Using the IRI, the MAGIC model, and the co-located ground-based GPS receivers to study ionospheric solar eclipse and storm signatures on July 22, 2009
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The longest total solar eclipse in the 21st century occurred in Southeast Asia on 22 July 2009 from 00:55 to 04:15 UT, and was accompanied by a moderate magnetic storm starting at 03:00 UT with a Dst reduction of −78 nT at 07:00 UT. In this study, we use the ionospheric reference model IRI, the data assimilation model MAGIC, and ground-based GPS receivers to simulate and examine the ionospheric solar eclipse and geomagnetic storm signatures in Taiwan and Japan. Cross-comparisons between the two model results and observations show that IRI fails to simulate the two signatures while MAGIC partially reproduces the storm features. It is essential to include ground-based GPS measurements to improve the IRI performance.
Key wordsSolar eclipse geomagnetic storm IRI GPS TEC MAGIC
The ionosphere can be affected by a variety of disturbances, including solar flares, coronal mass ejections (CMEs), geomagnetic storms, solar eclipses, etc. Ionospheric eclipse observations make a worthwhile contribution to study transient properties due to decreasing in the ionizing radiation from the Sun. Scientists have been using the total electron content (TEC) derived from ground-based receivers of the global positioning system (GPS) to monitor the source-response relation between the ambient rates of production, chemical loss, and motion of ionization (see papers listed in Afraimovich et al., 1998; Tsai and Liu, 1999; Jakowski et al., 2002; Le et al., 2009).
On the other hand, geomagnetic storms are powerful sources that disturb the ionosphere. During geomagnetic storms, the ionosphere has often been observed to deviate from its quiet time patterns (Prölss, 1987, 1995; Fesen et al., 1989; Fejer and Scherliess, 1995; Fuller-Rowell et al., 1998, 2002; Buonsanto, 1999; Liu et al., 1999; Kil et al., 2003; Lin et al., 2005, 2007). These storm-generated disturbances in electric field, thermospheric neutral wind, and neutral composition affect the mid- and low-latitude ionosphere significantly during the different phases of the magnetic storm. The ionospheric electron density shows either increase or decrease due to changes of the ionospheric drivers depending on storms, conditions and phases.
To simultaneously observe a larger area of the ionosphere responding to solar eclipses and geomagnetic storms, the TEC derived from a network of ground-based GPS receivers is ideal to be employed (Tsai and Liu, 1999). On the other hand, the International Reference Ionosphere (IRI) project was initiated by the Committee on Space Research (COSPAR) and by the International Union of Radio Science (URSI) in the late sixties with the goal of establishing an international standard for the specification of ionospheric parameters based on all worldwide available data from ground-based as well as satellite observations (Bilitza and Reinisch, 2008). The prime function of IRI is to give a general description of the ionosphere as part of the terrestrial environment. To have a better representation of the ionosphere during the storm periods, an empirical ionospheric correction model STORM was designed and included in IRI-2000 and IRI-2007 to capture the changes in F region electron density during geomagnetic storms (Araujo-Pradere and Fuller-Rowell, 2002; Araujo-Pradere et al., 2002). The model is driven by the previous 33 hours of ap, and the output is used to scale the quiet time F region critical frequency (foF2) to account for increases or decreases in electron density resulting from a storm.
Based on the vertical density profiles from the IRI-95 model, the MAGIC system is developed, which uses ground-based GPS observations to reproduce a four-dimensional model of the electron density in the ionosphere (Araujo-Pradere et al., 2007; Minter et al., 2007). The MAGIC model uses a set of empirical orthogonal functions (EOF) with a Kalman filter to characterize the vertical variation in electron density through the ionosphere.
The solar eclipse of 22 July 2009 (Espennak and Anderson, 2008) is the longest one during the 21st century, not to be surpassed until June 2132. It lasts a maximum of 6 minutes and 39 seconds off the coast of Southeast Asia, through northern Maldives, central China, and the Pacific Ocean. Coincidently, a moderate storm occurs at 03:00 UT during the solar eclipse period. In this study, we use IRI-2007, MAGIC, and the TEC of ground-based GPS receivers to observe ionospheric solar eclipse and magnetic storm effects in the West Pacific region during 22–26 July 2009. IRI simulates the average ionospheric plasma density, while ground-based GPS measurements monitor ionospheric TEC variations. These two provide references to examine the MAGIC performance. Note that this is for the first time MAGIC being used to simulate the ionosphere response to a solar eclipse.
2. Observation and Simulation
The IRI-2007 simulation covers 15–45°N, 115–145°E with a spatial resolution of 1° in both latitude and longitude and a time resolution of 1 hour. To simulate features of the moderate storm occuring at 03:00 UT on the solar eclipse day, the STORM model of the IRI-2007 is turn on and given with the latest ap index. For cross comparisons, MAGIC assimilates the data recorded by 213 GPS receiver stations in Taiwan and Japan within the same IRI simulation region. The MAGIC model computes the TEC and the electron density with 1° latitude by 1° longitude, and 15 km altitude grid every 2 minutes. Meanwhile, based on Liu et al. (1996), the TECs over 8 GPS stations are derived to monitor the ionospheric solar eclipse and storm signatures.
