Skycorr: A general tool for spectroscopic sky subtraction

Abstract

Context. Airglow emission lines, which dominate the optical-to-near- infrared sky radiation, show strong, line-dependent variability on time scales from minutes to decades. Therefore, the subtraction of the sky background in the affected wavelength regime becomes a problem if plain-sky spectra have to be taken at a different time from the astronomical data. Aims. A solution of this problem is the physically motivated scaling of the airglow lines in the plain-sky data to fit the sky lines in the object spectrum. We have developed a corresponding instrument-independent approach based on one-dimensional spectra. Methods. Our code skycorr separates sky lines and sky/object continuum by an iterative approach involving a line finder and airglow line data. The sky lines, which mainly belong to OH and O2 bands, are grouped according to their expected variability. The line groups in the sky data are then scaled to fit the sky in the science data. Required pixel-specific weights for overlapping groups are taken from a comprehensive airglow model. Deviations in the wavelength calibration are corrected for by fitting Chebyshev polynomials and rebinning via asymmetric damped sinc kernels. The scaled sky lines and the sky continuum are subtracted separately. Results. ESO-VLT X-shooter data covering 2.5 h with a good time resolution were selected to illustrate the performance. Data taken six nights and about one year before were also used as reference sky data. The variation of the sky-subtraction quality as a function of time difference between the object and sky data depends on changes in the airglow intensity, atmospheric transparency, and instrument calibration. Except for short time intervals of a few minutes, the sky line residuals were between 2.1 and 5.5 times weaker than for sky subtraction without fitting. Additional tests showed that skycorr performs consistently better than the method of Davies (2007, MNRAS, 375, 1099) developed for ESO-VLT SINFONI data. © 2014 ESO.