2000
DOI: 10.1029/2000jd900146
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Effective radiative properties of bounded cascade nonabsorbing clouds: Definition of the equivalent homogeneous cloud approximation

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Cited by 36 publications
(42 citation statements)
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“…When POLDER considers a cloudy pixel at a 6 km × 7 km resolution, MODIS with a pixel resolution of 1 km × 1 km accounts for a part of the sub-pixel variability. The convex nature of the reflectance-COT relationship implies that the mean COT of two cloudy pixels is larger than the effective COT derived from the mean reflectance of the two pixels (Cahalan, 1994;Szczap et al, 2000). Therefore, COT retrieved from the average reflectance of the pixels is smaller than the linear average value.…”
Section: Impact Of the Sensor Spatial Resolutionmentioning
confidence: 99%
See 1 more Smart Citation
“…When POLDER considers a cloudy pixel at a 6 km × 7 km resolution, MODIS with a pixel resolution of 1 km × 1 km accounts for a part of the sub-pixel variability. The convex nature of the reflectance-COT relationship implies that the mean COT of two cloudy pixels is larger than the effective COT derived from the mean reflectance of the two pixels (Cahalan, 1994;Szczap et al, 2000). Therefore, COT retrieved from the average reflectance of the pixels is smaller than the linear average value.…”
Section: Impact Of the Sensor Spatial Resolutionmentioning
confidence: 99%
“…Due to horizontal cloud inhomogeneities, the retrieved COT can be over or under estimated depending on cloud types, sensor resolution and observation geometries. For low spatial resolution, due to the so-called plan-parallel biases (Cahalan, 1994;Szczap et al, 2000), COT is generally underestimated. Observations of liquid clouds from AVHRR or POLDER show an important decrease in retrieved COT in forward directions, especially at oblique sun (Loeb and Coakley, 1998;Buriez et al, 2001), which is darkened by cloud-side shadowing in forward scattering viewing geometry.…”
Section: Introductionmentioning
confidence: 99%
“…These biases depend at least, on the cloud coverage and on the variability of cloud optical depth or water content. This variability is quantified by an inhomogeneity parameter, often defined as the standard deviation normalized by the mean of the studied quantity (Szczap et al, 2000;Carlin et al, 2002;Oreopoulos and Cahalan, 2005;Sassen et al, 2007;Hill et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…To describe the amplitude of the optical depth for 1-D and 2-D overcast cloud, Szczap et al (2000) defined the inhomogeneity parameter of optical depth ρ τ . For 3-D broken fields, this parameter is defined according to…”
Section: Control Of the Mean And Of The Inhomogeneity Parametermentioning
confidence: 99%
“…We simulated water clouds with a constant effective radius of 10 m, a mean optical thickness of =10. We generated five different clouds by modifying the scale of spectral correction L (1 or 5km), the heterogeneity parameter, which is the product of the standard deviation and the mean optical thickness, = / [4] (0.7, 1.0), the fractional cloud cover cf (1.0, 0.7) and the cloud spatial distributions (S1 and S2). Note that, so far, we have only treated cases with optical thickness heterogeneity without including microphysical variabilities.…”
Section: Simulated Cloud Fieldsmentioning
confidence: 99%