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eSDO 1111: Solar Algorithm List

This document can be viewed as a PDF. Deliverable eSDO-1111
E.Auden, W. Chaplin, L. Culhane, Y. Elsworth, A. Fludra, R. Harrison, M. Thompson, L. van Driel-Gesztelyi
31 March 2005

Introduction

The following solar algorithms will be written and implemented as grid services. All four institutions in the eSDO consortium will be responsible for 2 - 4 algorithms. A full description for each algorithm including inputs, outputs, science and technical use cases, interfaces, and proposed solutions will be included with deliverable eSDO-1121.

List of Algorithms

  1. Mode Parameters Analysis
  2. Mode Asymmetry Analysis
  3. Subsurface Flow Analysis
  4. Perturbation Map Generation
  5. Local Helioseismology Inversion Workbench
  6. Loop Recognition
  7. Magnetic Field Extrapolation
  8. Helicity Computation
  9. CME Dimming Region Recognition
  10. DEM Computation
  11. Small Event Detection
  12. Solar Rotation Profiling (if time permits)
  13. Oscillation Sources Analysis (if time permits)

Algorithm Detail

  1. Mode Parameters Analysis: (renamed from "mode frequency analysis" 23/09/05)
    • Primary Responsibility: University of Birmingham, Co-I Yvonne Elsworth and Bill Chaplin
    • Description: The mode frequency analysis algorithm will calculate mode parameters such as frequency, power, line width and variability. The analysis procedure will filter HMI time series data to isolate single oscillation modes or a family of modes. After a fourier analysis is applied to these modes, fitting procedures will determine the mode parameters.
  2. Mode Asymmetry Analysis
    • Primary Responsibility: University of Birmingham, Co-I Yvonne Elsworth and Bill Chaplin
    • Description: This algorithm will measure the departure of the mode from a symmetric profile by applying simultaneous fitting over several modes to identify the noise contributions.
  3. Subsurface Flow Analysis
    • Primary Responsibility: University of Sheffield, Co-I Michael Thompson
    • Description: Using HMI tracked dopplergrams as input, this algorithm will measure subsurface flows in upper convection zone, resulting in travel-time difference maps for different skip distances and orientations, subsurface flow maps under the tracked region obtained by inversion, and combinations of flow maps under tracked regions into synoptic maps. These data products will promote understanding and predicting active region evolution and evolution of atmospheric magnetic structures.
  4. Perturbation Map Generation
    • Primary Responsibility: University of Sheffield, Co-I Michael Thompson
    • Description: This algorithm will measure wavespeed anomalies in the upper convection zone and, in particular, under active regions to understand active region and sunspot subsurface structures and flux emergence. This analysis will generate travel-time anomaly maps for different skip distances, subsurface wavespeed anomalies under the tracked region obtained by inversion, and combinations of wavespeed anomaly maps under tracked regions into synoptic maps.
  5. Local Helioseismology Inversion Workbench
    • Primary Responsibility: University of Sheffield, Co-I Michael Thompson
    • Description: The workbench will provide a front-end GUI for specifying and launching inversions of helioseismic data on local or remote machines. Subsurface reconstructions of flows or wavespeed anomalies will be obtained by inversion. The workbench will maintain queueing systems, data indices and inversions results; in addition, the user will be able to retrieve and display inversions results.
  6. Loop Recognition
    • Primary Responsibility: Mullard Space Science Laboratory, Co-I Len Culhane and Lidia van Driel-Gesztelyi
    • Description: Coronal loops observed by SDO will be identified in AIA images. Using an iterative approach, identified coronal loops will be matched with magnetic field line extrapolations.
  7. Magnetic Field Extrapolation
    • Primary Responsibility: Mullard Space Science Laboratory, Co-I Len Culhane and Lidia van Driel-Gesztelyi
    • Description: Using SDO magnetograms as photospheric boundary condition, a fast fourier transform will be used to calculate magnetic field strength and directionality for each point of an arbitrarily defined computational box. The algorithm will compute magnetic connectivities between opposite magnetic polarities and draw characteristic field lines.
  8. Helicity Computation
    • Primary Responsibility: Mullard Space Science Laboratory, Co-I Len Culhane and Lidia van Driel-Gesztelyi
    • Description: Using a series of SDO magnetograms as input, this procedure will compute the flux of magnetic helicity through the photospheric boundary. Magnetic field extrapolations and the derived magnetic connectivities will be used to improve the helicity flux results.
  9. CME Dimming Region Recognition
    • Primary Responsibility: Rutherford Appleton Laboratory, Co-I Richard Harrison and Andrzej Fludra
    • Description: Time series of difference images in coronal lines will be examined for the change of brightness (dimming). Visual detection of the coronal dimming has proved successful in the past, but this automated algorithm will detect varying spatial scales of the dimming region from approximately 45 heliographic degrees down to a fraction of an active region area.
  10. DEM Computation
    • Primary Responsibility: Rutherford Appleton Laboratory, Co-I Richard Harrison and Andrzej Fludra
    • Description: Calculation of differential emissional measure (DEM)1 requires calibrated line intensities and line emissivities as a function of temperature, or G(T) functions. The solar community has developed several DEM algorithms use either iterative methods or gradient optimization methods with smoothing constraints. One of these existing algorithms, such as the DEM program included in the CHIANTI package, will be selected for eSDO based on current availability of software and ease of adaptation.
  11. Small Event Detection
    • Primary Responsibility: Rutherford Appleton Laboratory, Co-I Richard Harrison and Andrzej Fludra
    • Description: The algorithm will detect small-scale brightenings in AIA images of the corona, transition region and photosphere. Based on the EIT brightness detection work of Berghmans, Clette, and Moses2, this procedure will define a reference background emission, identify events through a scan of light curves of all pixels, and determine event dimensions in the temporal and spatial domains.
  12. Solar Rotation Profiling (if time permits)
    • Primary Responsibility: University of Sheffield
    • Description: HMI data will be used to develop solar rotation profiles as a function of depth and latitude for the internal Sun between the solar surface and the convective zone.
  13. Oscillation Sources Analysis (if time permits)
    • Primary Responsibility: University of Birmingham, Co-I Yvonne Elsworth and Bill Chaplin
    • Description: Beginning with the simple assumptions that the mode asymmetry in velocity can be related to the location of the oscillation source, this algorithm will augment the oscillation source profile using noise analysis in both velocity and intensity.

References

  1. Withbroe, 1975, Solar Phys., 45, 301.
  2. Berghmans, Clette and Moses, 1998, A&A, 336, 103.

-- ElizabethAuden - 23 Mar 2005

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Topic revision: r13 - 2005-10-12 - ElizabethAuden
 
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