Impact of Lower
Atmosphere and High-Latitude Forcing on Thermospheric Density
Vikash Kumar Singh*
Ph.D. Scholar, Department of Physics, Shree Krishna
University, Sagar Road, Chhatarpur, M.P. India
vikashami92@gmail.com
Abstract : During the
geomagnetically disturbed period from 31 January to 3 February 2024, this
research examines the combined effects of decreased atmospheric forcing and
high-latitude magnetospheric inputs on thermospheric neutral density. The work
investigates the impact of realistic lower-boundary conditions, specifically
those derived from WACCMX-SD, on the global thermospheric response relative to
climatological forcing using Swarm-C satellite observations and a number of
TIEGCM-based simulations. By using real lower atmospheric disturbances, density
errors are regularly reduced, particularly in the northern hemisphere In many
latitude zones, reductions of up to 15% have been seen. It is important to have
correct representations of the connection between the magnetosphere and
ionosphere because models powered by field-aligned currents (FAC) obtained from
AMPERE data perform better than those employing empirical Weimer electric
fields, especially at night and at high northern latitudes. Results show that
complex interactions including circulation patterns, tidal variability,
composition variations, and scale height differences based on altitude are the
root cause of interhemispheric asymmetries in density response. The research
concludes that in order to better model and forecast space weather, it is
necessary to take into account both lower atmospheric dynamics and
high-latitude energy inputs, since both are crucial in capturing fluctuations
in thermospheric density.
Keywords: lower atmosphere, high-latitude
forcing, thermospheric density
INTRODUCTION
Atmospheric tides, planetary waves,
and seasonal circulation patterns may alter the thermosphere's condition, and
fluctuations in geomagnetic activity also affect it. The significance of
comprehending this multiscale interaction for satellite drag, orbital
prediction, and variability in the ionosphere-thermosphere (IT) system has
grown in recent years. [1]
Increased energy intake from
field-aligned currents or particle precipitation in the auroral area may
significantly change the thermosphere's density, temperature, or composition
during geomagnetic storms, according to research. Also, neutral winds and
vertical transport are affected by lower atmospheric forcing, which includes
both migratory and non-migrating tides. This causes hemispheric asymmetries and
variations in mass density that are dependent on altitude. [2]
These coupling mechanisms can now be
more accurately represented thanks to recent developments in whole-atmosphere
modeling. The fluctuation of planetary waves and tides may be better captured
by data-assimilative models like WACCMX-SD, which, when combined with MERRA-2
reanalysis, provide lower boundary conditions that are more realistic than
climatological ones.[3]
This period is perfect for testing
the relative contributions of lower atmospheric drivers and magnetospheric
forcing because the Swarm-C satellite detected substantial density enhancements
and clear hemispheric differences during the moderate geomagnetic disturbance
from 31 January to 3 February 2024, which NOAA classified as a G1 storm. [4] During
this time, Swarm-C was in an orbit of 450–478 km, a region where atomic oxygen
is abundant and where differences in density may be detected due to tiny
changes in wind-driven transport. [5]
Although this trend flipped in
certain daylight low-latitude locations, demonstrating complex seasonal and
dynamical interactions, observations indicated that neutral density in the
Southern Hemisphere was 30% greater than the Northern Hemisphere during
nighttime orbits. [6]
The study's objective is to
ascertain the relative contributions of each driver to the observed
fluctuations in neutral density by comparing several TIEGCM simulations that
include climatological and WACCMX-SD lower bounds in addition to Weimer and
AMPERE-derived high-latitude forcing. [7] To enhance thermospheric modeling,
this method clarifies interhemispheric disparities, reactions that vary with
altitude, and the processes that lead to simulation mistakes.[8]
METHODOLOGY
The neutral density from 31 January
to 3 February 2024, a moderately geomagnetically disturbed interval, was
examined and how lower atmospheric and high-latitude forcing influenced it.
This is a modest G1 on the NOAA Space Weather scale, but it is nonetheless
notable. Due to mesoscale magnetosphere-ionosphere coupling events, "Next
Generation Advances in Ionosphere-Thermosphere Coupling at Multiple Scales for
Environmental Specifications and Predictions" focused on this period. This
work aims to uncover the impact of lower atmospheric forcing with high-latitude
magnetosphere forcing, after an initial data-model comparison that revealed
significant hemispheric disparities in the simulation outcomes for obtaining
the Swarm neutral mass density readings. This research made use of TIEGCM
models and Swarm-C neutral density assessments.
