Probabilistic Solar Wind and Geomagnetic Forecasting Using an Analogue Ensemble or "Similar Day" Approach | JoVE Visualize

Area of Science:

Space weather and solar physics
Atmospheric and space physics
Geomagnetism

Background:

Accurate near-Earth solar-wind forecasting is crucial for space-weather prediction and mitigation.
Current numerical magnetohydrodynamic models show skill in long-term forecasting but lack accuracy for short-term (hours to days) predictions.
The analogue ensemble (AnEn) method, adapted from atmospheric weather forecasting, offers a probabilistic approach to predict future conditions based on past analogous data.

Purpose of the Study:

To investigate the efficacy of the analogue ensemble (AnEn) method for short-term solar-wind and geomagnetic condition forecasting.
To determine optimal parameters and observation windows for AnEn-based solar-wind forecasts.
To assess the AnEn's capability in predicting geomagnetic indices Dst and Kp.

Main Methods:

The study employed the analogue ensemble (AnEn) approach, identifying past periods with conditions similar to the present to forecast future solar-wind properties.
Forecast accuracy was evaluated by varying input parameters (solar-wind speed, density, in-ecliptic magnetic field components) and the lookback window (6-12 hours).
The AnEn method was also applied to forecast geomagnetic indices Dst and Kp.

Main Results:

AnEn forecasts for solar-wind speed improved when considering both speed and density. Out-of-ecliptic magnetic field forecasts benefited from including in-ecliptic components.
Optimal forecasts were generally achieved using the preceding 6-12 hours of observations.
The AnEn provided valuable probabilistic forecasts for solar-wind speed, density, and in-ecliptic magnetic field up to four days, and for Dst and Kp indices up to four days. Forecasts for the out-of-ecliptic magnetic field were valuable for six to seven hours.

Conclusions:

The analogue ensemble (AnEn) method offers a valuable probabilistic forecasting tool for near-Earth solar-wind conditions and geomagnetic indices, outperforming other methods for short-term predictions.
The AnEn's effectiveness can be enhanced by carefully selecting input parameters and observation windows.
Further improvements to the AnEn method are anticipated for more accurate space-weather forecasting.