Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6)

Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6)

Uncertainty quantification (UQ) in weather and climate models is required to assess the sensitivity of their outputs to various parameterization schemes and thereby improve their consistency with observations. Herein, we present an efficient UQ and Bayesian inference for the cloud parameters of the...

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Bibliographic Details
Main Authors: Raju Pathak, Hari Prasad Dasari, Samah El Mohtar, Aneesh C. Subramanian, Sandeep Sahany, Saroj Kanta Mishra, Omar Knio, Ibrahim Hoteit
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Climate
Subjects:
climate modeling
uncertainty quantification
Bayesian inference
cloud parameters
parameterization schemes
Online Access:https://www.frontiersin.org/articles/10.3389/fclim.2021.670740/full

Internet

https://www.frontiersin.org/articles/10.3389/fclim.2021.670740/full

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