Abstract
Climate services often require observational climate data to inform decision-making on mitigation and adaptation activities. Understanding the uncertainties in the climate datasets that are used for this purpose, and how these uncertainties relate to the context of the climate service is critical to making well-informed decisions. Recent developments in the production of climate-relevant satellite datasets has focused on characterising uncertainties from a bottom-up perspective with a high degree of mathematical rigour. Using the example of three essential climate variables: sea surface temperature, soil moisture and carbon dioxide we discuss how to translate the highly-detailed uncertainty information provided with high-resolution datasets into something appropriate to the scale of a climate service, where the decision-making context might be local, regional or global. Close engagement between climate data producers and climate service providers is essential to ensure we have the best possible platform to make decisions as we adapt to climate change.