Future NASA observing missions, including Earth science missions, envision distributed observing systems that coordinate spacecraft, models, analytics, and ground systems across institutional and computational boundaries. The Novel Observing Strategies Testbed (NOS-T), funded by NASA’s Earth Science Technology Office, provides a lightweight, cloud-native environment to realize and evaluate new mission concepts before costly flight or operational development. This presentation describes how operational deployment of NOS-T revealed required capabilities for resilient distributed observing-system experimentation: secure multi-user access, reliable persistent messaging, automated session recovery, governed information exchange, and coordinated scenario time control.
The Snow Observing Strategy (SOS) project demonstrates NOS-T capabilities in an applied Earth science workflow spanning mission-planning and satellite-simulation applications executed at Arizona State University (ASU), NOS-T services hosted on NASA’s Science Cloud, and NASA Land Information System forecasting workflows running on the NASA Center for Climate Simulation Discover supercomputer. Within this distributed setup, NOS-T coordinated a 2024-2025 Missouri River Basin snow campaign, selecting high-reward synthetic radar observations that improved snow water equivalent estimation relative to a passive-microwave baseline. A second SOS campaign replayed the 2018-2019 snow season, reproducing the model-testbed exchange with event-driven synchronization and unattended service-account authentication. Across both campaigns, NOS-T sustained long-duration execution with zero message loss, automated recovery from network disconnections, and low-latency coordination sufficient to keep distributed applications synchronized with external model execution.
The resulting NOS-T capability set provides a practical model for future observing mission requirements: secure participation across organizations, reliable exchange among heterogeneous systems, recoverable long-duration operations, shared interface conventions, and explicit coordination of scenario time. By demonstrating these needs before implementation, NOS-T helps teams refine and compare observing strategies, identify interface requirements, and mature operational concepts of distributed mission architectures.