Below is a summary of the weather
and climate for the period from January 30 to February 3, 2024. Starting at 5
nT, geomagnetic activity begins around the end of January 30. On January 31, a
few hours later, the IMF Bz moves south and stays south until 1 February (doy
32) six UT. IMF On 2 February (doy 33), the usual By and Bz swings occur, but
on 3 February, at approximately four UT, there is a long-lasting southern IMF
Bz phase that begins late and continues for a few hours before moving
northward. As on January 31st, the Sym-H index, which is a measure of the
symmetric ring current's strength, will be in the negative state until February
1st. Recuperation occurs on February 2nd, followed by another disturbance on
February 3rd.
Figure 1: Dates and weather forecasts for January 30–February 3, 2024
(1924
Neutral Density of A Swarm
A four-step Swarm data product
(DNSxACC version 0201) by Siemes et al. (2016) provides neutral density [9].
Until then, Swarm-C orbits about 450-478 km. South-bound high-latitude orbits
are 20 kilometers higher than north-bound. NRLMSIS2.0 says lower altitudes have
1.4-5 times greater neutral density. In medium to low latitude orbits,
overnight is 2.5-3 hours SLT and daylight is 14-15 hours. Figure shows the
average sun zenith angle lighting the southern polar region at night. An angle
darkens the northern hemisphere.
Methods for comparing neutral
density emphasize different variance features. Neutral density may be measured
globally, orbitally, relative, absolute, and altitude-scaled. To eliminate
scaling bias based on common height, use the orbit's neutral density.
With no more than two orbits per
bin, observed neutral density is likely more accurate than calculated, which
uses 2 hours and 4 degrees of geographic latitude bins. Doy 32 and 34 have high
geomagnetic activity, raising neutral density. However, at low and medium
latitudes, the neutral density is not necessarily larger in the NH than in the
SH.
Distinct variations in neutral
density between the 2 hemispheres may have several causes. Variations in the
sun zenith angle throughout the year cause neutral dynamics & composition
to vary throughout the hemispheres. Swarm orbit altitude differs between SH
summer and NH winter, which counteracts the seasonally increased neutral
density in the former. Furthermore, the neutral density and thermospheric and
ionospheric states may be altered by the reduced atmospheric forcing, which
includes its own intrinsic seasonal fluctuation. The increased energy input from
high latitudes into the IT system during geomagnetic storms might cause
hemisphere variations. To model the neutral density fluctuations using TIEGCM,
we will examine the role of forcing at lower atmospheric and upper latitude
levels.
TIEGCM
Incorporating thermosphere and
ionosphere energetics, chemistry, and atmospheric dynamics, the TIEGCM achieves
self-consistency. Implications from magnetosphere-ionosphere coupling, the wind
dynamo, and the current produced by gravity & plasma pressure gradients
constitute the TIEGCM's ionospheric electrodynamics.
Its range depends on solar cycle
conditions, from 97 to 450–600 kilometers. We utilize 2.5o x 2.5o horizontal
resolution for global latitude and longitude. An analytical auroral model
defines cloud particle precipitation in both circumstances. Weimer and FAC
driven models updated the default TIEGCM auroral parametrization, as seen in
the first supporting document. This section shall refer to the Weimer-driven
simulation as "Weimer" & the field-aligned current-driven
simulation as "FAC."
The two hemispheres' high latitude
FAC patterns are generated by principal component analysis of Iridium satellite
AMPERE magnetic field observations. The FAC distribution is smoother than the
AMPERE field-aligned current since less PC are used. Compared to AMPERE FAC,
PC-based FAC has a lower hemisphere combined up and down FAC measure. By
increasing the FAC magnitude in both sides by 45%, we may attain hemispheric
integrated FAC intensities comparable to the initial AMPERE data.
The
three-step process for determining electrostatic potential... The electric
potential is first determined by the global wind dynamo and the hemispherically
symmetrical FAC component. Using either the local wind dynamo or the symmetric
potential solution from step 1, the FAC at the top of the ionosphere in each
magnetic hemisphere is calculated in step 2. In the third phase, for each
hemisphere, utilize the computed FAC minus the given FAC. In Step 2, the FAC is
computed at the upper boundary at high latitudes, and in Step 3, the zero
potential restriction is determined at the equatorwards border (here at |400| magnetic
latitude). Repeat for each hemisphere. After stages 1 and 3, a magnetic grid
has symmetric and asymmetric potentials. To calculate electric potential, add
steps 1 and 3. To balance ionosphere current, the FAC must be modified at each
level.
