Assessment of the NeQuick Model at Mid-latitudes using GPS TEC and Ionosonde Data

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Assessment of the NeQuick model

at mid-latitudes

using GPS TEC and ionosonde data

Benoît Bidaine (ULg – Geomatics, Belgium) René Warnant (RMI, Belgium

July 11th, 2007

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Ionosphere Troposphere 2

40.3 TEC

I

f

=

⋅

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1. Tools

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1. Tools

Modelling and measuring the ionosphere

2. vTEC analysis

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1. Tools

2. vTEC analysis

NeQuick vs GPS TEC data

3. Case days

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4. Profile analysis

NeQuick vs ionosonde data

1. Tools

2. vTEC analysis

NeQuick vs GPS TEC data

3. Case days

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4. Profile analysis

1. Tools

2. vTEC analysis 3. Case days

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NeQuick is

an empirical « profiler ».

• Output = Ne Æ TEC with integration

• Layer peaks = anchor points

Æ monthly median CCIR maps

• Input = ionospheric variations such as solar flux

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It will be used on a daily basis

for GALILEO SF users.

Optimize Az Run NeQuick Measure sTEC

• Monthly flux replaced by daily parameter (Az)

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TEC can be determined

with GPS.

• Geometric free observables (code and phase)

1. Tools , 2 2 , 1 2 1 1 40.3 i i i p GF p p GF L L P TEC CG f f ⎛ ⎞ = ⋅ _⎜ − _⎟+ ⎝ ⎠ 1 , ₂ ₂ , 2 1 1 1 40.3 i i L i p GF p p GF L L f TEC CP c f f ϕ = − ⋅ ⎛_⎜ − ⎞_⎟+ ⎝ ⎠

• Differential code biases estimated and eliminated

• Latitude filter Æ vertical:

• Mean over 15 minutes

1 1

sta iono sta

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Ne profiles can be obtained

with an ionosonde.

• Vertical sounding Æ virtual heights

and plasma frequencies

1. Tools 8.98 f = ⋅ Ne ' 2 cT h =

• Scaling Æ true heights and Ne

• Digisonde from UMLCAR

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Ne profiles have different

analytical formulations.

1. Tools

Digisonde

Sum of Epstein layers _{Each layer in terms of}

shifted Chebyshev polynomials

+ valley

Semi-Epstein layer α-Chapman function

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We can learn a lot

using collocated data.

1. Tools

• Dourbes (Belgium ; 50.1N 4.6E)

• GPS station: vTEC every 15 minutes

• Digisonde DGS256: profiles every hour till 2005 and every 20 minutes afterwards

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4. Profile analysis 1. Tools

2. vTEC analysis

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Let’s compare measured and

modelled vTEC evolution with time.

• Variations: 1 solar activity (year and solar flux)

2 season (month)

[3 UT (expected monthly median)]

• Statistics: 1 mean (bias) [or median]

Æ over/underestimation 2 RMS Æ error

2. vTEC analysis

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Solar activity

Tools

• Data: 1998 for average solar activity, 2000 to 2002 for high,

2006 for low

• Model: ITU-R version

index R₁₂ (SIDC) or Φ₁₂ (NOAA)

2. vTEC analysis

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Solar activity

TEC

2. vTEC analysis 5 7 9 11 13 15 17 19 21 23 25 1997 1999 2001 2003 2005 2007 Year TEC [ T EC u ]

GPS NeQuick (SSN) NeQuick (flux)

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Solar activity

Conclusion

• SA index

– Better monthly smoothed flux

– Conversion formula to investigate

• Focus

– Low SA level: 2006 Æ overestimation

– High SA level: 2002 Æ underestimation

2. vTEC analysis

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Season

Low solar activity level

2. vTEC analysis 1 2 3 4 5 6 7 8 9 10 11 12 60 80 100 120 140 160 180 200 Month

Solar radio flux [10

−22 W m −2 Hz −1] 1 2 3 4 5 6 7 8 9 10 11 12 −6 −4 −2 0 2 4 6 8 10 12 Month TEC [TECu]

Measured vTEC mean Modelled vTEC mean vTEC difference mean

vTEC difference RMS 6-month

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Season

High solar activity level

2. vTEC analysis 1 2 3 4 5 6 7 8 9 10 11 12 150 155 160 165 170 175 180 185 190 195 Month

Solar radio flux [10

−22 W m −2 Hz −1] 1 2 3 4 5 6 7 8 9 10 11 12 −10 −5 0 5 10 15 20 25 30 35 40 Month TEC [TECu]

Measured vTEC mean Modelled vTEC mean vTEC difference mean

vTEC difference RMS Solar flux

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Season

Conclusion

2. vTEC analysis • Ambivalent behaviour • Flux influence • Focus

– Low SA level: July 2006 Æ good

– Autumn: October 2006 Æ bad

– Summer: July 2002 Æ good

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4. Profile analysis 1. Tools

2. vTEC analysis

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Low solar activity level

3. Case days 5 10 15 20 25 30 0 0.5 1 1.5 2 2.5 Day

vTEC difference [TECu]

