A flexible three-dimensional stratocumulus, cumulus and cirrus cloud generator (3DCLOUD) based on drastically simplified atmospheric equations and Fourier transform framework

Szczap, Frédéric; Gour, Yahya; Fauchez, Thomas; Cornet, Céline; Faure, Thierry; Jourdan, Olivier; Dubuisson, P.

doi:10.5194/gmdd-7-295-2014

Cited by 2 publications

(1 citation statement)

References 52 publications

(69 reference statements)

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“…The mean COTs, mean volume extinction coefficients, and the inhomogeneity factors of the regional cirrus cases are listed in Table . The inhomogeneity factor was calculated as the ratio of the standard deviation of COT to the domain‐averaged COT (Szczap et al, ). Given that the inhomogeneity factor was almost the same for Case 1 (M1 and T1) and Case 2 (M2 and T2), Case 2 was optically thicker than Case 1.…”

Section: Inhomogeneous Cirrus Cloudsmentioning

confidence: 99%

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3‐D Radiative Effects, and Cloud Inhomogeneity

et al. 2018

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For inhomogeneous cirrus clouds, cloud optical thickness (COT) and effective diameter (De) provided by the Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 cloud products are associated with errors due to the single habit assumption (SHA), independent pixel assumption (IPA), photon absorption effect (PAE), and plane‐parallel assumption (PPA). SHA means that every cirrus cloud is assumed to have the same shape habit of ice crystals. IPA errors are caused by three‐dimensional (3D) radiative effects. PPA and PAE errors are caused by cloud inhomogeneity. We proposed a method to single out these different errors. These errors were examined using the Spherical Harmonics Discrete Ordinate Method simulations done for the MODIS 0.86 μm and 2.13 μm bands. Four midlatitude and tropical cirrus cases were studied. For the COT retrieval, the impacts of SHA and IPA were especially large for optically thick cirrus cases. SHA errors in COT varied distinctly with scattering angles. For the De retrieval, SHA decreased De under most circumstances. PAE decreased De for optically thick cirrus cases. For the COT and De retrievals, the dominant error source was SHA for overhead sun whereas for oblique sun, it could be any of SHA, IPA, and PAE, varying with cirrus cases and sun‐satellite viewing geometries. On the domain average, the SHA errors in COT (De) were within −16.1%–42.6% (−38.7%–2.0%), whereas the 3‐D radiative effects‐ and cloud inhomogeneity‐induced errors in COT (De) were within −5.6%–19.6% (−2.9%–8.0%) and −2.6%–0% (−3.7%–9.8%), respectively.

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Section: Inhomogeneous Cirrus Cloudsmentioning

confidence: 99%

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3‐D Radiative Effects, and Cloud Inhomogeneity

et al. 2018

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Impacts of cloud heterogeneities on cirrus optical properties retrieved from spatial thermal infrared radiometry

Fauchez¹,

Dubuisson²,

Cornet³

et al. 2014

Preprint

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Abstract. This paper presents a study, based on simulations, of the impact of cirrus cloud heterogeneities on the retrieval of cloud parameters (optical thickness and effective diameter) for the Imaging Infrared Radiometer (IIR) on board CALIPSO. Cirrus clouds are generated by the stochastic model 3DCLOUD for two different cloud fields and for several averaged cloud parameters. One is obtained from a cirrus observed on the 25 May 2007 during the airborne campaign CIRCLE-2 and the other is a cirrus uncinus. The radiative transfer is simulated with the code 3DMCPOL. To assess the errors due to cloud heterogeneities, two related retrieval algorithms are used: (i) The split window technique to retrieve the ice crystal effective diameter and (ii) an algorithm similar to the IIR operational algorithm to retrieve the effective emissivity and the effective optical thickness. Differences between input parameters and retrieved parameters are compared as a function of different cloud properties such as the mean optical thickness, the heterogeneity parameter and the effective diameter. The optical thickness heterogeneity for each 1 km × 1 km observation pixel is represented by the optical thickness standard deviation computed using 100 m × 100 m subpixels. We show that optical thickness heterogeneity may have a strong impact on the retrieved parameters, mainly due to the Plane Parallel Approximation (PPA). In particular, for cirrus cloud with ice crystal size of approximately 10 μm, the averaged error on the retrieved effective diameter is about 2.5 μm (~ 25%) and on the effective optical thickness of about −0.20 (~ 12%). Then, these biases decrease with the increase of the ice effective size due to a decrease of the cloud absorption and thus of the PPA bias. Cloud heterogeneity effects are much more higher than other possible sources of error. They become larger than the retrieval incertitude of the IIR algorithm from a standard deviation of the optical thickness, inside the observation pixel, superior to 1.

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A flexible three-dimensional stratocumulus, cumulus and cirrus cloud generator (3DCLOUD) based on drastically simplified atmospheric equations and Fourier transform framework

Cited by 2 publications

References 52 publications

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3‐D Radiative Effects, and Cloud Inhomogeneity

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3‐D Radiative Effects, and Cloud Inhomogeneity

Impacts of cloud heterogeneities on cirrus optical properties retrieved from spatial thermal infrared radiometry

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