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Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition.

Kim RS, Moon YJ, Gopalswamy N, Park YD, Kim YH - Space Weather (2014)

Bottom Line: To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study.However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them.We then performed the two-step forecast.

View Article: PubMed Central - PubMed

Affiliation: Astronomy and Space Program Division, Korea Astronomy and Space Science Institute Daejeon, South Korea.

ABSTRACT

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (B z  ≤ -5 nT or E y  ≥ 3 mV/m for t≥ 2 h for moderate storms with minimum Dst less than -50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted.

No MeSH data available.


Related in: MedlinePlus

(left column) The relationship between the minimum Dst index and magnetic field strengths in the positive direction (open circles) and negative direction (filled circles). (right column) The relationship between the minimum Dst index and (top) duskward electric field, (middle) ion number density and flow pressure, and (bottom) solar wind speed and plasma temperature, respectively.
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fig02: (left column) The relationship between the minimum Dst index and magnetic field strengths in the positive direction (open circles) and negative direction (filled circles). (right column) The relationship between the minimum Dst index and (top) duskward electric field, (middle) ion number density and flow pressure, and (bottom) solar wind speed and plasma temperature, respectively.

Mentions: To select storm criteria of solar wind parameters, we examine their relationship with the minimum Dst index as shown in Figure 2. For the magnetic field strength, we consider all six components (positive Bx, By, Bz and negative Bx, By, Bz) to see which direction of solar wind magnetic field is more related to the storm intensity. In Figure 2 (left column), the open circles represent the maximum values of magnetic field strength in the positive direction and filled circles are the maximum values in the negative direction. It is clearly seen that the strong storms have strong magnetic fields, and we find that the negative Bz has the best relationship with the minimum Dst with the highest correlation coefficient of 0.84 among six magnetic field components. As shown in the right column of the figure, IP duskward electric field (Ey) also has good correlation with the minimum Dst (cc = −0.85). However, other parameters such as the ion number density (Ni) and the plasma temperature (T) do not show strong relationships. These results are consistent with other research [Yermolaev et al., 2007; Echer et al., 2008; Ji et al., 2010].


Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition.

Kim RS, Moon YJ, Gopalswamy N, Park YD, Kim YH - Space Weather (2014)

(left column) The relationship between the minimum Dst index and magnetic field strengths in the positive direction (open circles) and negative direction (filled circles). (right column) The relationship between the minimum Dst index and (top) duskward electric field, (middle) ion number density and flow pressure, and (bottom) solar wind speed and plasma temperature, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508932&req=5

fig02: (left column) The relationship between the minimum Dst index and magnetic field strengths in the positive direction (open circles) and negative direction (filled circles). (right column) The relationship between the minimum Dst index and (top) duskward electric field, (middle) ion number density and flow pressure, and (bottom) solar wind speed and plasma temperature, respectively.
Mentions: To select storm criteria of solar wind parameters, we examine their relationship with the minimum Dst index as shown in Figure 2. For the magnetic field strength, we consider all six components (positive Bx, By, Bz and negative Bx, By, Bz) to see which direction of solar wind magnetic field is more related to the storm intensity. In Figure 2 (left column), the open circles represent the maximum values of magnetic field strength in the positive direction and filled circles are the maximum values in the negative direction. It is clearly seen that the strong storms have strong magnetic fields, and we find that the negative Bz has the best relationship with the minimum Dst with the highest correlation coefficient of 0.84 among six magnetic field components. As shown in the right column of the figure, IP duskward electric field (Ey) also has good correlation with the minimum Dst (cc = −0.85). However, other parameters such as the ion number density (Ni) and the plasma temperature (T) do not show strong relationships. These results are consistent with other research [Yermolaev et al., 2007; Echer et al., 2008; Ji et al., 2010].

Bottom Line: To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study.However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them.We then performed the two-step forecast.

View Article: PubMed Central - PubMed

Affiliation: Astronomy and Space Program Division, Korea Astronomy and Space Science Institute Daejeon, South Korea.

ABSTRACT

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (B z  ≤ -5 nT or E y  ≥ 3 mV/m for t≥ 2 h for moderate storms with minimum Dst less than -50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted.

No MeSH data available.


Related in: MedlinePlus