Experiment on long-term forecasting of geomagnetic activity based on nonlocal correlations

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Abstract

The experiment was performed on the use of advanced macroscopic nonlocal correlations to forecast slow random fluctuations of the Dst index of geomagnetic activity. The global maximum correlation of Dst with the signal of the electrode detector reaches 0.97, which is sufficient for the forecast, and its time shift corresponds to the advance of the detector signal relative to Dst by 329 days. The large magnitude of the time shift is due to the slow diffusion mechanism of entanglement swapping between the detector and the source. At the same time, the position of the global maximum of the correlation function coincides with the position of the global minimum of the entropy independence function, which confirms its undistorted by possible nonlinearity of the relationship and determines the optimal lead time of the forecast. Long series of test forecasts Dst have been calculated using data from a nonlocal correlation detector with a fixed lead time using three methods: current regression, current impulse transient response and current neural network. The accuracy of the forecasts is sufficient for all practical purposes.

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About the authors

S. M. Korotaev

Schmidt Institute of Physics of the Earth, RAS (IPE RAS)

Author for correspondence.
Email: korotaev@gemrc.ru

Geoelectromagnetic Research Centre (GEMRC)

Russian Federation, Moscow, Troitsk

V. O. Serdyuk

Schmidt Institute of Physics of the Earth, RAS (IPE RAS)

Email: korotaev@gemrc.ru

Geoelectromagnetic Research Centre (GEMRC)

Russian Federation, Moscow, Troitsk

I. V. Popova

Schmidt Institute of Physics of the Earth, RAS (IPE RAS)

Email: korotaev@gemrc.ru

Geoelectromagnetic Research Centre (GEMRC)

Russian Federation, Moscow, Troitsk

J. V. Gorohov

Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation, RAS IZMIRAN)

Email: korotaev@gemrc.ru
Russian Federation, Moscow, Troitsk

E. O. Kiktenko

Schmidt Institute of Physics of the Earth, RAS (IPE RAS)

Email: korotaev@gemrc.ru

Geoelectromagnetic Research Centre (GEMRC)

Russian Federation, Moscow, Troitsk

D. A. Orekhova

Schmidt Institute of Physics of the Earth, RAS (IPE RAS)

Email: korotaev@gemrc.ru

Geoelectromagnetic Research Centre (GEMRC)

Russian Federation, Moscow, Troitsk

References

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Supplementary files

Supplementary Files
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2. Fig. 1. Diagram of the detector device [Korotaev et al., 2019]: E - electrodes (the complex internal structure is not shown), the potential difference of which (U) is the detector signal; NaCl—electrolyte (3% aqueous solution); V—detector body (hard rubber); t1,t2.te - temperature sensors. The distance between the electrodes is 30 cm.

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3. Fig. 2. Correlation function r U and Dst and independence function τ - time shift Dst relative to U, days.

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4. Fig. 3. Demonstration of the possibility of forecasting by U by shifting the filtered series by the amount of advance of the global maximum correlation (329 days). The upper time axis corresponds to U, the lower one to Dst.

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5. Fig. 4. Forecast of Dst by the current regression method with a fixed lead time of 329 days (thin line) compared with the actual curve (thick line). The root mean square error of the forecast is 0.99 nT.

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6. Fig. 5. Forecast of Dst by the current impulse transient response method with a fixed lead time of 329 days (thin line) in comparison with the actual curve (thick line). The root mean square error of the forecast is 0.40 nT.

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7. Fig. 6. Forecast of Dst by the current neural network method with a fixed lead time of 329 days (thin line) in comparison with the actual curve (thick line). The root mean square error of the forecast is 0.29 nT.

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