 This study explores the triple collocation error estimation technique to assess the relative quality of several globally available soil moisture products from active and passive microwave sensors. The technique estimates the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three linearly related data sources with independent error structures. The study reveals trends in uncertainty related to different observation principles, frequencies, and choice of independent reference dataset. Results suggest that the triple collocation method provides realistic error estimates, and if theoretical prerequisites are fulfilled, errors estimated for remote sensing products are hardly influenced by the choice of third independent dataset. This study can help develop adequate strategies for combined use of various scatterometer and radiometer-based soil moisture datasets to improve improved flood forecast modeling or generation of superior multi-mission long-term soil moisture datasets. This article was authored by W.A. Durigo, K. Saipal, R.M. Paranusa, and others. We are article.tv. Links in the description below.