Time-Dependence (structuring) of the Alpha-to-Proton Ratio (A He ) in the Solar Wind at 1 AU: Initial results, Implications, and Speculations Harlan E.

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Presentation transcript:

Time-Dependence (structuring) of the Alpha-to-Proton Ratio (A He ) in the Solar Wind at 1 AU: Initial results, Implications, and Speculations Harlan E. Spence (BU) and Justin C. Kasper (MIT  SAO)

Outline Background: Alpha abundance ratio variability on long time scales (solar cycle, solar rotation) Motivation: Small-scale solar wind density structuring Alpha/proton data set Short-term A He variations (hours) Case study Statistical properties of variability Implications of variability as tracer of coronal processes and dynamics

Background: Long-Term Variability Ogilvie & Hirshberg (1974) and Feldman et al. (1978) reported on A He on solar cycle time scales Aellig et al (2001) demonstrated that A He is a strong function of solar cycle, especially for solar wind speeds below 500 km/s Kasper et al. (2007) demonstrated a clear 6-month variation for slow speeds dependent on latitude When gradient effects are removed at solar minimum, a fascinating linear trend emerges between wind speed and A He

Motivation: Solar wind density structuring at 1AU Kepko and Spence (2003) studied magnetospheric response to quasi- periodic (~3-hr) train of convected proton density structures in solar wind at 1AU (see their Figure 1 to right) Characteristic size scales of these “pressure-balanced” structures (in the direction of the solar wind flow) is of order 10’s to ~100 Re (~60 to ~600 Mm) We explore variations of A He on these shorter time scales, following on the work by Kepko and Spence (2003) and recent work by N. Viall, combined with ideas developed recently by Kasper et al. (2007)

Alpha/Proton Data Set Wind SWE Faraday Cups measure reduced distribution functions of solar wind hydrogen and helium along 40 angles every 92 seconds (Oglivie, 95) Derive bulk velocities, thermal speeds and temperature anisotropies, and number densities for hydrogen and helium by fitting the measurements with convected bi-Maxwellian distribution functions We use the bi-Maxwellian hydrogen and helium data product available from the National Space Science Data Center We avoid data believed to be deleteriously affected by unusual non-Maxwellian distribution functions, or by the presence of interplanetary shocks.

Case Study: Small-scale Structure in Solar Wind A He Solar wind speed (slow and nearly constant), proton density, A He, and the IMF orientation for the interval containing the large proton density variations Red curve is the typical A He as a function of ob- served speed as predicted by Kasper et al.(07) Alpha-rich struc- ture accompan- ied by IMF rota- tions

A He Varability: Statistical Properties Survey one year of Wind SWE data and plot according to variability level of solar wind parameter (p + and a density) During periods of most levels of variability in helium abundance (left plot) there is an extremely high correlation between alpha density and A He (i.e., the alpha variation drives the A He variations) During periods of highest variability in proton abundance there is only a weak anti-correlation between proton density and A He (center plot) and an even weaker correlation between proton density and helium density (right plot) da vs. CC( da, d A He ) d p + vs. CC( d p +, d A He ) d p + vs. CC( d p +, da ) Correlated Uncorrelated Anticorrelated

Summary and Implications Statistically-significant A He variations are seen clearly in conjunction with the class of convected solar wind density variations with size scales of 10’s to 100’s Mm’s and accompanied by magnetic field rotations Variability is driven by inherent variability in the alphas – this makes it clear that these structures are of solar coronal origin Size scales “map” back to coronal loop scales where alpha ratios could be modulated by processes such as interchange reconnection (loop residence time determines A He through differential settling of alphas versus protons) Charge-state variations would greatly enhance this analysis, though the fast time variability (tens of minutes) of small- scale convected structures pushes the limits of detection