A better understanding of cloud optical thickness derived from the passive sensors MODIS/AQUA and POLDER/PARASOL in the A-Train constellation

Zeng, S.; Cornet, Céline; Parol, Frédéric; Riédi, J.; Thieuleux, F.

doi:10.5194/acp-12-11245-2012

Cited by 36 publications

(28 citation statements)

References 44 publications

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“…On the contrary, we can notice an increase of the retrieved optical thickness value in the backscatter direction (relative bias ranging from +3% for the flat cloud, +43% for the bumpy cloud and +21% for the fractional cloud). This angular behavior was already simulated by several authors at the resolution of 1 km Varnai, 2000;Iwabuchi and Hayasaka, 2002;Zinner and Mayer, 2006) and agrees pretty well with POLDER observations (Buriez et al, 2001;Zeng et al, 2012). In the backscatter 10 directions, the cloud sides illuminated by the sun making the cloud brighter than in the forward direction where, on the contrary, cloud sides are in the shadow (Varnai and Davies, 1999).…”

Section: Description Of the Synthetic Generated Clouds And Radiative supporting

confidence: 73%

“…In the latter, the plane-parallel bias and 3D cloud effects were observed in the COT values retrieved from multi-angle measurements under oblique solar illumination, lower COT were 20 retrieved in the forward viewing direction and larger COT in the backward viewing direction (Figure 8 and 9 in Zeng et al (2012)). Reflectances simulations from known cloud properties help to understand quantitatively the errors or biases on the retrieved cloud properties.…”

Section: Introductionmentioning

confidence: 99%

“…Comparisons with MODIS cloud products were analyzed for cloud fraction in Zeng et al (2011), for cloud phase in Zeng et al (2013) and cloud optical thickness in Zeng et al (2012). In the latter, the plane-parallel bias and 3D cloud effects were observed in the COT values retrieved from multi-angle measurements under oblique solar illumination, lower COT were 20 retrieved in the forward viewing direction and larger COT in the backward viewing direction (Figure 8 and 9 in Zeng et al (2012)).…”

Section: Introductionmentioning

confidence: 99%

“…several radiometers such as AVHRR (Loeb and Coakley, 1998), MODIS (Varnai and Marshak, 2002) and POLDER (Buriez et al, 2001;Zeng et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Cloud heterogeneity effects on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

Cornet¹,

C-Labonnote²,

Szczap³

et al. 2017

Preprint

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Abstract. Simulations of total and polarized cloud reflectance angular signatures such as the ones measured by the multiangular and polarized radiometer POLDER3/PARASOL are used to evaluate cloud heterogeneity effects on cloud parameter retrievals. Effects on optical thickness, cloud albedo, effective radius and variance of the cloud droplet size distribution and aerosol above cloud optical thickness are analyzed. Three different clouds having the same mean optical thicknesses were 15 generated: the first one with a flat top, the second one with a bumpy top and the last one with a fractional cloud cover. At small scale (50 m), for oblique solar incidence, the illumination effects lead to higher total but also polarized reflectances.The polarized reflectances even reach values that cannot be predicted by the 1D homogeneous cloud assumption. At the POLDER scale (7 km x 7 km), the angular signature is modified by a combination of the plane-parallel bias and the shadowing and illumination effects. In order to quantify effects of cloud heterogeneity on operational products, we ran the 20 POLDER operational algorithms on the simulated reflectances to retrieve the cloud optical thickness and albedo. Results show that the cloud optical thickness is greatly affected: biases can reach up to -70%, -50% or +40% for backward, nadir and forward viewing directions respectively. Concerning the cloud albedo, the errors are smaller, between -4.7% for solar incidence angle of 20° and up to about 8% for solar incidence angle of 60°. We also tested the heterogeneity effects on new algorithms that allow retrieving cloud droplet size distribution and cloud top pressures and also aerosol above clouds. 25Contrarily to the bi-spectral method, the retrieved cloud droplet size parameters are not significantly affected by the cloud heterogeneity, which proves to be a great advantage of using polarized measurements. However the cloud top pressure obtained from molecular scattering in the forward direction can be biased up to 120 hPa (around 1 km). Concerning the aerosol optical thickness (AOT) above cloud, the results are different depending on the available angular information. Above the fractional cloud, when only side scattering angles are available, the AOT can be underestimated because of the plane-30 parallel bias. For solar zenith angle of 60°, on contrary, it is overestimated because the polarized reflectances are increased in forward directions.Atmos. Meas. Tech. Discuss., https://doi

