382 Evaluation of Multi-layer Cloud Property Retrievals from Optimal Estimation and Bayesian Retrieval Algorithms

Monday, 11 January 2016
Yifeng Ding, Texas A&M University, College Station, TX; and P. Yang and S. L. Nasiri

Three physical and radiative cloud properties, namely, optical thickness (), effective diameter (De), and cloud top height(h) can be simultaneously inferred from IR radiances for multi-layer cloud cases. The retrieval algorithm implementation is based on a computationally efficient radiative transfer model and spaceborne measurements of narrowband infrared (IR) radiances at the top of the atmosphere. This study focuses on the evaluation of the retrieval results derived from two different algorithms, optimal estimation (OE) algorithm and Bayesian retrieval algorithm. Both of the two methods are able to offer comprehensive error analysis and quality flags. The evaluation results can potentially useful for retrieving the multi-layer clouds properties, a research subject that receives little attention. This presentation will discuss the pros and cons of retrieving cloud properties from the aforesaid retrieval algorithms.
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