flagged region that is wider than 10 channels and less than 40 channels from one end of the spectrum (potential bright sources that lie near the edge of the spectrum and cause incorrect continuum over-subtraction during the former data reduction). Otherwise the flagged channel (which is not likely to belong to a bright source) gets replaced by a first order polynomial interpolation from nearby channels. We repeat the above steps of flagging and convolution until $\sigma_m$ (with typical value of a few times 0.1 mJy beam$^{-1}$) varies by less than 10$^{-5}$ mJy beam$^{-1}$, or after 10 iterations. Figure \[fig:subcont\] shows that this procedure models a variety of spectral baseline shapes successfully.

The final step of this procedure consists of combining all spectral baseline models into individual cubes. We smooth these cubes with a gaussian kernel with a FWHM of 2 pixels in the Ra-Dec direction in order to reduce the fluctuation between adjacent pixels (this does not significantly modify the PSF (which has a typical FWHM of 3.7 pixels). Finally, we subtract the resulting spectral baseline model cube from the original cube. After this subtraction, the median rms of each data cube drops very slightly from 0.367 to 0.363 mJy 