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Intra-annual Variations of the Thermospheric Density at 400 Km Altitude from 1996 to 2006

Advances in space research(2014)

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Abstract
We investigate the intra-annual variations of globally averaged thermospheric density at 400km altitude from 1996 to 2006 by using Artificial Neural Network Method (ANNM). The results indicate that thermospheric density is governed by solar activity, and the absolute error of our model is 13.67%, less than NRLMSISE-00 model. Fourier representation can catch the intra-annual variations more accurately than NRLMSISE-00 model and JB2008 model especially during 2002. We find that the Autumn maximum is slightly greater than Spring maximum during solar minimum, while the reverse is correct during solar maximum. There is a strong linear relation between solar activity and the amplitude of annual/semiannual variations, and the correlation coefficients are 0.9534 and 0.9424, respectively. Moreover, the amplitude ratio of the annual to semiannual variation is about 1.3 averaged, and changes in different years, but it has little relation with solar activity. Besides that, the amplitude of annual variation is larger than semiannual variation during 1996 and 2006 except 1998 and 2000. The relative error of NRLMSISE-00 model is 14.95%, decreasing to 12.49% after revising, and the correlation coefficients between this empirical model and its improved results and the observation are 0.8185 and 0.9210, respectively. Finally, we suggest the revised version of MSIS series of model should use the Fourier representation to express the intra-annual variations.
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Key words
ANN method,Thermospheric density,Intra-annual variation,NRLMSISE-00 model
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