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An assessment of the NRLMSISE-00 density thermosphere description in presence of space weather events C. Lathuillère and M. Menvielle The data and the method Statistical analysis for year 2004 8 larger events of 2004 • Conclusion

The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

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An assessment of the NRLMSISE-00 density thermosphere description in presence of space weather events C. Lathuillère and M. Menvielle. The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion. STAR/CHAMP densities – May 3 rd , 2003. to the sun. - PowerPoint PPT Presentation

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Page 1: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

An assessment of the NRLMSISE-00 density thermosphere description in presence of

space weather events

C. Lathuillère and M. Menvielle

• The data and the method• Statistical analysis for year 2004• 8 larger events of 2004• Conclusion

Page 2: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

STAR/CHAMP densities – May 3rd, 2003

Den

sitie

s (1

0-15

g.cm

-3)

The datato thesun

daytime and night time orbit sections are considered

separately

… between -50° and 50° in latitude, with a 1° sampling

rate with respect to the latitude

STAR/CHAMP densities – May 3rd, 2003

STAR atmosphere density along CHAMP trajectory at about 400 km altitude

Den

sitie

s (1

0-15

g.cm

-3) ~5:30 pm LT at equator

~5:30 am LT at equator

Inclination:87°

Page 3: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

TOTAL MASS DENSITY at the satellite altitude (10-15 g/cm3) 10 LT 22 LT

The method: Running SVD analysis over 15 consecutive orbits (about 1 day)

The projection on the first component accounts for large scale variations: spatial variations are captured by the first principal component, and time variations are captured by the associated projection coefficient: C1.

Residuals account for smaller scales, as tides and gravity waves

Page 4: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

Comparison with NRLMSISE-00 model

NRLMSIS:with MgII proxy and ap

CHAMP data

Normalized coefficient:

C1 CHAMP / C1 NRLMSIS_quietC1 NRLMSIS/ C1 NRLMSIS_quiet

NRLMSIS_quiet:with MgII proxy and Ap=4

MgII proxy: The composite MgII index (Viereck et al, 2004) is used as a proxy for solar EUV instead of F10.7

Page 5: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

NRLMSIS_quiet is used as a reference, that accounts for LT, seasonal variations, solar activity…

Page 6: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

- Statistical analysis: binning of normalized C1 coefficients as a function of ap

- Analysis of the height larger events

Page 7: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

Day time Night time

x : CHAMP data

x : NRLMSIS model

correlation coefficient between CHAMP data and ap

ap index ap index

Den

sity

per

turb

atio

n

Binning is done using the value of ap from the previous 3 hour interval

Page 8: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

x Day time

+ Night time

Page 9: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

Linear fit

y =1.9 x – 0.9

x Day time

+ Night time

Page 10: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

x Day time

+ Night time

Day and Night time with ap <100

Page 11: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

x Day time

+ Night time

Day and Night with ap <100

Quadratic fit

y =1.92 x2 – 3 x + 2.14

Page 12: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

Density perturbation: CHAMP data and NRLMSIS model

Day of 2004

ap magnetic index

Day time Night time

- the relative density increase is greatly underestimated by the model

- the model seems to correctly represent the shape of the perturbation

3 days

Page 13: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

The perturbations appear later in the data than in the model and this timing discrepancy is slightly larger during night ( 3-4.5 hours) than during day time.

Density perturbation: CHAMP data and NRLMSIS model normalized to the amplitude of the data perturbation

Normalization factor mean value = 2.3

3 days

Page 14: The data and the method Statistical analysis for year 2004 8 larger events of 2004 Conclusion

Conclusion

• NRLMSISE-00 correctly estimates the main features of the thermosphere density response to geomagnetic activity:

- the morphology of UT variations - the larger relative increase during night than during day time But it underestimates :

• the amplitude of the density response (by about a factor 2)• and its phase lag (up to 4.5 hours)

Altitudes about 400km. Latitudes between 50S and 50N