patches are
transported over the polar cap following the convection pattern.
In addition to transport of solar-produced plasma from lower latitudes, soft
particle precipitation is an important source of F-region plasma
density irregularities at high latitudes e.g.,. Soft
particle precipitation in the cusp region where particles precipitate
directly from the magnetosheath can produce polar cap patches that can be
convected over the polar cap e.g.,. As a result of plasma transport and particle precipitation, the
high-latitude F region ionosphere is nonuniform and highly dynamic.
This is a challenge for models aiming to accurately represent the high-latitude ionosphere.
The International Reference Ionosphere (IRI) model is widely used for
ionospheric and magnetospheric research, also at high latitudes. IRI is an
empirical model which provides monthly averages of ionospheric parameters
from an altitude of 50 to 2000 km . Among the
data sources used to build the IRI model are incoherent scatter radars
(ISRs), the ISIS and Alouette topside sounders, rocket and satellite
observations, as well as the worldwide network of ionosondes. As ionosondes
are an essential data source for the IRI model, the IRI model is known to be
less accurate at high and low latitudes, where the ionosonde coverage is lower
compared to midlatitudes e.g.,.
In the present study we use ISR data from the EISCAT Svalbard radar (ESR),
covering the polar cap and cusp, to evaluate the IRI model-predicted electron
density in the F region. As the radar started its operations in the
1990s, the accumulated database now contains data from more than one solar
cycle. Long time series of ionospheric data are essential when the aim is to
study the performance of the IRI model during different diurnal, seasonal and
solar activity conditions. Using the ESR data allows us to evaluate the IRI
model in the region where the model is known to be less accurate under
various conditions.
Previous studies have also used observational data to evaluate the IRI model
e.g.,, but few of these have evaluated the model at latitudes as high as
the auroral zone or the polar cap, or with long enough time series to
evaluate the model at different parts of the solar cycle.
and used data from ISRs in their studies.
used Arecibo ISR data from experiments performed between 1985 and 2009,
covering three different solar cycles, to evaluate the IRI-predicted F2 layer
critical frequency (foF2) and height (hmF2) at midlatitudes. They found an
overestimation of foF2 at day and an underestimation at night. For hmF2 they
found an underestimation, especially during high solar activity. However,
after applying a correction for solar activity, they found that the IRI model
reproduced the seasonal variation well. compared ISR data
from Millstone Hill, at midlatitudes, and ESR, in the polar cap, with the
IRI-2001 model. They used the ISR data to evaluate the IRI electron density
and plasma temperature profiles. As expected due to the poor data coverage at
high latitudes, they found that the model performed best at midlatitudes.
used 1-month-long data from October 2002 from Millstone
Hill and the ESR and therefore did not study any solar cycle or seasonal
variations.
Several studies have compared ionosonde data with the IRI model. At
midlatitudes, compared 10 years of NmF2 and hmF2 data from a
digisonde located at the Korean Peninsula with the IRI-2007 model. They
looked at different diurnal, seasonal, solar activity and geomagnetic
conditions and found that although there was good agreement between the
observed and IRI-predicted NmF2, there were significant differences between
the model and observed hmF2 during midnight, especially during high solar
activity. At auroral latitudes, compared hmF2 observed at
three different ionosonde stations with the hmF2 values predicted by IRI-2001
for three separate years at different parts of the solar cycle. They found
the best agreement when the solar activity was high.
In a study by data from four ionosonde stations located
within the polar cap were used to evaluate the hmF2, peak density (NmF2),
M(3000)F2 and the bottomside thickness parameter B0 predicted by the IRI-2007
model during the latest extended solar minimum from 2008 to 2010. In
addition, data from the Resolute Advanced Modular ISR were used to evaluate
the IRI-predicted topside thickness. They evaluated the IRI peak height and
density, and topside and bottomside thickness and found differences which
they attributed to errors in the modeling of the IRI M(3000)F2 factor and
poor representation of diurnal and seasonal variability.