We can explain background variations
and disturbances in horizontal wind, neutral temperature, or geopotential
height at the TIEGCM LB, about 97 km. We run two simulations to determine how
decreasing atmospheric forcing affects neutral density. We employ a
climatological LB baseline or perturbations in one simulation. The MSIS00 model
& HWM07 horizonal wind model establish the LB background, while we employ
GSWM tidal climatology. GSWM includes diurnal, semi-diurnal, and non-migrating
tidal components. The mid-month TIEGCM describes and interpolates hourly GSWM
perturbations chronologically. This simulation is labeled "Climate".
A TIEGCM simulation is compared
using WACCMX-SD LB. Surface and thermosphere climate model WACCM-X includes
complete atmosphere. WACCM-X dynamics are pushed up to 50 km toward reanalysis
data like Modern-Era Retrospective analysis for Research & Applications,
Version 2 to model certain time periods. WACCMX-SD data at the TIEGCM LB may
reveal the background "B" & perturbations "P"
throughout this time, including planetary waves and tides. We employ WACCMX-SD
output at the pressure level closest to the TIEGCM LB to study the neutral
density change caused by a more realistic background environment and the lower
boundary perturbation. Baseline: geopotential height, neutral temperature,
daily zonal & diurnal horizontal wind mean. By removing background from
total fields, perturbation fields result. "WacXBP" is the LB
WACCMX-SD simulation. Simplify the "Climate" simulation using the
climatological baseline (CB) & WACCMX-SD perturbations (WacXP) as
"WacXP-CB" case study. Every simulation uses the TIEGCM, although
they handle forcing at the lower boundary and high latitudes differently.
Using the 3-hourly Kp
index-generated high latitude electric potential and suitable lower boundary
forcing, all of our simulations start on day 10, 2024. High latitude forcing
simulations were resumed from day 30. Using the same binning approach, we
compare the synthetic data to the TIEGCM simulated neutral density for the
Swarm-C orbit. For all time, the TIEGCM's upper boundary has been higher than
Swarm-C's orbital height. The sum of the absolute differences (L-1 norm) of the
binned data is used to compare the simulated and actual neutral densities,
rather than the root mean square error, which weights by error size. The entire
Swarm-C neutral density fluctuations are used to determine comparative errors
unless otherwise stated.
RESULTS
Implications of reduced atmospheric
forcing
First, we compare simulations
utilizing climatological forcing at the lower boundary and WACCMX-SD (WacXBP)
to investigate how lower atmospheric forcing impacts neutral density at Swarm-C
altitude. The high latitude FAC force is same in all cases. The graphic shows
that Climate & WacXBP simulations of the Swarm-C neutral density for both
nighttime and daytime orbits were wrong.
At night, neutral density error is
larger than during the day. NH has a higher daytime simulated neutral density.
Everywhere except north of 60 degrees south, nighttime simulated neutral
density is overestimated. The neutral density error is not increased by the doy
32–34 unrest.
Compare the Climate simulation to
the WacXBP simulation in Figure. More realistic LB fluctuations decreased
inaccuracy, especially in NH. The southern hemisphere's mid- &
low-latitudes have substantially lower nighttime inaccuracy than daytime.
Neutral density in the southern polar area is consistent throughout the
simulation.
Figure 2: Differences in neutral density between TIEGCM(WacXBP) or Swarm-C & TIEGCM(Climate) & Swarm-C, as well as variations in the neutral density's daytime and nighttime orbits
We narrow the emphasis in Figure to
the average fluctuation in neutral density over certain latitudinal regions in
order to simplify the findings. Typically, the discrepancy is more pronounced
after the sun goes down. When comparing the WacXBP and Climate simulations for
the shown northern hemisphere scenarios, the former shows less inaccuracy
overall; however, this improvement is less pronounced at night. When comparing
the WacXBP and Climate simulations, the difference in the northern hemisphere
is around a 15% reduction in inaccuracy. We cannot rule out the possibility
that LB conditions from other years with comparable variability might provide
similar findings, even if the climatology outperforms the WacXBP simulation
using the wave spectrum from the February 2024 timeframe when it comes to
capturing the neutral density. This is beyond the purview of the present
investigation, which is concerned with the significance of the lower atmosphere
& extreme latitude forcing in general.
Figure 3: Swarm-C, TIEGCM(WacXBP) , &
TIEGCM changes in neutral density over the northern hemisphere's latitudes.
