10.6084/m9.figshare.8947400.v1 Jonathan Hobbs Jonathan Hobbs Amy J. Braverman Amy J. Braverman Eric J. Fetzer Eric J. Fetzer Hai Nguyen Hai Nguyen Kyo Lee Kyo Lee Ali Behrangi Ali Behrangi Joaquim Teixeira Joaquim Teixeira Kelsey Foster Kelsey Foster Simulation-Based Uncertainty Quantification for Level 2 Retrievals ESIP 2019 ESIP Summer 2019 Uncertainty Quantification Remote Sensing AIRS Atmospheric Sciences 2019-07-23 19:47:40 Poster https://esip.figshare.com/articles/poster/Simulation-Based_Uncertainty_Quantification_for_Level_2_Retrievals/8947400 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.<div><br></div>