Empirical Testing of Solar Coronal and Solar Wind Models
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1 Empirical Testing of Solar Coronal and Solar Wind Models Lauren Woolsey University of Maryland - College Park (2011) Mentor: Dr. Leonard Strachan
2 Introduction What is the Solar Wind? * Outflow of particles discovered theoretically in 1958 and experimentally in * Two regimes of solar wind Coronal Holes and Streamer belts? * Coronal Holes have open field lines, source of fast solar wind. * Non-thermal heating may be significant factor in wind generation. Models can help determine mechanisms. Research Goal: * Use the thermodynamic MAS model output to compare synthesized emission line profiles to those from UVCS observations. * In this way, we hope to verify if the processes used in the model correctly describe the corona and solar wind. Image: TSE1991/image/TSE91-4cmp1w.JPG
3 Introduction (continued) Experimental Approach * Two main types of science activity: theory and experiment * By comparing models with observations, we can: a) help to constrain parameters used in theoretical models b) propose new observations to verify model predictions * Forward modeling allows for comparison of model with observation. Model parameters are converted into observables. * Role of UV spectroscopic observations: Line-of-sight profiles provide estimates for plasma parameters such as densities, temperatures, and outflow speeds, which allow energetics to be constrained. Self-consistent coronal/solar wind models * The model only takes inputs at the base of the corona * A change in the magnetic field will alter the plasma parameters, which then change the field.
4 SOHO: Our Data Source * UVCS (Ultraviolet Coronagraph Spectrometer) ~Instrument on SOlar and Heliospheric Observatory ~Spectral lines include H Lyα and O VI 1032 & 1037 Å LEFT: RIGHT:
5 SOHO: UVCS Synoptic Data * Exposures at different heights for Lyα and OVI channels Slit has 360 rows of 7 pixels, which provides 42 length. For Lyα (1216 Å) Observations: Spectral Resolution is 0.23 Å Spatial Resolution range is 12 x x 24 Hard stop at 270 At low heights, synoptic fields of view overlap for full coverage; higher, there are gaps in the data. For model comparisons, UVCS data were interpolated to make a denser grid.
6 SOHO: Data Analysis * Data Analysis Software (DAS) v.40 calibrates raw UVCS data into physical units * Gaussian fits to the data determine total intensities and 1/e widths DATA MAP At left, Quick Look image from DAS40. At Right: H Ly α Below: O VI lines
7 MAS: Modeling the Corona * The model tested is an MHD model of the Corona named Magnetohydrodynamics Around a Sphere (MAS). * Developers: J. Linker, Z. Mikić, R. Lionello, P. Riley, N. Arge, and D. Odstrcil * One of the more complex solar wind models available, but it is only a one-fluid model (not physical for a plasma) * Solves MHD equations for steady state or dynamical solutions
8 n0 = 2 x 1012 cm-3 Relaxation to Steady State T0 = 20,000 K From the B-field Temperature NSO at Kitt Peak and radiation loss term Hch= Hexp+ HQS+ HAR Q(t) from Athay (1986) SOLAR WIND PARAMETERS: 1 20 solar radii
9 MAS: 3D Grid to 1D Line * For each solar rotation, the model returns 3D arrays of data for V (shown), Ne, Te, and B, which we plot at different radii, latitudes, and longitudes. * UVCS integrates along a specified line of sight (LOS), model must match. * Defining a LOS: Polar Angle, Height, Endpoints * Once the model data is defined along a line of sight, spectral profiles produced with the model plasma parameters can be compared with the UVCS observed profiles.
10 Compare: CORPRO * CORPRO computes a LOS-integrated spectral profile I(λ) At each LOS point, calculate emissivity (ne, v, Te, Tp): The total intensity is a sum of these emissivities 1/e width is fitted directly from integrated profile * Profiles can be plotted to get visual comparison * Model provides a single value for T, we must determine its components
11 Case 1: Assume Tmodel = Te * Solve Tp by matching Imodel = Iobs * Electron temperature controls ionization fraction N(P) term in total intensity * Proton Temperature is a kinetic temperature. It controls the 1/e width. However, Tp can also affect total intensity through Doppler dimming. * Tp is determined by adjusting the parameter until the modeled intensity matches observed intensity (within data uncertainty) * 1σ observational error bars may be smaller than symbols. No model error was provided.
