OMB Individually Reported
Development of a Next-Generation Ensemble Prediction System for Atmospheric Composition
Low riskExact public inventory row
Description
The project's goal is to reduce the computational burden of atmospheric composition modeling at the GMAO, by building an AI emulator for the GEOS Composition Forecast model.
Detailed example
Global forecasts of air pollutants
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
The project could lead to significant saving in the computational costs of atmospheric composition forecasts for NASA and could provide the public with longer range probabilistic forecasts of air quality.
Controls / human review
ATO: Not reported; PIA: Not published