Context. To enable radial velocity (RV) precision on the order of ~0.1 m s−1 required for the detection of Earth-like exoplanets orbiting solar-type stars, the main obstacle lies in mitigating the impact of stellar activity. Aims. This study investigates the dependence of derived RVs with respect to the formation temperature of spectral line segments. Methods. Using spectral synthesis, we computed the stellar temperature below which 50% of the emergent flux originates for each observed wavelength point of unblended spectral lines. We then constructed RV time series for different temperature ranges using template matching. Results. With HARPS-N solar data and HARPS α Cen B measurements, we demonstrate on time intervals of prominent stellar activity that the activity-induced RV signal has different amplitude and periodicity depending on the temperature range considered. We compare the solar measurements with simulated contributions from active surface regions seen in simultaneous images, and find that the suppression of convective motion is the dominant effect. Conclusions. From a carefully selected set of spectral lines, we are able to measure the RV impact of stellar activity at various stellar temperatures ranges. We are able to strongly correlate the effect of convective suppression with spectral line segments formed in hotter temperature ranges. At cooler temperatures, the derived RVs exhibit oppositely directed variations compared to the average RV time series and stronger anticorrelations with chromospheric emission.

Context. Radial velocity (RV) measurements induced by the presence of planets around late-type stars are contaminated by stellar signals that are of the order of a few meters per second in amplitude, even for the quietest stars. Those signals are induced by acoustic oscillations, convective granulation patterns, active regions co-rotating with the stellar surface, and magnetic activity cycles. Aims. This study investigates the properties of all coherent stellar signals seen on the Sun on timescales up to its sidereal rotational period. By combining HARPS and HARPS-N solar data spanning several years, we are able to clearly resolve signals on timescales from minutes to several months. Methods. We use a Markov Chain Monte Carlo (MCMC) mixture model to determine the quality of the solar data based on the expected airmass-magnitude extinction law. We then fit the velocity power spectrum of the cleaned and heliocentric RVs with all known variability sources, to recreate the RV contribution of each component. Results. After rejecting variations caused by poor weather conditions, we are able to improve the average intra-day root mean square (RMS) value by a factor of ∼1.8. On sub-rotational timescales, we are able to fully recreate the observed RMS of the RV variations. In order to also include rotational components and their strong alias peaks introduced by nightly sampling gaps, the alias powers are accounted for by being redistributed to the central frequencies of the rotational harmonics. Conclusions. In order to enable a better understanding and mitigation of stellar activity sources, their respective impact on the total RV must be well-measured and characterized. We are able to recreate RV components up to rotational timescales, which can be further used to analyse the impact of each individual source of stellar signals on the detectability of exoplanets orbiting very quiet solar-type stars and test the observational strategies of RV surveys.