Find out why the NH boosts neutral
density more than the SH by dissecting the models. In the lower thermosphere,
the Climate and WacXBP models show unique 5-day averaged zonal mean wind
patterns at 120 km about doy 30-34. The main points will be supported by a
simplified diagram. The climate model's thermosphere circulation has a
summer-to-winter cycle, with raising in the south (beyond 20 S), going north,
and dropping in the north (beyond 70 N). The WacXBP model has a slightly
greater average speed near the poles and a lower southern hemisphere speed
beyond 70 S, below 120 km.
The two models' circulations over
140 km are comparable in summer and winter. The Climate simulation changes
temperature and composition, whereas WacXBP has greater circulation. Figure
displays average zonal mean neutral temperature for a 5-day period (doy 30-34)
between 200 < |λg| 60o. WacXBP in the SH has lower temperatures than
the Climate simulation above 150 km because to upwelling and adiabatic cooling.
The WacXBP model forecasts higher North Atlantic temperatures owing to
downwelling, but the climate simulation predicts a cooler thermosphere.
The WacXBP simulation's southern hemisphere is
warmer than the Climate simulation's below 140 km, perhaps due to greater
downhill or no upward circulation. Temperature and mean circulation alter
neutral density and composition. The neutral density is more impacted by N2
than O1 below 180 km. In the southern hemisphere below 140 km, WacXBP has a
lower N2 number density than Climate. This is because the former transports N2
from locations with greater number densities towards greater altitudes with an
upward pace, whereas the later does so at a downward rate. At these altitudes,
the WacXBP scenario has a lower neutral density in the southern hemisphere than
the Climate scenario due to less N2 in the lower thermosphere.
Figure 4: (A). Doy 30–34 TIEGCM(WacXBP) vs. (Climate) (A). diurnal and
zonal mean circulation (B–D). TIEGCM(WacXBP) & TIEGCM(Climate) show average
changes across 20o < |λg| ≤ 60o and doy 30–34 at altitude (B).
neutral density vs. TIEGCM(WacXBP); K (D) temperature. Comparing O & N2
number density to TIEGCM(WacXBP).
Lower altitude circulation in the
northern hemisphere is not different in the models. The WacXBP example has a
lower neutral density at these altitudes than the Climate simulation due to
enhanced tidal variability and air mixing.
At 450 km swarm heights, atomic
oxygen should dominate. Summer has a greater scale than winter, hence vertical
gradients in O1 density are fewer in southern summer than northern winter. Because
the northern winter hemisphere has bigger vertical gradients, the LB boundary's
vertical velocity fluctuations will affect number density more than in the
southern summer. Due to stronger downwelling, WacXBP lowers O1 more in the
northern hemisphere than Climate. Because O1 transfers better to
high-recombination locations. Since WacXBP has a larger scale height in NH than
Climate, altitude reduces the absolute difference in O1 number density.
As in the NH, the SH had a smaller
absolute change in O1 number density between Climate or WacXBP models. In the
WacXBP model, vertical winds and tidal variations may boost air mixing. The
Climate simulation has a higher southern hemisphere mean temperature &
scale height than the WacXBP simulation, although their absolute O1 number
density disparity grows slowly with altitude. Southern hemisphere neutral density
differences grow roughly linearly with altitude in Climate & WacXBP
simulations, although they are lower than the NH difference between 200 &
470 km. At the end of the simulation, decreasing boundary forcings should
induce equal O1 number density changes in the southern & northern hemispheres
at altitudes above 450 km.
The models predict a maximum interhemispheric
difference of 350 km in the upper thermosphere, which varies with height and
the neutral density response to lower atmospheric forcing. At an altitude where
NH reacts more to LB changes than SH, Swarm-C is above the maximum differences.
We examine the effects of LB
disturbances and backdrop on the IT system by substituting the WacXB background
with the climatological LB background from CB. The WacXP-CB and WacXBP
simulations vary because to LB background force variation. Based on other
research, LB perturbations are more relevant than background forcing.
Quantitative study does not explain
how the hemispherically asymmetric component of WACCMX-SD perturbations creates
the response difference between the hemispheres. LB perturbations are necessary
to replicate large-scale neutral density Geopotential height, LB symmetric
zonal wind, & antisymmetric meridional winds are simulated. In most
instances, the southern-northern error gap increases when the LB is not
interrupted symmetrically. The WacXBP simulation may have 2% lower SH error and
8% higher NH error. Understanding how the two pieces react requires further
research. Asymmetric LB perturbations partially cause hemisphere neutral
density disparities, according to simulations.
