Uncertainty analysis of cloud properties retrieved from MICROBASE

 
Poster PDF

Authors

Chuanfeng Zhao — Beijing Normal University
Shaocheng Xie — Lawrence Livermore National Laboratory
Maureen Dunn — Brookhaven National Laboratory
Michael Jensen — Brookhaven National Laboratory

Category

Cloud Properties

Description

Quantification of uncertainty in cloud retrievals is important for cloud modeling studies. In this study, we perform an uncertainty analysis on the cloud properties retrieved from MICROBASE, the ARM baseline retrieval. Two types of uncertainties are studied. One is associated with uncertainties in defining those parameters that are used in the MICROBASE retrievals. The other one is related to uncertainties in the input data that are required to run the MICROBASE. The analysis is done by randomly perturbing several key parameters and required quantities within a range constrained by observations. In this poster, we will show preliminary results of this study based on ARM Southern Great Plains March 2000 data.