Precise near-infrared photometry, accounting for precipitable water vapour at SPECULOOS Southern Observatory

TL;DR

This paper introduces a new method and open-source tool, Umbrella, to correct for precipitable water vapour effects in near-infrared ground-based photometry, significantly improving measurement precision especially for long-term observations.

Contribution

The study presents a novel modelling technique and software to mitigate PWV-induced variability in near-infrared photometry, enhancing data accuracy for ground-based telescopes.

Findings

I+z' bandmost affected by PWV variability

Median RMS reduction of 1.1% for short-term variability

Median RMS reduction of 53.8% for long-term variability

Abstract

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.