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K. Franklin Evans, Steven J. Walter, Andrew J. Heymsfield, and Merritt N. Deeter

Introduction The high altitudes and cold temperatures of cirrus clouds contribute to their distinct radiative properties as well as their resistance to adequate characterization. The cold brightness temperatures of cirrus clouds compared to clear skies means they provide a large infrared“greenhouse” effect in addition to reflecting solar flux. Numerical studies have shown that the optical thickness of cirrus clouds determines whether they warm or coolthe atmosphere and surface ( Stephens and

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M. Wendisch, S. Mertes, A. Ruggaber, and T. Nakajima

to calculate spectral scattering and extinction coefficients ofthe aerosol particles and their phase function. Theseaerosol parameters were complemented by several gasspecies and their scattering and absorption properties(cf. Ruggaber et al. 1994). The meteorological parameters (pressure, temperature, and humidity) were takenfrom the measurements during the flight. Thus, the optical description of each layer was mainly based on aset of experimental data. The integrated irradiance and

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Hélène Chepfer, Philippe Goloub, James Spinhirne, Pierre H. Flamant, Mario Lavorato, Laurent Sauvage, Gérard Brogniez, and Jacques Pelon

climate change is accepted in a broad sense but still needs to be asserted more quantitatively ( Hansen et al. 1984 ). Among the missing quantities are the key radiative properties, that is, optical depth and microphysical characteristics, as well as structural parameters, for example, height, geometrical thickness, and geographical coverage. The ice crystal size in cirrus cloud is variable, and the particle shape can be complex. In situ measurements can be used to observe cirrus cloud composition

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James R. Campbell, Simone Lolli, Jasper R. Lewis, Yu Gu, and Ellsworth J. Welton

extinction-to-backscatter value corresponds with greater COD, and the relative distribution shifts within each subsample. We find that 47% (42%) correspond with optically thin cirrus (0.03 < COD ≤ 0.30) and 21% (34%) of the samples reflect relatively opaque clouds with COD > 0.30 at 20 (30) sr. Fig . 1. Histograms of daytime cirrus cloud macrophysical properties at the MPLNET site in 2012 determined using (left) 20- and (right) 30-sr constraints for lidar extinction to backscatter S . Cloud properties

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C. G. Schmitt, J. Iaquinta, and A. J. Heymsfield

application section) for visible wavelengths at cloud top, assuming an optical-depth-0.5 cloud with a sun angle 35° from vertical. For comparison, radiative forcing on the order of 4 W m −2 is expected by the doubling of atmospheric carbon dioxide in greenhouse gas studies ( Cess et al. 1993 ). Spheres of an effective size (referred to as “equivalent spheres”) are often used in substitution for ice particle populations when calculating ice-cloud scattering properties ( Neshyba et al. 2003 ). This is a

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Graeme L. Stephens and C. M. R. Platt

probe. Variance analyses ofthe cloud optical properties indicated that the sampled cloud layers possessed highly variable volume extinctioncoefficients with fractional deviations exceeding 0.5 at most levels, whereas ~the single-scattering albedo and theasymmetry parameter were more uniform along any given level. Variance analyses of the bidirectional reflectedradiation from Sc clouds indicated a variability of cloud reflectance on two distinct horizontal scales, whichcould in turn be related to the

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Andrew K. Heidinger, Christopher O’Dell, Ralf Bennartz, and Thomas Greenwald

similarities with that SOS model. For example, both the SOI and SOS approaches use an iterative method, in place of the adding approach, to integrate the radiative effects of multiple layers together. However, the largest difference between the two approaches is in the computation of the radiative properties of each layer. The SOS model requires that the model layers be optically thin enough that the single-scattering approximation is valid. As explained by Greenwald et al., this requires the SOS model to

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Seung-Hee Ham, Byung-Ju Sohn, Ping Yang, and Bryan A. Baum

perturbations and then CRF can be modified, which is known as cloud feedback . Substantial efforts have been made to understand cloud feedback mechanisms as a consequence of the increase of sea surface temperature (SST) or the increase of the amount of CO 2 in the atmosphere, but there are still significant uncertainties in current general circulation models (GCMs). The uncertainties are largely caused by inaccurate parameterizations or treatments of the formation, growth, optical properties, and vertical

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Christian A. Gueymard

. Henderson-Sellers, 1985: Climatological analysis of Arctic aerosol quantity and optical properties at Resolute, N. W. T. Atmos. Environ., 19, 707–714. Molineaux, B., and P. Ineichen, 1996: On the broad band transmittance of direct irradiance in a cloudless sky and its application to the parameterization of atmospheric turbidity. Sol. Energy, 56, 553–563. Myers, D. R., 1989: Estimates of uncertainty for measured spectra in the SERI spectral solar radiation data base. Sol. Energy, 43, 347

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M. Alcoba, M. Gosset, M. Kacou, F. Cazenave, and E. Fontaine

distributions observed in Benin, West Africa, with optical disdrometers . Geophys. Res. Lett. , 35 , L23807 , doi: 10.1029/2008GL035755 . Nelder , J. A. , and R. Mead , 1965 : A simplex method for function minimization . Comput. J. , 7 , 308 – 313 , doi: 10.1093/comjnl/7.4.308 . Protat , A. , and Coauthors , 2009 : Assessment of CloudSat reflectivity measurements and ice cloud properties using ground-based and airborne cloud radar observations . J. Atmos. Oceanic Technol. , 26 , 1717

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