Although , and have
compared the IRI model with high-latitude data, such comparisons have mainly
been made at midlatitudes. It is therefore highly relevant to evaluate the
IRI model for the high-latitude region, and in this study we compare the IRI
model with the ESR data from the polar cap and cusp.
Data and methodology
The EISCAT Svalbard radar, located at 78.15∘ N, 16.02∘ E
(geographic coordinates) and 75.43∘ N, 110.68∘ E
(geomagnetic coordinates), is one of three incoherent scatter radar systems
operated by the EISCAT Scientific Association. In addition to the ESR, an
ultra-high-frequency system
and a very-high-frequency system are located near Tromsø, Norway, with additional receiver
systems in Kiruna, Sweden, and Sodankylä, Finland. The radars are usually
operated in a campaign mode, and the data are therefore not continuous.
Typically, ESR operates around 1000–2000 h a year, but as part of an
IPY-ICESTAR project the ESR was operated nearly continuously from March 2007
to February 2008. Data from ESR can be used to obtain information about
primary plasma parameters: electron density, electron and ion temperature,
and line-of-sight plasma velocity (many other parameters can be derived from
them) from an altitude of about 50 and up to 1600 km. The complete
data set therefore provides a comprehensive overview of the ionosphere in the
polar cap and cusp during a range of different diurnal, seasonal, geomagnetic
and solar activity conditions.
To get access to the complete ESR data set, we have used the Madrigal
database, which is an archive of data from a range of different upper
atmosphere instruments. Nearly all the experiments since the EISCAT radars
were put into operation are available through Madrigal. All ESR data used in
this study have been retrieved from the EISCAT Madrigal database.
The Madrigal data have been collected from different experiment modes with
different time and altitude resolution and altitude span. As the ESR
measurements are not continuous and have different time and altitude
resolution, the data have been integrated in 3 h daily intervals for
3-month seasonal periods in each 20 km altitude bin as shown in Fig. . The seasonal binning is based on the equinoxes and solstices.
This means that spring includes February, March and April, summer includes
May, June and July, autumn includes August, September and October and winter
is November, December and January (consecutive months). Erroneous data that
sometimes appear in Madrigal were filtered out of the integration. The
filtering excluded records with electron densities lower than 108 m-3 and records with electron densities higher than 1012 m-3.
An exception was made for the upper electron density limit during solar
maximum years 1999, 2000, 2001 and 2002. Due to the higher solar activity the
filtering during these years only excluded records with electron densities
higher than 1013 m-3.
Altitude profiles of electron density (log10
Ne, m-3) measured by ESR and integrated over 3 h in a day
for 3 months (spring, summer, autumn, winter). Panels correspond to the 3 h
integration intervals.
The ESR results were compared with the IRI-2016 model. ESR has two parabolic
antennas: a 42 m diameter antenna fixed in the field-aligned direction and a
fully steerable antenna with a diameter of 32 m. In order to make the
comparison between the IRI model with the ESR data as accurate as possible ,
ESR data were only used if the elevation angle was larger than 75∘.
The IRI model is updated as new data become available, and in this study the
latest IRI-2016 model is used. Standard options were used for the IRI model.
An IRI profile was generated for each unique time where an ESR profile were
used. The IRI profile covered altitudes between 200 and 500 km with a step
size of 20 km. Each IRI profile therefore had one value in each 20 km
altitude bin. Since seasonal averages were used for the ESR data, and not
monthly averages as produced by IRI, the IRI-produced electron densities were
also binned and averaged according to season and 3 h daily intervals.
To further investigate the observed difference in the electron densities from
ESR measurements and IRI-produced electron densities, the total electron
content (TEC) and hmF2 parameters were also estimated. The TEC calculation
was done by integrating the electron density over each altitude bin. ESR TEC
was only calculated for seasons and daily time intervals when there were data
in each altitude bin to ensure that ESR TEC and IRI TEC could be compared.