3. Result and Interpretation
4. Discussion and Conclusion
To identify the eclipse and storm signatures, the standard deviation at each station during the observation period, 15–26 July 2009 is computed. It is found that the standard deviation is about 2–3 TECu. Figure 3 shows that the eclipse signature can be detected, except those three low obscuration stations, STK2 (43.5%), BJFS (74.1%), PIMO (49.8%) where the deviations are less than 2 standard deviations of 4–6 TECu. This might partially explain why MAGIC fails to reproduce the eclipse signature at STK2 (obscuration 43.5%). On the other hand, the storm signatures can be detected by all the 8 stations, because the deviations are greater than 2 standard deviations of 4–6 TECu. However, MAGIC still fails to reproduce the positive storm signature of NmF2 at STK2 and BJFS.
IRI fails to simulate the eclipse and storm features in the TEC, NmF2 and hmF2 during the 22 July 2009 event. However, MAGIC (based on IRI-95) with the ground-based GPS measurements successfully simulates the general eclipse and storm features in the TEC and NmF2. MAGIC fails to reproduce the TEC/NmF2 storm signatures at STK2 and BJFS which are located in high mid-latitudes and near the northern boundary of the assimilation region (Fig. 1). It might also be the boundary effect causing the failure. Meanwhile, MAGIC successfully simulates the TEC eclipse signature but not the NmF2, which might result from the EOFs being improperly used. Moreover, due to the same reason MAGIC fails to reproduce the hmF2 eclipse and storm signatures.
Figure 7 reveals that no clear latitudinal effect can be found in the IRI TEC during the two storm phases, which agrees with the results in Figs. 2 and 3. It is found that the MAGIC model and the observation yield the greatest value of the TEC maximum (TEC minimum) at about 15°N magnetic, where is near the EIA crest, during the positive (negative) storm phase. These suggest that the most prominent storm signatures occur in the EIA region.
The results show that MAGIC incorporating with IRI and ground-based GPS TEC observations could correctly reproduce the TEC (the TEC and NmF2) during the eclipse (storm) period. Therefore, ground-based TEC measurements might be worthwhile to be included in the IRI model to have better simulations on ionospheric solar eclipse and storm signatures.
C. Y. Lin wish to thank K. I. Oyama at National Cheng Kung University and S. Watanabe at Hokkaido University for inviting to attend IRI2009 Workshop Kagoshima University, Japan, November 2–7, 2009. This work is partially supported by National Science Council in Taiwan under NSC 98-2111-M-008-008-MY3.
- Araujo-Pradere, E. A. and T. J. Fuller-Rowell, STORM: An empirical storm-time ionospheric correction model, 2, Validation, Radio Sci., 37, doi:10.1029/2002RS002620, 2002.Google Scholar
- Araujo-Pradere, E. A., T. J. Fuller-Rowell, and M. V. Codrescu, STORM: An empirical storm-time ionospheric correction model, 1, Model description, Radio Sci., 37, doi:10.1029/2001RS002467, 2002.Google Scholar
- Espennak, F. and J. Anderson, Total Solar Eclipse of 2009 July 22, NASA/TP-2008-214169, 2008 (available on the website http://eclipse.gsfc.nasa.gov/SEpubs/20090722/rp.html).
- Fuller-Rowell, T. J., M. V. Codrescu, R. G. Roble, and A. D. Richmond, How does the thermosphere and ionosphere react to a geomagnetic storm?, in Magnetic Storms, edited by B. T. Tsurutani et al., pp. 203–225, AGU Monograph 98, Washington, D.C., 1998.Google Scholar
- Leick, A., GPS Satellite Surveying, 560 pp., John Wiley, New York, 1995.Google Scholar
- Lin, C. H., A. D. Richmond, R. A. Heelis, G. J. Bailey, G. Lu, J. Y. Liu, H. C. Yeh, and S.-Y. Su, Theoretical study of the low- and midlatitude ionospheric electron density enhancement during the October 2003 superstorm: Relative importance of the neutral wind and the electric field, J. Geophys. Res., 110, A12312, doi:10.1029/2005JA011304, 2005.CrossRefGoogle Scholar
- Liu, J. Y., H. F. Tsai, and T. K. Jung, Total electron content obtained by using the global positioning system, Terr. Atmos. Ocean. Sci., 7, 107–117, 1996.Google Scholar
- Prölss, G. W., Ionospheric F-region storms, in Handbook of Atmospheric Electrodynamics, edited by H. Volland, CRC Press, Boca Raton, Fla., 1995.Google Scholar
- Sover, O. J. and J. L. Fanselow, Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987, Jet Propulsion Lab. Publ., 83–39, Rev. 3, 1–60, 1987.Google Scholar