Influence
of high-latitude temperatures
When studying local and regional
effects in the thermosphere and ionosphere, in particular the cusp neutral
density improvements, it is crucial to have precise measurements of the
magnetospheric energy input into the IT system. The importance of a more accurate
depiction of forcing at high latitudes to the large-scale reaction at low and
medium latitudes is less apparent. Hence, we will contrast FAC simulation based
on AMPERE data with the empirical Weimer in the following. At the TIEGCM lower
boundary, WACCMX-SD forcing is applied in both simulations.
The neutral density error as it
relates to both the simulations and the Swarm-C data varies with latitude and
time, as seen in the figure. In the northern hemisphere, TIEGCM(FAC) often
performs better than TIEGCM(Weimer), particularly at night, with a decreased
neutral density error of up to 7%-20%. Daytime neutral density errors in
northern middle latitudes are comparable for TIEGCM(FAC) & TIEGCM(Weimer).
In the southern hemisphere, the TIEGCM(Weimer) simulation exhibits somewhat
fewer errors of 1-3% compared to TIEGCM(FAC), but, TIEGCM(FAC) improves the
night-time orbit neutral density agreement with Swarm-C.
Figure 5: neutral
density difference between TIEGCM(FAC) and Swarm-C (A) & (C) and
TIEGCM(Weimer) & Swarm-C (B) and (D) for night-time & day-time orbits,
respectively.
In the night-time orbit, the neutral
density error is bigger in the northern hemisphere than in the southern, as
demonstrated by the fluctuation poleward of |60o| geographic
latitude. Switching from Weimer to FAC forcing causes greater neutral density
changes and enhancements in Swarm-C orbit in the northern high latitudes,
especially at night, than in the southern sector. In response to high latitude
forces, the models' varying Joule heating across the hemispheres cannot explain
the observed hemispheric discrepancy. Figure shows the TIEGCM(FAC) or
TIEGCM(Weimer) models' hemispheric integrated Joule heating difference. Both
models reveal that the IT system's Joule heating input from the northern &
southern polar regions differs.
Figure 6: Swarm-C, TIEGCM(FAC), and TIEGCM(Weimer) throughout the
night, with large average neutral density changes over the length of the sky
The neutral density and Joule
heating discrepancies across the hemispheres are difficult to connect. The
northern and southern hemisphere models have a modest relationship in neutral
density & hemispheric integrated Joule heating (r = 0.45 and r = 0.3, respectively)
even with a time lag. Please note that the 100 GW anomaly in Figure from doy
31.5 to 32.0 accounts for 40-50% of the total hemispheric integrated Joule
heating from the TIEGCM(Weimer) and practically 100% of the TIEGCM(FAC).
The neutral density difference is
larger in the northern high latitude zone than in the southern high latitude
zone for the same Joule heating differences, hence we concentrate on average
values poleward of 60o geographic latitude at 3 hours SLT for doy
31.5 to 32.0. In this time period, the SH has a smaller neutral density
differential than the NH, but their hemispheric integrated Joule heating
differences are similar.
Figure 7: Difference. Night-orbit high
latitudinal averaged (600 < |λg| ≤ 900) neutral density [kg/m3]
difference between TIEGCM(FAC) and (Weimer) and (B). height & high
latitudinal integration (500 < |λm| ≤ 900) TIEGCM(FAC) &
TIEGCM(Weimer) northern & southern hemisphere joule heating rate [GW].
The higher thermosphere has a larger
neutral density difference between NH and SH, as seen in Figure. The dark
winter hemisphere is more affected by Joule heating because the neutral
temperature change in the NH is larger than in the SH for the same heating
difference. Figure also shows that the TIEGCM(Weimer) simulation has a slightly
higher integrated Joule heating value in the NH than the TIEGCM(FAC)
simulation, and that the NH dissipates energy more efficiently at higher
altitudes (above 120 km) than the SH, where it can change the atmosphere or
neutral density. The results below compare 2-4 and 3 hours SLT.
Figure shows how much the
simulations differ compositionally. A positive neutral mass density difference
exists below 150 km because the N2 number density in TIEGCM(FAC) is greater
than in TIEGCM(Weimer) in the NH, or this difference is larger than in the SH.
