Volunteer Develops AI Tool for NASA Noctilucent Cloud Project

• NASA-supported Space Cloud Watch project tracks noctilucent clouds (NLCs) to study shifts in weather patterns.
• Volunteer Namai Chandra created a machine learning tool to help participants and researchers distinguish NLCs from similar-looking lower-altitude clouds.
• The new pipeline automates screening while maintaining human review for ambiguous images.

Noctilucent Clouds (NLCs)

• Often called "night-shining" clouds, they scatter sunlight after sunset or before sunrise, appearing as silvery glows.
• Scientists are observing changes in NLC frequency and altitude, which may indicate long-term shifts in atmospheric or weather patterns.
• Distinguishing real NLCs from visual look-alikes has historically created a significant workload for project leaders due to manual verification requirements.

The New Identification Tool

• Namai Chandra collaborated with project scientists Drs. Chihoko Cullens and Brentha Thurairajah to develop the solution.
• The system architecture includes:
  • Image pre-screening.
  • Automated cloud classification.
  • Confidence-based routing, which flags images requiring expert human judgment.
• The tool is currently available to all contributors, allowing them to verify their observations before submission.