ESR hmF2 was estimated for each profile in a way similar to
. Cubic spline interpolation was used to set a fixed
distance of 10 km between each point in the profile. The maximum electron
density was then found in each interpolated profile, and a second-degree
polynomial was fitted to five points in the peak area centered around the
maximum. The maximum of the fitted polynomial was then used as an estimate of
the hmF2. To ensure a sufficient number of interpolation points around the
maximum, we searched for hmF2 in the altitude range 180 to 500 km.
Profiles from which it was difficult to extract any clear maximum were
excluded. This filtering excluded ESR profiles in which the maximum was found in
the lowest or highest range gate and profiles in which the electron density
doubled between two adjacent points (possible outliers). All the estimated
hmF2s were then categorized by season and 3 h time intervals, and the
average hmF2 in each bin was found.
Results and discussionComparison of the ratio ESR / IRI
Figure shows a histogram of how all the ESR data
compare with the IRI model. This is the distribution of the entire database
without binning, but after the electron densities outside the range 108 to 1012 m-3 have been excluded. If the IRI model had been
a perfect fit to the ESR data, all the data would have been located in the
bar where the ratio is 1, as indicated by the red line. From Fig. , it is apparent that the model both overestimates and
underestimates the electron density as measured by the radar; however, the
model is significantly biased towards an underestimation.
Histogram showing the distribution of all the data without binning.
The x axis shows the ratio between ESR data and the IRI model, the y axis
the number of data points.
Figure shows the ratio between the ESR-measured electron
density and electron density produced by IRI in each bin. As for Fig. , the eight top panels each represent a 3 h integration
interval. The bottom panel displays the sunspot number, which shows the solar
cycle variation. The four columns in each year represent the seasons in the
order of spring, summer, autumn and winter.
Altitude profiles of the ratio between ESR and IRI electron
densities. The eight top panels correspond to the different 3 h integration
intervals. The last panel shows the 3-month averaged sunspot number. The four
columns for each year represent the seasons in the order of spring, summer,
autumn and winter.
During solar maximum (1999–2002), the red color in Fig.
shows that the IRI model clearly underestimates the electron density for
altitudes below the F2 peak. The underestimation is visible in all seasons
and at any time of the day, but largest at nighttime and during winter. For
example, during winter in 2001 and 2002, the ratio of ESR to IRI electron
density is 2.5 or above for all altitudes between 200 and 500 km in the time
interval 18:00–21:00 UT. During summer, in the same time interval, the agreement is
much better between the IRI model and the ESR data. There is still some
underestimation, but this is mainly concentrated to below 260 km altitude,
and the ratio of ESR to IRI electron density is 2 or less. Also at higher
altitudes, above the F2 peak, the IRI model underestimates the electron
density. However, the ratio is less for this high-altitude underestimation
and it usually covers a smaller altitude range than the underestimation below
the F2 peak.
As the solar activity declines towards solar minimum, the situation changes.
Compared to the solar maximum, there is better agreement between the IRI
model and the ESR data at the altitudes below and above the F2 peak area
during the years 2003–2004. However, the dark blue color in Fig. shows that for these years the IRI model overestimates
the electron density in the area around the peak density.
During the extended solar minimum (2006–2010) the situation becomes more
similar to the solar maximum years. The IRI model fits the ESR data best in
the area around the peak height but underestimates the electron density
below ∼ 260 km and above ∼ 440 km altitude. At altitudes above
∼ 440 the underestimation is slightly stronger during solar minimum than
during solar maximum. On the other hand, below the peak height the altitude
range where the model underestimates the electron density is smaller than
during solar maximum, particularly at nighttime.
High electron density gives a larger signal-to-noise ratio in the radar
measurements. We therefore expect more outliers when the electron density is
low. To ensure that the larger number of outliers does not affect the
results, the electron density distribution at different parts of the solar
cycle was examined. Based on this examination, the lower limit on electron
density was set to 108 m-3 and the upper limit to 1013 m-3 during solar maximum and 1012 m-3 during other parts of
the solar cycle. Also, at higher altitudes the electron density is lower,
increasing the risk of erroneous data entering the analysis due to the lower
signal-to-noise ratio. Therefore, it was decided to only use EISCAT data from
below 500 km where the signal-to-noise ratio is in general sufficient. An
exception is winter data during solar minimum, where data above 400 km can be
unreliable. These data have therefore been removed from Figs. –.
