The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA's petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

The Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) is a NASA Earth Ventures Suborbital Investigation designed to test the hypothesis that oceanic frontogenesis and the kilometer-scale ("submesoscale") instabilities that accompany it make important contributions to vertical exchange of climate and biological variables in the upper ocean. These processes have been difficult to resolve in observations and models. A necessary step toward testing the hypothesis was to make accurate measurements of upper-ocean velocity fields over a broad range of scales and to relate them to the observed variability of vertical transport and surface forcing. To achieve that, we used aircraft-based remote sensing, satellite remote sensing, ships, drifter deployments, and a fleet of autonomous vehicles. This paper will provide a brief overview of the S-MODE measurements, with a special focus on surface current measurements.

The Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) is a NASA Earth Ventures Suborbital Investigation designed to test the hypothesis that kilometer-scale (“submesoscale”) ocean eddies make important contributions to vertical exchange of climate and biological variables in the upper ocean. To test this hypothesis, S-MODE will employ a combination of aircraft-based remote sensing measurements of the ocean surface, measurements from ships, measurements from a variety of autonomous oceanographic platforms, and numerical modeling. The field campaign will consist of two month-long intensive operating periods (IOPs) that will be preceded by a smaller-scale pilot experiment to test and improve operational readiness and to compare measurements made from different platforms. The pilot experiment was delayed because of the 2020 coronavirus pandemic, and it is currently planned for October-November 2020.