GOES-R DataJam: A Virtual Competition to Inspire the Next Generation of Satellite Data Users

The GOES-R DataJam held in October 2023 was a virtual interdisciplinary competition for undergraduate and graduate students to collaborate and develop innovative solutions to proposed challenges using GOES-R series geostationary satellite data. The goals of this educational event were to expand the remote sensing knowledge base and technical skillset of the participating students, provide them with the opportunity to network with NOAA and NASA professionals, award them with recognition for great ideas, leadership, and teamwork, and inspire them to be the next generation of satellite data users. That last goal is especially important due to the rapidly changing environment that this generation of students is experiencing, and it will take observations from many different satellite instruments to measure and analyze these environmental changes on a global-scale.

The GOES-R DataJam included a variety of training sessions on GOES-R, including interpretation and application of Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) data, how to access the open source data hosted on cloud provider systems, and practical coding examples for retrieving and plotting the data. There was also a scoping day, during which team leads explained their project ideas to recruit team members. The competition itself was a two-week period for project development and presentation preparation. A presentation day was held for judges to view and score the project results, and an awards ceremony was streamed to announce the winners of each challenge.

There were two challenges for the teams to choose from: one focused on data fusion, and the other on data visualization. The teams were required to use openly available data and tools, such as the GOES-R series data stored in the AWS and Google cloud buckets and the Google Earth Engine and Google Colab cloud computing environments. In addition, a JupyterHub environment on an AWS cloud server was provided to the teams as another option for collaborative code development.

This presentation will summarize the activities of the GOES-R DataJam, describe the lessons learned from the planning and execution of this event, and spotlight results from the winning teams.