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tokens: in the water column density (mainly due to airmass variations). As we can see with panel c, all the telluric lines are corrected to the noise level (including the telluric lines blended with stellar lines). 4. Methods In this section, we describe how the transmission spectrum was derived and how we can search for water vapor in it with the cross-correlation technique. 4.1. Transmission spectrum The transmission spectrum ( Seager Sasselov 2000 ; Brown 2001 ) was obtained during the transit, when the planet passes in front of the star. It is defined as the area occulted by the planet over the stellar disk as a function of wavelength and probes the highest layers of the atmosphere. We computed the transmission spectrum following the same formalism as Wyttenbach et al. (2017) . Once the spectra are corrected from telluric features, weseparated in-transit spectra from out-transit spectra. Anin-transit spectrum, , is a spectrum obtained when the planetoccults a part of the stellar disk, while an out-transit spectrum, ,corresponds to the full-disk stellar spectrum. We corrected each spectrum for the stellar reflex motion induced by the planet, using the orbital parameters in Table 1 . Then, we created the normalized master out-transit spectrum which is the sum of the out-transit spectra: We normalized all the in-transit spectra to the continuum level of the master out-transit spectrum with a fourth-degree polynomial. This normalization was made from 5338 Å to 6900 Å, which corresponds to the red CCD. We applied a sigma-clipping rejection algorithm on the spectra in order to replace all the cosmic ray hits by the mean value of the other spectra at each wavelength. A normalized in-transit spectrum is noted . Then, we computed the transmission spectrum as the sum of each individual transmission spectrum (), after applying a Doppler shift to the planet rest frame to compensate for the planet orbital motion during transit: Finally, we expressed the variation of the occulted area by the planet as a function of wavelength on an absolute scale, by using the known white-light radius ratio (Table 1 ) : 4.2. Cross-correlation function The study of water vapor in the transmission spectrum in the visible is difficult considering the low intensity of the water bands and the noise level, even if we are able to resolve each line. To detect water vapor we need to co-add hundreds of lines to maximize the signal-to-noise ratio (S/N). To do so we used the cross-correlation function (CCF), expressed by: This technique ( Baranne et al. 1996 ; Pepe et al. 2002 ) consists of projecting a binary mask (with an aperture width of one pixel) on the spectrum and to sum the transmitted flux at each wavelength. The mask contains the theoretical wavelengths of water vapor transitions, and is Doppler shifted successively to scan a radial velocity range of –80 to 80 km s with a step of 0.82 km s. This step corresponds to the size of one pixel on the CCD of HARPS. In this study,