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Simulation-Based Uncertainty Quantification for Level 2 Retrievals

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posted on 23.07.2019 by Jonathan Hobbs, Amy J. Braverman, Eric J. Fetzer, Hai Nguyen, Kyo Lee, Ali Behrangi, Joaquim Teixeira, Kelsey Foster
This work develops methodology, software, and practices for remote sensing retrieval Monte Carlo simulation experiments. We formulate a probabilistic and computational pipeline to resemble the data-generating process for Level 1 and Level 2 satellite products. We illustrate the implementation for the Atmospheric Infrared Sounder (AIRS). This poster was presented in July 2019 at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma Washington.

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NNH16ZDA001N-AIST

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