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Section: Description Of the Synthetic Generated Clouds And Radiative supporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…several radiometers such as AVHRR (Loeb and Coakley, 1998), MODIS (Varnai and Marshak, 2002) and POLDER (Buriez et al, 2001;Zeng et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cloud heterogeneity effects on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

Cornet¹,

C-Labonnote²,

Szczap³

et al. 2017

Preprint

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“…4b, we show the two-dimensional histogram of the pixel number as a function of relative CDNC differences and relative r e differences between 3.7 µm and 2.1 µm bands. We selected overcast clouds over ocean for our analysis because of fewer uncertainties on the retrievals of τ and r e (Wolters et al, 2010;Zeng et al, 2012). From this figure, we see that most of the CDNC differences decrease when r e differences decrease.…”

Section: Impact Of Cloud Entrainment and Drizzlingmentioning

confidence: 85%

Study of global cloud droplet number concentration with A-Train satellites

et al. 2014

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Abstract. Cloud droplet number concentration (CDNC) is an important microphysical property of liquid clouds that impacts radiative forcing, precipitation and is pivotal for understanding cloud-aerosol interactions. Current studies of this parameter at global scales with satellite observations are still challenging, especially because retrieval algorithms developed for passive sensors (i.e., MODerate Resolution Imaging Spectroradiometer (MODIS)/Aqua) have to rely on the assumption of cloud adiabatic growth. The active sensor component of the A-Train constellation (i.e., Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)/CALIPSO) allows retrievals of CDNC from depolarization measurements at 532 nm. For such a case, the retrieval does not rely on the adiabatic assumption but instead must use a priori information on effective radius (r e ), which can be obtained from other passive sensors.In this paper, r e values obtained from MODIS/Aqua and Polarization and Directionality of the Earth Reflectance (POLDER)/PARASOL (two passive sensors, components of the A-Train) are used to constrain CDNC retrievals from CALIOP. Intercomparison of CDNC products retrieved from MODIS and CALIOP sensors is performed, and the impacts of cloud entrainment, drizzling, horizontal heterogeneity and effective radius are discussed. By analyzing the strengths and weaknesses of different retrieval techniques, this study aims to better understand global CDNC distribution and eventually determine cloud structure and atmospheric conditions in which they develop. The improved understanding of CDNC can contribute to future studies of global cloud-aerosolprecipitation interaction and parameterization of clouds in global climate models (GCMs).

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View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

Horváth

Chellappan

Deneke

2014

J. Geophys. Res. Atmos.

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We investigated the view angle dependence of domain mean Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) and that of corresponding cloud optical thickness, effective radius, and liquid cloud fraction as proxy for plane-parallel retrieval biases. Independent Advanced Microwave Scanning Radiometer-EOS LWP was used to corroborate that the observed variations with sun-view geometry were not severely affected by seasonal/latitudinal changes in cloud properties. Microwave retrievals showed generally small (<10%) cross-swath variations. The view angle (cross-swath) dependence of MODIS optical thickness was weaker in backscatter than forward scatter directions and transitioned from mild ∩ shape to stronger ∪ shape as heterogeneity, sun angle, or latitude increased. The 2.2 μm effective radius variations always had a ∪ shape, which became pronounced and asymmetric toward forward scatter in the most heterogeneous clouds and/or at the lowest sun. Cloud fraction had the strongest and always ∪-shaped view angle dependence. As a result, in-cloud MODIS cloud liquid water path (CLWP) showed surprisingly good view angle (cross-swath) consistency, usually comparable to that of microwave retrievals, due to cancelation between optical thickness and effective radius biases. Larger (20-40%) nadir-relative increases were observed in the most extreme heterogeneity and sun angle bins, that is, typically in the polar regions, which, however, constituted only 3-8% of retrievals. The good consistency of MODIS in-cloud CLWP was lost for gridbox mean LWP, which was dominated by the strong cloud fraction increase with view angle. More worryingly, MODIS LWP exhibited significant and systematic absolute increases with heterogeneity and sun angle that is not present in microwave LWP.

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A better understanding of cloud optical thickness derived from the passive sensors MODIS/AQUA and POLDER/PARASOL in the A-Train constellation

Cited by 36 publications

References 44 publications

Cloud heterogeneity effects on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

Cloud heterogeneity effects on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

Study of global cloud droplet number concentration with A-Train satellites

View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

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