Recent studies disagree about the contribution of variations in temperature and salinity of the oceans-steric change-to the observed sea-level change. This article explores two sources of uncertainty to both global mean and regional steric sea-level trends. First, we analyze the influence of different temperature and salinity data sets on the estimated steric sea-level change. Next, we investigate the impact of different stochastic noise models on the estimation of trends and their uncertainties. By varying both the data sets and noise models, the global mean steric sea-level trend and uncertainty can vary from 0.69 to 2.40 and 0.02 to 1.56 mm/year, respectively, for 1993-2017. This range is even larger on regional scales, reaching up to 30 mm/year. Our results show that a first-order autoregressive model is the most appropriate choice to describe the residual behavior of the ensemble mean of all data sets for the global mean steric sea-level change over the last 25 years, which consequently leads to the most representative uncertainty. Using the ensemble mean and the first-order autoregressive noise model, we find a global mean steric sea-level change of 1.36 ± 0.10 mm/year for 1993-2017 and 1.08 ± 0.07 mm/year for 2005-2015. Regionally, a combination of different noise models is the best descriptor of the steric sea-level change and its uncertainty. The spatial coherence in the noise model preference indicates clusters that may be best suited to investigate the regional sea-level budget. Plain Language Summary Ocean temperature and salinity variations lead to changes in sea level, known as steric sea-level change. Steric variations are important contributors to sea-level change and reflect how the oceans have been responding to global warming. For this reason, several recent studies have quantified the contribution of steric variations to global and regional sea-level change. However, the reported rates largely differ between studies. In this paper, we look at how the use of different temperature and salinity data sets can be one of the causes of the different estimates of steric sea-level change published so far. We also investigate how different methods (noise models) used to obtain the rate of change can be another source of different results. We find that the rate of change can vary up to 2 mm/year for the global mean as a result of different data sets and methods used. Regionally, differences can reach up to several tens of millimeters per year. We show that the noise models should always be carefully chosen for each region, so that the rate of change is accurately estimated.