Both northern & southern hemispheres have positive atomic oxygen
differences below 340 kilometers. In the northern hemisphere, atomic oxygen
levels reach 340 km, however TIEGCM(FAC) has lower values than TIEGCM(Weimer)
owing to its smaller scale height. TIEGCM(FAC) northern hemisphere N2 number
density falls with altitude over 150 km compared to TIEGCM(Weimer). Since the
NH neutral density difference is practically constant in altitude between 180km
& 230km, the positive atomic oxygen difference may explain why TIEGCM(FAC)
reduces N2 number density faster than TIEGCM(Weimer). The NH neutral density
gap between 2 models decreases beyond 300 km due to temperature and
compositional changes.
Figure 8: At 3 hours SLT, the profiles of the discrepancies between
TIEGCM(FAC) and TIEGCM(Weimer) for the northern hemisphere (dark blue dashed
lines) and the southern hemisphere (dark orange dotted lines) averaged between
600 < |λg| ≤ 900 and doy 31.5 to 32.
The southern hemisphere TIEGCM(FAC)
so TIEGCM(Weimer) simulations show a smaller negative bias for N2 and a
positive bias for O1, and they change less with altitude than the northern
hemisphere At practically all altitudes, the TIEGCM(FAC) and TIEGCM(Weimer)
simulations show a lower SH than NH neutral density difference. This may be due
to the increase in O1 number density, the lesser fall in N2 number density, or
the smaller temperature change in SH than NH below 450 km Between 250 and 450
km, the southern neutral density difference is steady, but it should drop
beyond 450 km.
Complex dynamical and compositional
changes may occur during simple geomagnetically interrupted periods.
TIEGCM(Weimer) predicts greater equatorward thermospheric winds in the North
Atlantic than TIEGCM(FAC) and poleward winds in subauroral areas. Due to
neutral wind changes, the zonal mean atomic oxygen peak travels equatorward
from 60 N at quiescent time to 35 N in the TIEGCM(Weimer) simulation.
TIEGCM(FAC) simulations only show 45 N movement. The Weimer simulation has less
polar atomic oxygen below 350 km than the TIEGCM(FAC) simulation. Comparing
TIEGCM(Weimer) with TIEGCM(FAC) simulations shows increased and continuous
meridional transfer of atomic oxygen away from the polar area.
Numerous studies have extracted
neutral density and quiescent temporal fluctuations from geomagnetic activity.
We compute the average quiescent time variation and examine whether decreased
atmospheric forcing impacts neutral density. We will eliminate "disturbed"
neutral density from average quiescent time latitudinal variation using Climate
and WacXBP models.
Figure displays Swarm-C
"disturbed" neutral density after eliminating average latitudinal
quiescent time shifts from doy 30, 0-22 UT. Doy 32 and 34 stand out in mild
geomagnetism, as expected. Simulated quiescent time latitudinal variance is
removed by the same manner. Swarm-C neutral density without
"disturbed" causes simulation error. When utilizing WacXBP at the
lower boundary, TIEGCM(WacXBP) is less inaccurate than Climate.
Figure 9: Disturbance neutral density variation for both night-time
and day-time orbits of Swarm C, as measured by removing the average of 30 UT
0-21 for both panels (A-C) and (D) and (F), as well as the difference in
disturbance variations between TIEGCM(WacXBP) or Swarm-C (B) & (E),
alongside TIEGCM(Climate) & Swarm-C (C) & (F).
CONCLUSION
The study's conclusions show that
thermospheric neutral density changes are significantly shaped by both
high-latitude magnetospheric inputs and lower atmospheric forcing, which work
in concert. In the northern hemisphere, simulations using realistic WACCMX-SD
lower boundary conditions reduce density errors by up to 15% and improve
agreement with Swarm-C data, particularly at mid- and high latitudes, outperforming
those with climatological forcing. It is discovered that the effects of reduced
atmospheric variability are highly hemisphere- and altitude-dependent,
primarily because of variations in vertical winds, compositional gradients, and
tidal influences. Similarly, the use of AMPERE-derived field-aligned currents
enhances the depiction of high-latitude energy input, resulting in more
accurate density improvements during disturbed times, especially in the dark
winter hemisphere when Joule heating effects are more pronounced. The research
emphasizes that altitude-dependent compositional behavior, asymmetric heating,
and circulation alterations all contribute to interhemispheric asymmetries in
density response, which cannot be ascribed to a single cause. Overall, the
findings highlight how reliable space weather prediction models and neutral
density forecasts—which are essential for satellite operations—can only be
achieved by combining realistic high-latitude forcing with correct lower
atmospheric dynamics.
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