response of the thermospheric density to solar euv and ... · the fism (chamberlin et al. 2008),...
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Response of the thermospheric density to solar EUV and solar wind forcing
T. Dudok de Wit (University of Orléans) S. Bruinsma (CNES, Toulouse)
Impacts of Intermediate Time Scale SSI Variability 12/2018
Outline
Objective : understand how the thermospheric density responds to solar EUV and to geomagnetic variability
Method: use a transfer function model to gain a better understanding
Motto: learn from what fails
2
What we know
Impacts of Intermediate Time Scale SSI Variability 12/2018
What do we know ?
On time scales ≫ month: variability in the thermospheric neutral density is primarily driven by solar EUV forcing
4
Emmert et al. GRL (2010)
log(density) @ 400 km
solar EUV flux (f10.7 index)
Emmert et al. GRL (2008)
Impacts of Intermediate Time Scale SSI Variability 12/2018
What do we know ?
On time scales < few months: variability is primarily driven by geomagnetic activity (storms), solar EUV + flares
5
Impacts of Intermediate Time Scale SSI Variability 12/2018
What do we know ?
On time scales < few months: variability is primarily driven by geomagnetic activity (storms), solar EUV + flares
6
density @ 800 km
30 cm radio flux (F30)
Ap index
0
10
20
(t)
[10-1
4 k
g m
-3]
density
0
50
100
150
Ap
Ap
2001 2002 200350
100
150
F3
0 [
sfu
]
F30
Impacts of Intermediate Time Scale SSI Variability 12/2018
What do we know ?
On time scales < day (discarded here): highly variable impact of solar flares and geomagnetic storms
7
Qian & Solomon, SSR (2012)
Thermospheric Density: An Overview of Temporal and Spatial
Fig. 1 Neutral density responses to an X17 flare occurred on October 28, 2003 and an X28 flare occurredon November 4, 2003. (a) Neutral density observed by CHAMP on October 28, 2003. The solar local timeof CHAMP orbit was ∼13:10. (b) Neutral density observed by CHAMP on November, 2003. The solarlocal time of CHAMP orbit was ∼12:45. (c) Neutral density simulated by TIE-GCM for October 28, 2003,sampled along the CHAMP orbit. FISM flare spectra were used as solar input for the TIE-GCM. (d) Neutraldensity simulated by TIE-GCM for November, 2003, sampled along the CHAMP orbit. FISM flare spectrawere used as solar input for the TIE-GCM; (c) GOES 0.1–0.8 nm solar irradiance and geomagnetic Kp indexfor October 28, 2003. (d) GOES 0.1–0.8 nm solar irradiance and geomagnetic Kp index for November 4,2003
1974; Davies 1990; Mendillo et al. 1974; Zhang et al. 2005; Tsurutani et al. 2006), withrelatively sparse research concerning the thermosphere (Sutton et al. 2005; Liu et al. 2007a;Pawlowski and Ridley 2008). The thermosphere, with its large mass and high heat capac-ity, is expected to be slower in responding to transient events such as solar flares. How-ever, model simulations and observations show significant rapid density response to solarflares.
Figure 1a and 1b show neutral density at 400 km observed by the CHAMP satellite alongits day-time orbit, for October 28, 2003, and November 4, 2003. Figure 1c and 1d are neutraldensity simulated by the TIE-GCM. Input flare spectra for the TIE-GCM were provided bythe FISM (Chamberlin et al. 2008), which is based largely on data from TIMED/SEE andthe X-ray monitors on the GOES satellites. TIE-GCM density was sampled along CHAMPorbits for comparison to the measured density. Figure 1e and 1f show solar flux in the wave-length range 0.1–0.8 nm measured by GOES 10, and geomagnetic Kp index. An X17 flare
soft X-ray flux
Thermospheric Density: An Overview of Temporal and Spatial
Fig. 1 Neutral density responses to an X17 flare occurred on October 28, 2003 and an X28 flare occurredon November 4, 2003. (a) Neutral density observed by CHAMP on October 28, 2003. The solar local timeof CHAMP orbit was ∼13:10. (b) Neutral density observed by CHAMP on November, 2003. The solarlocal time of CHAMP orbit was ∼12:45. (c) Neutral density simulated by TIE-GCM for October 28, 2003,sampled along the CHAMP orbit. FISM flare spectra were used as solar input for the TIE-GCM. (d) Neutraldensity simulated by TIE-GCM for November, 2003, sampled along the CHAMP orbit. FISM flare spectrawere used as solar input for the TIE-GCM; (c) GOES 0.1–0.8 nm solar irradiance and geomagnetic Kp indexfor October 28, 2003. (d) GOES 0.1–0.8 nm solar irradiance and geomagnetic Kp index for November 4,2003
1974; Davies 1990; Mendillo et al. 1974; Zhang et al. 2005; Tsurutani et al. 2006), withrelatively sparse research concerning the thermosphere (Sutton et al. 2005; Liu et al. 2007a;Pawlowski and Ridley 2008). The thermosphere, with its large mass and high heat capac-ity, is expected to be slower in responding to transient events such as solar flares. How-ever, model simulations and observations show significant rapid density response to solarflares.
