OMB Individually Reported
Reconstruction of cloud vertical structure
Low riskExact public inventory row
Description
This work explores the feasibility of solving atmospheric remote sensing problems with machine learning using conditional generative adversarial networks (CGANs), implemented using convolutional neural networks. We apply the CGAN to generating two-dimensional cloud vertical structures that would be observed by the CloudSat satellite-based radar, using only the collocated Moderate-Resolution Imaging Spectrometer measurements as input.
Detailed example
Predictions
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Reconstruction of cloud vertical structure
Controls / human review
ATO: Not reported; PIA: Not published