  In the search for small exoplanets orbiting cool stars whose spectral energy
distributions peak in the near infrared, the strong absorption of radiation in
this region due to water vapour in the atmosphere is a particularly adverse
effect for the ground-based observations of cool stars. To achieve the
photometric precision required to detect exoplanets in the near infrared, it is
necessary to mitigate the impact of variable precipitable water vapour (PWV) on
radial-velocity and photometric measurements. The aim is to enable global PWV
correction by monitoring the amount of precipitable water vapour at zenith and
along the line of sight of any visible target. We developed an open source
Python package that uses Geostationary Operational Environmental Satellites
(GOES) imagery data, which provides temperature and relative humidity at
different pressure levels to compute near real-time PWV above any ground-based
observatory covered by GOES every 5 minutes or 10 minutes depending on the
location. We computed PWV values on selected days above Cerro Paranal (Chile)
and San Pedro M\'artir (Mexico) to benchmark the procedure. We also simulated
different pointing at test targets as observed from the sites to compute the
PWV along the line of sight. To asses the accuracy of our method, we compared
our results with the on-site radiometer measurements obtained from Cerro
Paranal. Our results show that our publicly-available code proves to be a good
supporting tool for measuring the local PWV for any ground-based facility
within the GOES coverage, which will help in reducing correlated noise
contributions in near-infrared ground-based observations that do not benefit
from on-site PWV measurements.
