Lowering Barriers to the Adoption and Mainstreaming of Earth Observation Data: The Global Precipitation Measurement Mission (GPM) Mentorship Program

Abstract The Global Precipitation Measurement (GPM) Mission Mentorship Program was designed to foster the adoption and application of Earth observation (EO) data in research and societal applications with a focus on satellite precipitation data. Developed as a free, online initiative, the program addressed persistent barriers to the effective use of GPM data by leveraging expertise from a broad network of subject matter experts (SMEs) and mentors from leading organizations. Key features include an incremental learning structure combining introductory lectures, hands-on demonstrations, and a capstone project, enabling participants from a global audience (71 countries over the 3 years) and with varied backgrounds to develop technical and domain-specific competencies. By tailoring the mentorship to individual participant needs and integrating hands-on data exploration, the program enhances the accessibility, usability, and societal impact of GPM products. This paper synthesizes lessons learned from program implementation, offering 10 actionable insights for designing scalable mentorship models that bridge the gap between EO data and its widespread application in addressing global challenges. Significance Statement Despite the growing availability of satellite data, substantial barriers persist that limit the adoption and effective use of precipitation data in support of climate resilience, disaster preparedness, and sustainable development. The Global Precipitation Measurement (GPM) Mentorship Program was established to address this challenge by providing free, structured, and hands-on training in the use of GPM data. Over 3 years, the program reached participants from 71 countries and supported over 50 capstone projects across fields including extreme precipitation and water resources. By combining expert-led lectures with tailored mentorship and data exploration, the program fostered long-term collaboration and delivered actionable insights in support of research and operational applications. These results demonstrate a scalable, user-centered model for accelerating the adoption of meteorological Earth observation data in real-world applications.