OMB Individually Reported
Retrieving Aerosol Optical Depth and High Spatial Resolution Ocean Surface Wind Speed From CALIPSO: A Neural Network Approach
Low riskExact public inventory row
Description
This study uses ocean surface wind speed derived from microwave radiometer to train spacebased lidar measurements to measure both wind speed and aerosol optical depth using neural networks.
Detailed example
wind speed and aerosol optical depth
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
This study uses ocean surface wind speed derived from microwave radiometer to train spacebased lidar measurements to measure both wind speed and aerosol optical depth using neural networks.
Controls / human review
ATO: Not reported; PIA: Not published