HMI_Logo HMI Team Workshop:
Local Helioseismology Pipelines
Stanford University      March 7-9, 2007

Ring Diagrams Team Report

	expect calibrated Dopplergrams, photograms, line-depth?, of
	Uniform quality (whatever that means), mapped with a uniform
	plate scale to something close to the observed pixel resolution,
	with sufficient ancillary data to remap the photosphere and
	possibly detrend the data: image center location, plate scale,
	effective observing time, observer location and velocity

	inversion kernels

	solar model for fluid dynamic diagnostics (Model S) and for
	sound-speed inversions

	maps of inverted V,c as data segments of common records (along
	with errors, inversion coefficients for multiple data
	series with primary keys of Carrington Time (center of tracking
	time interval, keyed to equal intervals in central meridian longitude
	(geocentric or at SDO?) and Carrington longitude and latitude
	Each series characterized by different surface grid spacing,
	cadence, and depths

	fit parameters with errors for each set used for above (i.e.
	each tracked cube)

	Grid spacings (= 0.5 track cube diameter) selected from range
	(1deg, 2deg, 4º, 8deg, 16deg) approx - total of 3—5 series
	coverage to be complete within region such that outermost edge
	of tracked data within 80deg of disc center; grid locations
	appropriate integral multiples of spacing, with longitudes
	characterized by center of tracking interval

	Cadence TBD in range ~3hr - 15hr, fixed to simple fractions of
	Carrington rotation, e.g. 15deg of rotation, 5 deg of rotation...
	oberving interval twice cadence

	tracking at rate for fixed model - either agreed-upon in advance,
	or one that minimzes variance in mean zonal velocity profile at
	surface (3 param in cos(lat)) over say first 3 rotations of HMI
	data (go back and redo); use Postel's projection, cubic convolution
	interpolation for now, but revisit.

	power spectra apodized with circular symmetry in k-space to 0 power
	at edge of region

	ring fits by two procedures (Haber, Basu), both subject to future
	refinement and modifications

	inversions by RLS and OLA for both fitting procedures, as above

	1. Try using larger rings for getting down to tachocline (LONG-TERM)

	2. Global fitting of power spectrum rather than individual ridges (")

	3. Characterize results from both methods for fits to MDI Hi-Res data
	at grid sizes of 2-16deg, in time ranges 4-15 hrs in order to
	optimize selection of output tilings (SHORT-TERM 9/1)

	4. Calculate 3-d inversion kernels and develop 3-d inversions

	5. Forward calculations (LONG-TERM)

	6. Inversions from artifical data of Stein et al., Hanasoge

	Run existing and pipeline code on MDI Hi-Res data in traditional
	environment and in DRMS

	port fastrack and powrspec - Bogart
	port ringfit11 (Basu style) - Bogart, Soares
	port ringfitaz (Haber style), include consolidation into single
		module - Haber, González
	provide FORTRAN binding to API for above - Suarez
	port SSW inversions - Haber
	port Basu inversions - Basu, Bogart
	Analyze Stein artificial data - ?
	Analyze Hanasoge artificial data - González
	Run characterization (research 3) - Bogart, Haber, Basu
	Invert large-rings data (reearch 1) - Hill

	1. FORTRAN binding		15 May (Suarez)
	2. port MDI code		15 June (Bogart, Soares)
	3. port GONG/JILA code		15 June (González, Haber)
	4. port Yale code		1 July (Basu)
	4.5 import MDI spectra to DRMS	15 May (Bogart)
	5. verification			15 Aug (tutti)

	a. specification of tracking input, output	1 Apr (Bogart, Schou)
	b. specification and import of 1D kernels	1 Apr (Haber, Basu)
	c. specification and import of 3D kernels	1 Sep (Haber)
	d. specify & import model			1 May (Hill)
	e. strawman data product specification		1 Apr (Haber, Bogart)
	f. refine data product specification		1 Sep (")
	g. output keyword specifications		1 May (Bogart)
	h. artificial data analysis (Hanasoge)		1 Jun (González)
	i. artificial data analysis (Stein et al.)	?
	j. determine appropriate tracking rate suitable	15 Aug (Scherrer)
	   for both rings and time-distance (and other?)