Improvement in the prediction of solar wind conditions using near‐real time solar magnetic field updates

Arge, C. N.; Pizzo, V. J.

doi:10.1029/1999ja000262

Cited by 729 publications

(750 citation statements)

References 21 publications

Supporting

Mentioning

733

Contrasting

Unclassified

Order By: Relevance

“…Also this would have the advantage of using features in the solar field that are seen at all observatories rather than just one. Second it is possible to improve the quality of the predicted speed on the solar source surface using a more complex model that includes location of the sub-Earth point relative to a coronal hole as well as the flux tube expansion factor [Arge and Pizzo, 2000]. It is also likely that the kinematic model for the propagation and interaction of high speed streams can be improved by parameterizing the model and then optimizing these parameters with historical data.…”

Section: Discussionmentioning

confidence: 99%

“…The velocity of solar wind emitted from the sub-Earth point on the Sun is inversely proportional to this factor [Wang and Sheeley, 1990]. This wind is propagated to the Earth taking into account compression of the slower wind that precedes fast streams [Arge and Pizzo, 2000]. Predictions of the speed at 1 AU are typically made 3-4 days in advance of arrival of the wind at the Earth.…”

Section: Discussionmentioning

confidence: 99%

“…The second is a method for identifying the stream interface from the predicted velocity profile. The technique for predicting the solar wind velocity at 1 AU 2-4 days in advance has been described elsewhere [Arge and Pizzo, 2000;Wang and Sheeley, 1990] and because of space limitations we do not repeat this here. For our purposes we assume that a real time procedure generates the solar wind velocity time series about three days in advance.…”

Section: A Stream Interface Detectormentioning

confidence: 99%

“…The technique utilizes observations of the photospheric magnetic field of the Sun to predict the solar wind velocity on a source surface around the Sun [Wang and Sheeley, 1990]. This velocity is then propagated to the Earth [Arge and Pizzo, 2000] and processed to detect stream interfaces. Knowing the time of arrival of an interface, probability distributions for Dst are used to forecast the expected level of activity.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Probabilistic Forecasting of the Dst Index

McPherron

Siscoe

Crooker

et al. 2013

The Inner Magnetosphere: Physics and Modeling

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: A Stream Interface Detectormentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Probabilistic Forecasting of the Dst Index

McPherron

Siscoe

Crooker

et al. 2013

The Inner Magnetosphere: Physics and Modeling

View full text Add to dashboard Cite

show abstract

“…Because it has different compositional properties and shows greater temporal and spatial variability, its sources are often assumed to lie outside the coronal holes that produce highspeed wind, with closed field regions being a favored choice (see Zurbuchen 2007, and references therein). However, an alternative viewpoint is that both high-and low-speed winds come from coronal holes (defined as open field regions), and that it is the rate of flux-tube expansion (Levine et al 1977;Wang & Sheeley 1990;Arge & Pizzo 2000;Poduval & Zhao 2004;Whang et al 2005) and/or the location of the coronal heating (Leer & Holzer 1980;Hammer 1982;Hollweg 1986;Withbroe 1988;Wang 1993Wang , 1994aSandbaek et al 1994;Cranmer et al 2007) that controls the wind speed at 1 AU. Thus, the slow wind tends to be highly variable because it emanates from just inside the boundaries of large coronal holes and from the small, rapidly evolving holes that form near active regions at sunspot maximum.…”

Section: Introductionmentioning

confidence: 99%

Time-dependent hydrodynamical simulations of slow solar wind, coronal inflows, and polar plumes

Pinto¹,

Grappin²,

Wang³

et al. 2009

A&A

View full text Add to dashboard Cite

Aims. We explore the effects of varying the areal expansion rate and coronal heating function on the solar wind flow. Methods. We use a one-dimensional, time-dependent hydrodynamical code. The computational domain extends from near the photosphere, where nonreflecting boundary conditions are applied, to 30 R , and includes a transition region where heat conduction and radiative losses dominate. Results. We confirm that the observed inverse relationship between asymptotic wind speed and expansion factor is obtained if the coronal heating rate is a function of the local magnetic field strength. We show that inflows can be generated by suddenly increasing the rate of flux-tube expansion and suggest that this process may be involved in the closing-down of flux at coronal hole boundaries. We also simulate the formation and decay of a polar plume, by including an additional, time-dependent heating source near the base of the flux tube.

show abstract

Type II solar radio bursts predicted by 3‐D MHD CME and kinetic radio emission simulations

Schmidt

Cairns

2014

JGR Space Physics

View full text Add to dashboard Cite

Citation:Schmidt, J. M., and I. H. Cairns (2014), Type II solar radio bursts predicted by 3-D MHD CME and kinetic radio emission simulations, J. Geophys. Res. Space Physics, 119, 69-87, doi:10.1002 Abstract Impending space weather events at Earth are often signaled by type II solar radio bursts.These bursts are generated upstream of shock waves driven by coronal mass ejections (CMEs) that move away from the Sun. We combine elaborate three-dimensional (3-D) magnetohydrodynamic predictions of realistic CMEs near the Sun with a recent analytic kinetic radiation theory in order to simulate two type II bursts. Magnetograms of the Sun are used to reconstruct initial solar magnetic and active region fields for the modeling. STEREO spacecraft data are used to dimension the flux rope of the initial CME, launched into an empirical data-driven corona and solar wind. We demonstrate impressive accuracy in time, frequency, and intensity for the two type II bursts observed by the Wind spacecraft on 15 February 2011 and 7 March 2012. Propagation of the simulated CME-driven shocks through coronal plasmas containing preexisting density and magnetic field structures that stem from the coronal setup and CME initiation closely reproduce the isolated islands of type II emission observed. These islands form because of a competition between the growth of the radio source due to spherical expansion and a fragmentation of the radio source due to increasingly radial fields in the nose region of the shock and interactions with streamers in the flank regions of the shock. Our study provides strong support for this theory for type II bursts and implies that the physical processes involved are understood. It also supports a near-term capability to predict and track these events for space weather predictions.

show abstract

Improvement in the prediction of solar wind conditions using near‐real time solar magnetic field updates

Cited by 729 publications

References 21 publications

Probabilistic Forecasting of the Dst Index

Probabilistic Forecasting of the Dst Index

Time-dependent hydrodynamical simulations of slow solar wind, coronal inflows, and polar plumes

Type II solar radio bursts predicted by 3‐D MHD CME and kinetic radio emission simulations

Contact Info

Product

Resources

About