A new method for detection of cirrus overlapping water clouds and determination of their optical properties

被引:68
作者
Chang, FL
Li, ZQ
机构
[1] Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA
[2] Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA
关键词
D O I
10.1175/JAS3578.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer ( MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible ( 0.65 mu m) and infrared ( 11 mu m) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth <similar to 4 ( emissivity <similar to 0.85). For more than two-layer clouds, its validity depends on the thickness of the upper-layer cloud. A preliminary validation is conducted by comparing against ground-based active remote sensing data. Pixel-by-pixel retrievals and error analyses are presented. It is demonstrated that retrievals based on a single-layer assumption can result in systematic biases in the retrieved cloud top and optical properties for overlapped clouds. Such biases can be removed or lessened considerably by applying the new algorithm.
引用
收藏
页码:3993 / 4009
页数:17
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