Figure 1a and 1b show neutral density at 400 km observed by the CHAMP satellite alongits day-time orbit, for October 28, 2003, and November 4, 2003. Figure 1c and 1d are neutraldensity simulated by the TIE-GCM. Input flare spectra for the TIE-GCM were provided bythe FISM (Chamberlin et al. 2008), which is based largely on data from TIMED/SEE andthe X-ray monitors on the GOES satellites. TIE-GCM density was sampled along CHAMPorbits for comparison to the measured density. Figure 1e and 1f show solar flux in the wave-length range 0.1–0.8 nm measured by GOES 10, and geomagnetic Kp index. An X17 flare
measured density
soft X-ray flux
Impacts of Intermediate Time Scale SSI Variability 12/2018
Forcings
2 external forcings
Solar radiative forcing in the EUV
daily-yearly variations, impulsive bursts during flares only
Joule heating due to geomagnetic activity
highly variable in time
2 internal forcings
Dynamical coupling with the mesosphere below
wave activity: energy and momentum exchange
Infrared cooling by trace gases continuous, caused by greenhouse gases (CO2, CH4, …)
8
strong effect
strong but highly intermittent
weak and poorly known
weak with slow trend
Impacts of Intermediate Time Scale SSI Variability 12/2018
Open questions
1. How exactly does the thermosphere respond to external forcings (linearity, characteristic time scales, etc.) ? This response is not instantaneous (convolutive)
2. What are the best solar EUV proxies ? Is it possible to use one single solar proxy ?
3. What are the best geomagnetic proxies ? Is it possible to use one single geomagnetic proxy ?
9
Impacts of Intermediate Time Scale SSI Variability 12/2018
Major problem
Very few cases when one ONLY of solar/geomagnetic forcing is active
10
How can we study the effect of one forcing, while ignoring the other ?
0
10
20
(t)
[10-1
4 k
g m
-3]
density
0
50
100
150
Ap
Ap
2001 2002 200350
100
150
F3
0 [
sfu
]
F30
Impacts of Intermediate Time Scale SSI Variability 12/2018
2 strategies
11
model with physical assumptions
(MSIS, DTM, …)
tune
solar input
geomagnetic input
density
Impacts of Intermediate Time Scale SSI Variability 12/2018
2 strategies
12
model with physical assumptions
(MSIS, DTM, …)
tune
tune
empirical model (transfer function) density
solar input
solar input
geomagnetic input
geomagnetic input
density
Data and pre-processing
Impacts of Intermediate Time Scale SSI Variability 12/2018
Data
Data: orbit-averaged daily density at 800 km from STELLA (1993-2010)
Geomagnetic proxies: Am, Ap, etc.
Solar proxies: Mg index, F10.7, F30, etc.
14
Impacts of Intermediate Time Scale SSI Variability 12/2018
Pre-processing
Separate the observations into 2 time scales:
Baseline = long-term variations (> 1 month) mostly solar forcing + seasonal variations
Difference = short-term variations (< 1 month) solar and geomagnetic forcing
15
Dudok de Wit & Bruinsma, GRL (2011)
ρ(t)
[10−
14 k
g m−3
]
Apr02 Jul02 Oct02 Jan03 Apr03 Jul030
2
4
6
8
10densitysmoothing (30 days)baselineAp/50
Baseline is more resilient to geomagnetic storms and
to flares
Impacts of Intermediate Time Scale SSI Variability 12/2018
Pre-processing
Long-term variations (baseline) are well modelled by a nonlinear response of the density to the EUV
16
40 60 80 100 120 140
F30 [sfu]
0
1
2
3
4
5
[1
0-1
4 k
g m
-3]
STELLA monthly values of baseline
baseline of EUV flux
base
line
of d
ensit
y
Impacts of Intermediate Time Scale SSI Variability 12/2018
Transfer function model
Model the short-term variability (< 1 month) assuming the response of the density is linear and time-invariant
17
Impacts of Intermediate Time Scale SSI Variability 12/2018
Transfer function model
Model the short-term variability (< 1 month) assuming the response of the density is linear and time-invariant
Consider an Output Error (OE) model
18
density geomagne,cindex EUVflux modelerror
⇢[t] =B1(z�1)
F1(z�1)u1[t] +
B2(z�1)
F2(z�1)u2[t] + ✏[t]
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Impacts of Intermediate Time Scale SSI Variability 12/2018
Transfer function model
Model the short-term variability (< 1 month) assuming the response of the density is linear and time-invariant
