This study aims to improve the uncertainty estimates of soil moisture datasets produced by merging various satellite products via inverse-variance weighting. In this scheme, the weight of each sensor depends on its specific uncertainty derived from Triple Collocation Analysis (TCA). However, the TCA-derived uncertainties are themselves uncertain due to finite sample sizes, introducing a second-order uncertainty we denote the ‘...

Earth observation data should inform decision making, but good decisions can only be made if the uncertainties in the data are taken into account. Making sense of uncertainty information can be difficult, because uncertainties represent the statistical spread in the observations (e.g., expressed as $$x \pm y$$ x ± y ), which does not relate directly to one specific use case of the data. Here, we propose a Bayesian framework to...