Correspondence of variations of AE and Apo indices in 23–24 solar cycles

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Abstract

The auroral electrojet index AE is often used in forecasting models as a characteristic of a source of the disturbance propagation in the geosphere from the pole to middle and low latitudes. However, these data are no longer available digitally since January 2020. Instead of the AE−index, we suggest using the recently introduced 1 h Apo−index, given the close proximity of magnetometer networks for these indices at high latitudes and the availability of the Apo−index in real time. To this end their correlation is analyzed during 276 intense storms for 1995–2017. Storm profiles are constructed by method of superposed epoch with zero epoch time t0 = 0 taken at the threshold value of AE ≥ 1000 nT. A comparison is made of the storm profiles of AE(t), Apo(t), the interplanetary electric field E(t) and the solar wind speed Vsw(t) within 72 hours: 24 hours before the storm peak t0, and 48 hours after it. A good agreement is obtained between the sets AE(t) and Apo(t) with a correlation coefficient of 0.70. Comparison with the interplanetary parameters testifies on the correlation of AE(t) and Apo(t) with the electric field E(t) but absence of their coupling with the solar wind speed Vsw(t). A two−parametric formula is derived for dependence of the auroral electrojet index AE(t) on the interplanetary electric field E(t) and the geomagnetic Apo(t) index for the geomagnetic storm forecasting. In the absence of E(t) data, formulae for the dependence of AE(t) on Apo(t) is introduced for implementation in real time and the inverse dependence of Apo(t) on AE(t) for reconstruction of the 1 h Apo−index before 1995. Validation of the proposed models with data for 5 intense storms in 2018 has shown a close resemblance of the model with observation data of the AE−index with a high coefficient of determination R2 ranging from 0.62 to 0.81.

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About the authors

T. L. Gulyaeva

Pushkov Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation of Russian Academy of Sciences

Author for correspondence.
Email: gulyaeva@izmiran.ru
Russian Federation, Moscow, Troitsk

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Supplementary files

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2. Fig. 1. Magnetometer networks providing data for the production of AE and Apo indices.

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3. Fig. 2. Profiles of intense storms for 1995−2017, centered at the moment of the AE index peak: (a) AE(t) profiles; (b) Apo(t); (c) E(t); (d) Vsw(t). Individual profiles are black lines, median is white curve.

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4. Fig. 3. Regression dependencies between the AE and Apo indices: (a) dependence of AE on Apo; (b) dependence of Apo on AE.

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5. Fig. 4. Two-parameter dependence of the AE index storm profile on the E and Apo parameters.

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6. Fig. 5. Observational data and model calculations during the storm from March 17 to 19, 2018. (a) 1 − AE index observations; 2 − model calculation (2); 3 − model calculation (4); (b) electric field E observations; (c) Apo index observations.

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7. Fig. 6. Similar to Fig. 5 for the storm from August 25 to 27, 2018.

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