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)