OMB Individually Reported
High Resolution Earth and Planetary Atmospheric Predictions using Machine Learning
Low riskExact public inventory row
Description
We are developing a machine learning (ML) tool that can predict high-resolution in situ atmospheric conditions using relatively lower resolution remote data e.g., from an orbiting spacecraft.
Detailed example
Predictions
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Our ML tool could be used to map and track atmospheric cycling on Earth and planetary bodies, not only as a fundamental science tool, but also as a mechanism for tracking planetary weather from orbit.
Controls / human review
ATO: Not reported; PIA: Not published