July:

best month

Lowest RMS: 27th

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Low solar activity level

3. Case days 0 5 10 15 20 −6 −5 −4 −3 −2 −1 0 1 2 3 4 TEC [TECu] UT [h] 25 26 27 28 29 July: best month Lowest range comparable with GPS TEC uncertainty

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Lowest range

comparable with GPS TEC uncertainty

Low solar activity level

3. Case days

27 27.1 27.2 27.3 27.4 27.5 27.6 27.7 27.8 27.9 0

5 10 15

Modelled vTEC [TECu]

27 27.1 27.2 27.3 27.4 27.5 27.6 27.7 27.8 27.9 0 5 10 15 Day

Measured vTEC [TECu]

July: best month Lowest RMS: 27th Maximum: 19h

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Low solar activity level

3. Case days 5 10 15 20 25 30 0 1 2 3 4 5 6 7 Day

October:

worst month

Highest RMS: 30th

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Low solar activity level

3. Case days 0 5 10 15 20 −14 −12 −10 −8 −6 −4 −2 0 TEC [TECu] UT [h] 27 28 29 30 31 October: worst month False maximum: 17h30

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30 30.1 30.2 30.3 30.4 30.5 30.6 30.7 30.8 30.9 0

5 10 15 20

30 30.1 30.2 30.3 30.4 30.5 30.6 30.7 30.8 30.9 2 4 6 8 10 Day

Low solar activity level

3. Case days October: worst month Highest RMS: 30th False maximum: 17h30

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High solar activity level

3. Case days 5 10 15 20 25 30 0 2 4 6 8 10 12 Day

July:

best month

Lowest RMS: 10th

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High solar activity level

3. Case days 0 5 10 15 20 −6 −4 −2 0 2 4 6 8 10 12 TEC [TECu] UT [h] 7 8 9 10 11 July: best month Small bias: 9h45

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High solar activity level

3. Case days 10 10.1 10.2 10.3 10.4 10.5 10.6 10.7 10.8 10.9 8 10 12 14 16 18 20 22

10 10.1 10.2 10.3 10.4 10.5 10.6 10.7 10.8 10.9 8 10 12 14 16 18 20 22 Day

July: best month Lowest RMS: 10th Small bias: 9h45

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High solar activity level

3. Case days 5 10 15 20 25 0 5 10 15 20 25 30 Day

February:

worst month

Highest RMS: 26th

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High solar activity level

3. Case days 0 5 10 15 20 −10 0 10 20 30 40 50 TEC [TECu] UT [h] 24 25 26 27 28 February: worst month Maximum underestimation: 10h30

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High solar activity level

3. Case days 26 26.1 26.2 26.3 26.4 26.5 26.6 26.7 26.8 26.9 0 10 20 30 40 50

26 26.1 26.2 26.3 26.4 26.5 26.6 26.7 26.8 26.9 0 20 40 60 80 100 Day

February: worst month Highest RMS: 26th Maximum underestimation: 10h30

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Conclusion

• Afternoon maximum in summer:

July 27th, 2006 – 19h

• False afternoon maximum in autumn:

October 30th, 2006 – 17h40

• Morning maximum in summer:

July 10th, 2002 – 10h

• Underestimation at high solar activity:

February 26th, 2002 – 10h

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4. Profile analysis

1. Tools

2. vTEC analysis 3. Case days

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108 109 1010 1011 1012 0 100 200 300 400 500 600 700 800 900 Ne [e− m−3] h [km] Measured Ne Modelled Ne

Absolute value of Ne difference

July 27th, 2006

19h

4. Profile analysis Denser topside Slightly less dense F2 peak

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October 30th, 2006

17h40

4. Profile analysis 108 109 1010 1011 1012 0 100 200 300 400 500 600 Ne [e− m−3] h [km] Measured Ne Modelled Ne

Denser topside Slightly denser F2 peak Denser bottomside Slower decrease

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107 108 109 1010 1011 1012 0 100 200 300 400 500 600 700 800 900 1000 Ne [e− m−3] h [km] Measured Ne Modelled Ne

July 10th, 2002

10h

4. Profile analysis Less Dense topside Denser F2 peak

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February 26th, 2002

10h

4. Profile analysis 108 109 1010 1011 1012 1013 0 100 200 300 400 500 600 700 800 Ne [e− m−3] h [km] Measured Ne Modelled Ne

Huge

difference for

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Conclusion

• Topside to be investigated

• CCIR maps to be investigated

– SA dependence

– Month dependence – UT dependence

4. Profile analysis

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General conclusion

• Benefit from collocated data

• NeQuick behaviour:

varying even at mid-latitudes

• Elements to investigate:

– solar activity parameter

– topside formulation

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Perspectives

• Ionosonde scaled characteristics

• Evolutions of NeQuick

• Other solar activity parameters

• Generalization:

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Framework

• PhD at University of Liège (Geomatics)

• Collaborations

– RMI (Brussels)

– ESA/ESTEC (TEC-EEP)

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Ionosphere