  The variability induced by precipitable water vapour (PWV) can heavily affect
the accuracy of time-series photometric measurements gathered from the ground,
especially in the near-infrared. We present here a novel method of modelling
and mitigating this variability, as well as open-sourcing the developed tool --
Umbrella. In this study, we evaluate the extent to which the photometry in
three common bandpasses (r', i', z'), and SPECULOOS' primary bandpass (I+z'),
are photometrically affected by PWV variability. In this selection of
bandpasses, the I+z' bandpass was found to be most sensitive to PWV
variability, followed by z', i', and r'. The correction was evaluated on global
light curves of nearby late M- and L-type stars observed by SPECULOOS' Southern
Observatory (SSO) with the I+z' bandpass, using PWV measurements from the
LHATPRO and local temperature/humidity sensors. A median reduction in RMS of
1.1% was observed for variability shorter than the expected transit duration
for SSO's targets. On timescales longer than the expected transit duration,
where long-term variability may be induced, a median reduction in RMS of 53.8%
was observed for the same method of correction.
