We usually take both twilight sky flats and dome flats; our experience is that sky flats do a better job of flattening the data, but we need both types of data if we are to construct a good pupil ghost for the Kitt Peak data.
The first step is to simply combine the data by filter to generate a
master dome flat and master sky flat; we use flatcombine and
sflatcombine. Note that flatcombine will automatically
process the dome flats through ccdproc to make the cross-talk
correction, overscan correction, and so on, but for some reason
sflatcombine is not that smart. So, first process your sky
flats through basic ccdreductions as follows:
ccdproc sflat* xtalkcor+ fixpix+ overscan+ trim+ zerocor+
using the cross-talk and bias image you specified when you did
setinstrument
PACKAGE = mscred
TASK = flatcombine
input = dflat* List of flat field images to combine
(output = Flat) Output flat field root name
(combine= average) Type of combine operation
(reject = crreject) Type of rejection
(ccdtype= flat) CCD image type to combine
(process= yes) Process images before combining?
(subsets= yes) Combine images by subset parameter?
(delete = no) Delete input images after combining?
(scale = mode) Image scaling
(statsec= ) Image section for computing statistics
(nlow = 1) minmax: Number of low pixels to reject
(nhigh = 1) minmax: Number of high pixels to reject
(nkeep = 1) Minimum to keep (pos) or maximum to reject (neg)
(mclip = yes) Use median in sigma clipping algorithms?
(lsigma = 3.) Lower sigma clipping factor
(hsigma = 3.) Upper sigma clipping factor
(rdnoise= 20) ccdclip: CCD readout noise (electrons)
(gain = 2.8) ccdclip: CCD gain (electrons/DN)
(snoise = 0.) ccdclip: Sensitivity noise (fraction)
(pclip = -0.5) pclip: Percentile clipping parameter
(blank = 1.) Value if there are no pixels
(mode = ql)
PACKAGE = mscred
TASK = sflatcombine
input = @allskies2 List of images to combine
(output = Sflat) Output sky flat field root name
(combine= average) Type of combine operation
(reject = crreject) Type of rejection
(ccdtype= ) CCD image type to combine
(subsets= yes) Combine images by subset parameter?
(scale = mode) Image scaling
(statsec= ) Image section for computing statistics
(nkeep = 1) Minimum to keep (pos) or maximum to reject (neg)
(nlow = 1) minmax: Number of low pixels to reject
(nhigh = 1) minmax: Number of high pixels to reject
(mclip = yes) Use median in sigma clipping algorithms?
(lsigma = 6.) Lower sigma clipping factor
(hsigma = 3.) Upper sigma clipping factor
(rdnoise= rdnoise) ccdclip: CCD readout noise (electrons)
(gain = gain) ccdclip: CCD gain (electrons/DN)
(snoise = 0.) ccdclip: Sensitivity noise (fraction)
(pclip = -0.5) pclip: Percentile clipping parameter
(blank = 1.) Value if there are no pixels
(grow = 3.) Radius (pixels) for neighbor rejection
(fd = )
(mode = ql)