Consider an Output Error (OE) modelusing the Z transform
19
density geomagne,cindex EUVflux modelerror
B(z�1)u[t] = b0u[t] + b1z�1u[t] + b2z
�2u[t] + . . .<latexit sha1_base64="ABbQhHQgHbcnjE1ZP9iK3KmYPzg=">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</latexit><latexit 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= b0u[t] + b1u[t� 1] + b2u[t� 2] + . . .<latexit sha1_base64="9L+gb3hxhHf6oH82I/GAdzeZYiA=">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</latexit><latexit sha1_base64="9L+gb3hxhHf6oH82I/GAdzeZYiA=">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</latexit><latexit sha1_base64="9L+gb3hxhHf6oH82I/GAdzeZYiA=">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</latexit><latexit sha1_base64="9L+gb3hxhHf6oH82I/GAdzeZYiA=">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</latexit><latexit sha1_base64="q9b/n3t31xxvFbrAMPgqMOBla70=">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</latexit><latexit sha1_base64="ctVNULD7ettKMhXQ+eE+iBuq4Ic=">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</latexit>
⇢[t] =B1(z�1)
F1(z�1)u1[t] +
B2(z�1)
F2(z�1)u2[t] + ✏[t]
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Impacts of Intermediate Time Scale SSI Variability 12/2018
Transfer function model
Model selection : how many terms in B(z-1) and in F(z-1) ? Typically 2 to 3 only (parcimoniny)
Model validation : train model on one sample and test it on a different one.
Results : model performs well but model error ϵ still contains dynamic noise rather than instrumental one
20
⇢[t] =B1(z�1)
F1(z�1)u1[t] +
B2(z�1)
F2(z�1)u2[t] + ✏[t]
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Results
Impacts of Intermediate Time Scale SSI Variability 12/2018
Results
Performance of empirical model is comparable to that of DTM
22
Jan 02 Apr 02 Jul 02 Oct 02 Jan 03 Apr 030
2
4
6
8
10
12
14
[10
-14 k
g m
-3]
observed densityOE modelDTM modelAp / 50
with F10.7
Impacts of Intermediate Time Scale SSI Variability 12/2018
Results
Performance of empirical model is comparable to that of DTM
23
Jan 02 Apr 02 Jul 02 Oct 02 Jan 03 Apr 030
2
4
6
8
10
12
14
[10
-14 k
g m
-3]
observed densityOE modelDTM modelAp / 50
with F30
Impacts of Intermediate Time Scale SSI Variability 12/2018
Results
Performance of empirical model is comparable to that of DTM
24
Jan 02 Apr 02 Jul 02 Oct 02 Jan 03 Apr 030
2
4
6
8
10
12
14
[10
-14 k
g m
-3]
observed densityOE modelDTM modelAp / 50
with F30Jan 02 Apr 02 Jul 02 Oct 02 Jan 03 Apr 03
am
plit
ude [arb
. units
]
SEMMgIISSNF10.7F30GyroBrem
Impacts of Intermediate Time Scale SSI Variability 12/2018
Impulse response
Impulse response = how would the density respond to a one-day unit increase in either solar or geomagnetic forcing
25
Impacts of Intermediate Time Scale SSI Variability 12/2018
Impulse response = how would the density respond to a one-day unit increase in either solar or geomagnetic forcing
Impulse response
26
-5 0 5 10
time [days]
-2
0
2
4
6
8
10
12
14
16
imp
uls
e r
esp
on
se o
f d
en
sity
10-3 response to Ap
-5 0 5 10
time [days]
-2
0
2
4
6
8
10
12
14
16
imp
uls
e r
esp
on
se o
f d
en
sity
10-3 response to F30
Overshoot and rapid relaxation
Slow relaxation, partly non-causal
1σ confidence interval
Impacts of Intermediate Time Scale SSI Variability 12/2018
Conclusions (1/2)
Empirical model offers better reconstruction than existing (DTM, JB2006, ...) models ➞ 20-30% error reduction
No need to distinguish periods during which one type of forcing only is active ➞ better statistics
Allows to test different solar proxies for orbit specification
27
Impacts of Intermediate Time Scale SSI Variability 12/2018
Conclusions (2/2)
Most appropriate solar EUV proxy is the 30 cm radio flux (F30)(rather than F10.7 or MgII index)
Response on time scales < 1 month EUV forcing: response is remarkably linear
geomagnetic activity: mostly linear response
Recovery time for geomagnetic forcing is < 1 day = faster than the resolution of our data (beware)
Learn from what does not (yet) work
28
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�⇢
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