We used a minimum size threshold of five pixels in order to remove very small SGLs or slush likely comprised solely of mixed pixels, following previous studies (Arthur et al., 2021; Moussavi et al., 2020; Pope et al., 2016, Stokes et al., 2019).

We manually verified our classification results against 2175 Landsat 8 images and removed any false positives (cloud, shadow or rock mis-identified as SGLs that bypassed initial cloud, rock and seawater masking procedures due to spectral similarities). These false positives were often distinguishable by their ''diffuse'' boundaries, as opposed to distinct lake objects. Moussavi et al. (2020) recorded an accuracy of >94% when validating SGLs classified using our method against manually-digitized SGLs.

A detailed description of the data collection, quality control, processing and analysis, as well as full references, is given in: Arthur, J.F, Stokes, C.R., Jamieson, S.S.R, Carr, J.R, Leeson, A.A, Verjans, V. (in review) Large interannual variability in supraglacial lakes around East Antarctica.