Altitude profiles of the ratio between ESR and IRI electron
densities for three different versions of the IRI model (IRI-2001, IRI-2012
and IRI-2016) in 2001. The data have been binned according to season, as
indicated, and as daily 3 h averages. The rows show how the IRI-2001,
IRI-2012 and IRI-2016 models reproduce the polar ionosphere during 2001
respectively.
Comparison with previous versions of the IRI model
A new topside model, the NeQuick model e.g.,, has
been used as the standard option by the IRI model since IRI-2007.
compared the NeQuick and the IRI topside model with
topside profiles from the ISIS-2 satellite and found that the NeQuick topside
model provides a better representation of the topside ionosphere than the IRI
topside model. IRI-2012 also introduced a new model for bottomside thickness,
ABT-2009 , which has since been used as the standard
option . As the IRI model offers several options to choose
from, including those used as standard options in the previous versions of
the IRI model, it is of interest to investigate whether another choice of options
would give a better agreement with the ESR electron density. Therefore, we
have chosen to also compare earlier versions of the IRI model with the ESR
electron density to check whether a different set of standard options would give a
better representation of the electron density in the high-latitude
ionosphere.
Figure shows the ratio ESR electron density over IRI, for the
IRI-2001, IRI-2012 and IRI-2016 during 2001 (solar maximum). Above ∼ 440 km the IRI-2001 model represents the polar cap ionosphere during spring
and summer slightly better than the IRI-2012 and IRI-2016 model. The median
ratio over the spring and summer plots for altitudes 440–500 km is ∼ 1.35
and ∼ 1.37 for the IRI-2012 and IRI-2016 models, respectively, but only
∼ 0.97 for the IRI-2001 model. A different situation is seen during
winter where IRI-2012 and IRI-2016 clearly perform better than the IRI-2001
model. In general, the performance of the IRI-2012 and IRI-2016 is similar,
but some differences can be observed. For example, both models underestimate
the electron density below 300 km, but the underestimation is stronger for
the new IRI-2016 model, particularly around the equinoxes where the median
ratios are ∼ 1.81 and ∼ 2.29 for the IRI-2012 and IRI-2016 model,
respectively.
Same as Fig. , but for 2008, in the extended solar
minimum, instead of 2001.
Total electron content from ESR (blue) and IRI model (red) given in
TEC units (TECU). Each panel corresponds to a 3 h integration bin, and each
year contains four seasonal bins (spring, summer, autumn and
winter).
The height of the F2 peak from ESR (blue) and IRI model (red). Each
panel corresponds to a 3 h integration bin, and each year contains four seasonal
bins (spring, summer, autumn and winter). Error bars correspond to 1
standard deviation.
Figure is similar to Fig. but compares the
performance during a year in the extended solar minimum (2008). Here, all
three versions of the IRI model show similar behavior. However, in contrast
to the situation during solar maximum, the IRI-2016 model is slightly better
at reproducing the ionosphere below 300 km during the extended solar minimum
than IRI-2012. Below 300 km the median ratio over all seasons is ∼ 1.39
for IRI-2012 and ∼ 1.31 for IRI-2016. Also the mean ratio over the plot
for bins below 300 km confirms that the underestimation is stronger for the
IRI-2012 model than for IRI-2016. The mean ratio is ∼ 3.12 for IRI-2012
and ∼ 1.87 for IRI-2016.
