Probabilistic Forecasting of the Dst Index

Abstract

The Dst index can be predicted by an autoregressive moving average filter that transforms the solar wind electric field and dynamic pressure into changes in the index. Integration of these changes gives Dst. The maximum lead time possible is less than 60 minutes. Longer lead times are probably unobtainable due to the stochastic nature of IMF Bz. In this paper we use photospheric observations of the solar magnetic field to predict Dst. Our technique uses the Wang-Sheeley-Arge (W-S-A) model to forecast the time variations of solar wind speed, IMF polarity, and IMF strength at Earth four days in advance. Since the waveform of Bz is incalculable from solar observations we make use of air mass climatology. In this technique the cumulative probability distribution is determined as a function of time relative to a stream interface. During the declining phase of the solar cycle persistent coronal holes create high speed streams. The interface between these streams and slower speed solar wind ahead provides a reference time that can be used to organize the cumulative probability distributions determined from historic data (climatology). We then use the predicted arrival of an interface and the associated cumulative distributions to predict the probability that |Dst| will fall within a range of values. This technique works best for small to moderate storms occurring during the declining phase of the solar cycle. CMEs are not predictable by this model hence we do not expect this approach to work as well at solar maximum.

Flux enhancement of radiation belt electrons during geomagnetic storms driven by coronal mass ejections and corotating interaction regions

“…Note also that, since the strength of CIR-driven storms is usually weak to moderate [Tsurutani et al, 1995], many large flux events are associated with weaker storms with Dst > À100 nT. The results obtained in this paper for CIRassociated storms, however, can be naturally extended to the weaker CIR-related storms, considering the fact that our results are very similar as those of McPherron et al [2005]. Superposing all of the CIR events in 1995 about the stream interfaces, McPherron et al [2005] showed that the flux recovers to the prestorm level 1 day after the interface arrival, and enhances about one order of magnitude larger than the prestorm level in a few days.…”

“…A slow stream occasionally associated with a heliospheric current sheet [Smith, 2001] is compressed ahead of the stream interface, while a highspeed stream with large-amplitude Alfvé nic fluctuations originating from a solar coronal hole follows the stream interface [Tsurutani et al, 2006]. A gradual density increase with the westward flow deflection exists about a half day before the arrival of the stream interface [McPherron et al, 2005]. It is worthwhile noting here that, as shown in this picture, a CME-related disturbance is nearly a radial profile of the solar wind structure, while a CIR-related disturbance is nearly an azimuthal profile.…”

Probabilistic space weather forecast of the relativistic electron flux enhancement at geosynchronous orbit

“…Note that the probabilistic forecast of Kataoka and Miyoshi (2006) is a similar concept of daily and weekly probability of the meteorological precipitation forecast. McPherron and Siscoe (2004) and McPherron et al (2005) proposed similar probability forecast for the prediction of the Dst index.…”

Probabilistic forecasting of the disturbance storm time index: An autoregressive Gaussian process approach

“…Although much research has been done on prediction of the D s t index, much less has been done on probabilistic forecasting of D s t . One such work described in McPherron et al [] involves identification of high speed solar wind streams using the WSA model [see Wang and Sheeley , ], using predictions of high speed streams to construct ensembles of D s t trajectories which yield the quartiles of D s t time series.…”