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>