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In the search for small exoplanets orbiting cool stars whose spectral energydistributions peak in the near infrared, the strong absorption of radiation inthis region due to water vapour in the atmosphere is a particularly adverseeffect for the ground-based observations of cool stars. To achieve thephotometric precision required to detect exoplanets in the near infrared, it isnecessary to mitigate the impact of variable precipitable water vapour (PWV) onradial-velocity and photometric measurements. The aim is to enable global PWVcorrection by monitoring the amount of precipitable water vapour at zenith andalong the line of sight of any visible target. We developed an open sourcePython package that uses Geostationary Operational Environmental Satellites(GOES) imagery data, which provides temperature and relative humidity atdifferent pressure levels to compute near real-time PWV above any ground-basedobservatory covered by GOES every 5 minutes or 10 minutes depending on thelocation. We computed PWV values on selected days above Cerro Paranal (Chile)and San Pedro M\'artir (Mexico) to benchmark the procedure. We also simulateddifferent pointing at test targets as observed from the sites to compute thePWV along the line of sight. To asses the accuracy of our method, we comparedour results with the on-site radiometer measurements obtained from CerroParanal. Our results show that our publicly-available code proves to be a goodsupporting tool for measuring the local PWV for any ground-based facilitywithin the GOES coverage, which will help in reducing correlated noisecontributions in near-infrared ground-based observations that do not benefitfrom on-site PWV measurements.

Near real-time precipitable water vapour monitoring for correcting near-infrared observations using satellite remote sensing