Presented at the GHRSST XXIII international science team meeting, 27 June-1 July 2022, online and in-person (Barcelona). #GHRSST23 Short abstract Sea surface temperature (SST) climatology datasets provide the reference for observations of ocean anomalous events, which may have significant effects on the local marine ecosystem. The representativeness of the SST climatologies of the historical and current ocean surface states is essential to identify and predict anomalous events. Here we compare five high-resolution SST climatology datasets around the Australian coast to investigate the uncertainty introduced by the reference SSTs to current estimates of SST anomalies. The datasets studied are: (i) 0.05-degree global daily climatology calculated by this study from the ESA SST Climate Change Initiative (CCI) Analysis v2.0 product (1981-2016); (ii) 0.25-degree global daily climatology for 1981-2016, derived from the NCEI daily AVHRR_OI SST; (iii) 0.02-degree SST Atlas of the Australian Regional Seas (SSTAARS), a pixel-wise daily climatology for 1992-2016; (iv) 0.05-degree NOAA Coral Reef Watch (CRW) global monthly climatology for 1985–2012 and (v) 0.1-degree global daily climatology for 1994-2016, derived from the BRAN_2016 ocean reanalysis. The climatology datasets formed from SST CCI analysis v2.0 data are used as the reference to compare datasets (ii)-(v) based on the same reference time period and central year. This study indicates that climatologies (i) and (v) would be suitable for use as a reference over the Australian region. However, for smaller spatial scales, or where a night-only SST climatology is required, the 2 km daily SSTAARS would also be suitable. The feature resolution of the climatology datasets (i) and (v) is significantly coarser than SSTAARS climatology.