Satellite imagery of the Earth atmosphere, oceans and land have been available for more than five decades. The ability to visualize evolving storm systems, ocean current circulation or seasonal ecosystem change inspires not only a sense of awe and wonder but also a feeling of mastery over the natural world. Instruments on satellites are, however, more than cameras in the skies. They measure Earth system radiation – both incoming and outgoing, reflected and emitted – in distinct electromagnetic channels. Passive remote sensing of top-of-atmosphere radiation is often described as indirect measurements of Earth system properties. For example, measurements of reflected radiation can be classified into vegetation types or inverted into cloud properties, and measurements of emitted radiation can be inverted into atmospheric profiles of temperature and moisture. This is easy enough to say, but what does such an indirect measurement mean to a decision-maker otherwise familiar with direct temperature measurements from, say, balloon launches? In distributing satellite data products to potential users, how does one talk about measurement error, retrieval uncertainty, inversion, dependence, correlation, or information content without obscuring the value of the product and its suitability for real-world planning and decision making? How does one build confidence in data products with such an abstract origin as “outgoing radiation”? Perhaps most importantly, how does one educate and foster user communities that implement satellite data products correctly and interpret their observed patterns accurately? These questions are especially relevant today as access to and need for satellite products are at an all-time high. This talk will discuss the challenges we face as algorithm developers and data product designers in communicating complex science concepts to the general public. Our discussion will make specific, real-world reference to lessons learned from NUCAPS (NOAA-Unique Combined Atmospheric Processing System) products in weather forecasting environments. It is only when scientific concepts enter the public domain that society can truly benefit from innovation.