vdt: Merged Day Complex SHT Time Series

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A network day time series (mrvdt) is created by merging the contemporaneous mode coefficients from site days that contribute to the network day using a weighted average at each time sample based on the Modulation Transfer Function and its estimated error.

Inclusive times can be found in the FITS header keywords TS_START and TS_END. The data product is identified by its date.

Dimensionally, the x-axis is time (sec), the y-axis is the order of the spherical harmonic, M, from 0 to L, with the window function at the last row, and the z-axis contains the real [*,*,1], and imaginary parts [*,*,2]. The real part of the row containing the window function is the observed window function and the imaginary part is the window function after gap filling.

Starting with network day 960606, these data products were no longer archived to a DSDS tape. L-nu diagrams are still produced.

• Sample Time Series
• Sample FITS header

Steps involved:

1. Calibrate the measured MTF files.
   lpar mtfcal
        input = ""              List of input MTF[k(r)] files
       output = ""              List of output MTF[l] files
   (trim_file = "grasplib$plm_0200.txt") ASCII triming file
   (data_type = "velocity")     Image data type |velocity|intensity|
(correct_type = "full")         Correction type |full|sky_optics|pixel_only|
        (mask = yes)            Apply moving mask?
    (mask_cbr = 0.05)           Moving mask radius for cosine-bell apodization
  (mask_EWrad = 0.95)           Maximum mask fractional radius in E-W direction
  (mask_NSrad = 0.95)           Maximum mask fractional radius in N-S direction


2. Create the day time series template with mkts.
   lpar mkts
     rootname =                 Rootname of monthly times series template
     ts_start =                 TS_START value: yyyy/mm/dd hh:mm:ss
       ts_end =                 TS_END value: yyyy/mm/dd hh:mm:ss
  (gong_month = INDEF)          GONG month number
    (gong_day = "0000/00/00")   GONG date for merged daily template (YY/MM/DD)
     (l_start = 0)              Starting L-value
       (l_end = 200)            Ending L-value
       (l_max = INDEF)          L_max of SHT decomposition (default= l_end)
      (m_type = "all")          M-type: all|even
  (dispersion = 60.)            Time dispersion (seconds)
(merge_templa = no)             Merge time series template

   output
        mrvdtYYMMDDd[000-200]

   sample FITS header output
        TS_START= '1996/05/26 00:00:16'
        TS_END  = '1996/05/26 23:59:16'
        (data product id: mtvdt960526d[000-200])


3. Merge the sites into the day template with tsmerge.
   lpar tsmerge
        input =                   Input list of site day times series images
        ots_path =                Full path name of network day L=0 image
        mtf_path = "./"           Full path MTF image directory
        (type_weight = "mtferr")  Type of weighting (mtferr|equal|oldmtferr)
        (threshold = 2.)          Reject data where  MTF <= threshold * MTF_ERROR

   sample FITS header output
        MERGE_BB=                    T
        MERGE_LE=                    T
        MERGE_ML=                    T
        (Each merged site will have an entry similar to this)


4. Normalize the time series from a 3-plane image (with real, imaginary,
   and weights as the three planes) to a 2-plane image with tsnorm.
   lpar tsnorm
        input =              Input list of network day times series images
       output =              Output list of normalized network day times series

   sample FITS header output
        GHIST000= 'Task TSNORM (96/08/06 15:24:06, V93.2.32)'
        GHIST001= 'input=tmrvdt960523d000.imh'


5. Fill gaps in GONG time series via autoregressive filter with gapfill.
   lpar gapfill
        maxlen = 20             Maximum Auto-regressive filter length
        fill_factor = 0.1       Filling factor
        (max time length gap filled by gapfill = maxlen * fill_factor)

    sample FITS header output
        TS_NEFF =                 1354
        GTS_NEFF=                 1440
        GHIST002= 'Task GAPFILL (96/08/06 15:31:51, V93.2.32)'
        GHIST003= 'input=mrvdt960523d000.imh,maxlen=20,fill_factor=0.1'


6. Find the fraction of the month time series that is filled.
        Fill factor = GTS_NEFF / ts_length


7. Write the time series to a DSDS tape.
        Starting with network day 960606, this data product will no longer
        be archived to a tape.

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