Evaluating nonlinear maximum likelihood optimal estimation uncertainty in cloud and aerosol remote sensing
Abstract Uncertainty estimates are important when retrieving properties of clouds and aerosols from satellites measurements. These measurements must be interpreted using a form of inverse theory, such as optimal estimation. In atmospheric remote sensing these inverse methods often assume that the fo...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Wiley
2020-08-01
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Series: | Atmospheric Science Letters |
Subjects: | |
Online Access: | https://doi.org/10.1002/asl.980 |