12 Case 1: Sample Lyα profiles Streamer at 2.5 Rsun Coronal Hole at 2.5 Rsun
13 Case 2: Assume Tmodel = Tavg Tavg = ½(Te + Tp) Table: Best α value where Imod = Iobs Height (Rsun) Value for α Te = α Tavg Tp = (2 α) Tavg / / (2.0) +/- 0.01
14 Case 2: Results for CH * For a fixed α, vnt can be determined using the model for vnt vs. r at right and B, n, and v parameters from MAS model to match line widths. * Non-thermal velocities: 89.8 km/s at 1.7 Rsun 90.3 km/s at 2.0 Rsun Left: Coronal 1.7 Rsun; 2.0 Rsun Landi & Cranmer (2009)
15 Summary of Results * STREAMER Generally, the equatorial region (the slow-wind regime) is well-described by the MAS model when using case 1 (Tmod = Te). * CORONAL HOLE Te is increasing at 2 Rsun with no sign of a turnover below 2.25 Rsun. Non-thermal velocities are roughly 90 km/s for protons (most UVCS studies focus on OVI ions) With the set of values determined for α and vnt there is excellent agreement between MAS model and observations. * While agreement is good, it is not unique.
16 Future Work * Examine the MAS model and other MHD models for other periods in the solar cycle * Incorporate the data from O VI to add further constraints to the model parameters * Study an active region in the corona to see how shaped empirical heating function compares to observations Recommendations * MAS model should incorporate separate Te and Tp parameters (two-fluid physics) in order to be more physically accurate, or provide a better definition of which single temperature is calculated.
17 References Akinari, N. (2007). Broadening of resonantly scattered ultraviolet emission lines by coronal hole outflows. ApJ, 660: Cranmer et al. (1999). An empirical model of a polar coronal hole at solar minimum. ApJ, 511: 481. Jacques, S.A. (1977). Momentum and energy transport by waves in the solar atmosphere and solar wind. ApJ, 215: Kohl et al. (1995). The Ultraviolet Coronagraph Spectrometer for the Solar and Heliospheric Observatory. Solar Physics, 162(1-2): Landi, E. and Cranmer, S.R. (2009). Ion temperatures in the low solar corona: Polar coronal holes at solar minimum. ApJ, 691: Lionello, R., J.A. Linker, and Z. Mikić (2009). Multispectral emission of the Sun during the first whole Sun month: Magnetohydrodynamics simulations. ApJ, 690: Ong et al. (1997). Self-consistent and time-dependent solar wind models. ApJ, 474: L143-L145. Withbroe, G.L., J.L. Kohl, and H. Weiser (1982). Probing the solar wind acceleration region using spectroscopic techniques. Space Science Reviews, 33: THANK YOU!
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19 UVCS Instrument Parameters * Ly-α channel Ruling frequency: 2400 l/mm Angle of incidence α: Angle of diffraction β: 3.98 Main radius of curvature: 750 mm Minor radius of curvature: mm Reciprocal Dispersion: 5.54 Å/mm (1st order) Spectral Bandwidth of pixel: 0.14 Å (1st order) Spatial width of pixel: mm Image:
20 Carrington Rotations DATE LONGITUDE * Model takes a base synoptic magnetogram from a full Carrington Rotation (e.g. from NSO at Kitt Peak) * One CR represents a full solar rotation from a point when 0 longitude faces Earth to the next. Image from
21 Parameters from Line Width If absence of non-thermal velocities (e.g. Alfvén waves): V1/e = c*δλ1/e/λ0 V1/e = sqrt(2kt/m) T = (m/2k)*v1/e2 = (mc2/2kλ02)*δλ1/e2 Lyα 1216 Å from H (m = proton mass) V1/e = 246.6*Δλ1/e V1/e = sqrt( T/60.5 ) T = ( 3.68 x 106 ) Δλ1/e Å from OVI (m = 16*proton mass) V1/e = 291*Δλ1/e V1/e = sqrt( T/965 ) T = ( 81.7 x 106 ) Δλ1/e2
22 MAS Model {n,v,t,b} CORPRO Goal is to search for consistency between the MAS model and the UVCS Data by using Forward Modeling. UVCS Data { I(rows,col) } DAS v40 Modeled { Itot, Δλ1/e } Observed { Itot, Δλ1/e } Data Map { I(λ) }
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