Comparison of the total electron content (TEC)
From the binned ESR data the TEC between 200 and 500 km was also calculated and a comparison between ESR TEC and IRI TEC is shown
in Fig. , where TEC is given in TEC units (1 TECU =1016 electrons m-2). Figure shows that the TEC is best reproduced
during the solar minimum and that the IRI model underestimates the TEC during
the solar maximum. The IRI model reproduces TEC well during the extended
solar minimum but underestimates the TEC during solar maximum. Although the
general tendency is that IRI-TEC underestimates the ESR-TEC, there are
also examples of IRI overestimating the electron density. For example in
spring 1999, one can observe an overestimation of TEC in Fig. ,
consistent with the overestimation of the electron density at altitudes
around the peak height and above, as seen in Fig. . The
underestimation observed during the solar maximum 2001–2002 is consistent
with the results found using Canadian GPS-TEC data
during the most recent solar maximum. They attributed this underestimation to
the topside thickness parameterization in the IRI model.
Comparison of the height of the maximum density in the F2 layer
Also the heights of the F2 layer peak (hmF2) as given from the IRI model were
compared with hmF2 calculated from the ESR data. Both the estimated ESR hmF2s
and the hmF2s from the IRI model were binned according to season and time of
day, and the median in each bin was found. For the IRI model, we obtained the
hmF2 from all the times an ESR profile was available. The results are seen
in Fig. , where the blue line represents the estimated ESR hmF2s
and the red line the IRI hmF2s. As shown, the general tendency seems to be
that the agreement is best during solar maximum, while the IRI model
overestimates the hmF2 during solar minimum. The IRI model seems to reproduce
the hmF2 measured by the ESR best in the time intervals 03:00–12:00 UT. Figure
shows that the IRI hmF2 has greater seasonal variation than
the ESR hmF2, especially at nighttime.
Conclusions
Electron density from the IRI-2016 model has been compared with data from the
EISCAT Svalbard radar covering more than one solar cycle. The results of this
comparison could be useful for users and developers of the IRI model, since
it is possible from our study to identify the time periods and altitude
ranges where the model might need improvement. Also, an inclusion of the
entire ESR data set might contribute to improving the performance of the IRI
model at high latitudes. The most important results are summarized as
follows:
The IRI model is found to be biased towards an underestimation of the
electron density in the polar cap and cusp. This underestimation is most
severe at nighttime and during solar maximum. A large discrepancy between the
IRI TEC and ESR TEC during the solar maximum (1999–2002) is consistent with
the findings of from the latest solar maximum.
Also previous versions of the IRI model have been compared with the ESR
electron density. Comparisons with the IRI-2001 and the IRI-2012 model show
that there are no major differences in the performance of the IRI-2016 model
and of previous versions. There are, however, some small differences. Most
noticeably, the IRI-2012 and IRI-2016 model reproduce the electron density
during winter 2001 significantly better than the IRI-2001 model. During solar
minimum, the IRI-2016 model seems to be slightly improved for altitudes below
the hmF2 compared with the IRI-2012 model.
An overestimation of the hmF2 occurs both during solar minimum and solar
maximum, but it seems to be slightly stronger during nighttime than during
daytime. At nighttime the IRI model hmF2 has clear seasonal variations, while
the hmF2 observed with the ESR radar has very little seasonal variation.
Finally, the comparison shows that the IRI model performs best at altitudes
close to the hmF2. At these altitudes (around 350 km during solar maximum and
260 km solar minimum), the IRI model reproduces the electron density more
accurately than at higher or lower altitudes.
Data availability
The EISCAT Svalbard radar data were retrieved from the Madrigal database and
are freely available from http://madrigal.haystack.mit.edu. Fortran code for
the various versions of the IRI model used can all be downloaded from
http://irimodel.org.
Acknowledgements
EISCAT is an international association supported by research organizations in
China (CRIRP), Finland (SA), Japan (NIPR and STEL), Norway (NFR), Sweden
(VR) and the United Kingdom (NERC). The authors wish to thank the IRI
working group for providing the models used in this paper. The topical editor, S. Milan, thanks D. Bilitza and one anonymous referee for help in
evaluating this paper.
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