IINTERACT aims at new Earth Observation (EO) variables and at operational and climate applications, based on the capability capitalization of three teams (CSIC, UPC and USAL) with long joint research trajectory on satellite remote sensing (RS). The cornerstones of INTERACT are i) the definition of new EO concepts based on the synergy of missions, variables and applications, creating new, added-value assets; ii) the capitalization of the RS expertise of the teams; and iii) the integration of such assets in the Barcelona Expert Center (BEC) production and distribution system to reach the community at large. In an age of intense and rapid changes in the economy and the environment, INTERACT aim is beyond established, monolithic paradigms of single missions, single variables, to better respond to the societal needs. Synergy at all levels (instrumental, variable, application) is the leitmotiv of INTERACT. Thanks to this synergistic approach, INTERACT gathers together the expertise on data processing and aims at a new generation of EO products, with a special focus on long-term series of enhanced spatio-temporal resolution variables: sea surface salinity on semi-enclosed seas and polar regions, sea ice parameters, wind forcing, coastal and extreme ocean winds, chlorophyll concentration, water quality, vegetation optical depth, plant water content, vegetation biomass, etc. New and enhanced information content is generated to address crucial scientific questions: Which changes are taking place on the ocean surface due to climate change? How are fast mesoscale convective systems affecting the atmospheric flow? Can we forecast the next crop yield with good accuracy? Which is the impact of the changes in land runoff? Are climate patterns modifying soil moisture, affecting vegetation hydric stress and favoring risks like wildfires, floods and disease spread?The vertex of this synergistic, integrative effort of INTERACT is the assembling of some major pieces of the Earth system (interactions between ocean, atmosphere and land), aiming at variables never previously described by RS means.