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K. Franklin Evans

linear, and adjoint models. Section 3 describes testing of the forward, tangent linear, and adjoint models, and shows examples of the adjoint sensitivities for cloud model fields. 2. The SHDOMPP and SHDOMPPDA algorithms a. SHDOMPP SHDOMPP calculates unpolarized radiative transfer in a plane-parallel medium for either collimated solar and/or thermal emission sources of radiation. The optical properties of the medium input to SHDOMPP are assumed to be uniform in each layer, which is different from

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Peter M. Norris and Arlindo M. da Silva

assimilating clear-sky fluxes to determine temperature and moisture profiles. This approach is still very new, but progress is being made ( Janisková et al. 2002 ; Greenwald et al. 2004 ; Chevallier et al. 2004 ). The challenge is not only to have a forward model that accurately accounts for cloud optical properties, but also that passive radiative observations still only partially constrain the cloud properties (especially in multilayer cloud schemes, which are common). Janisková et al. conduct some

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Qing Yue, K. N. Liou, S. C. Ou, B. H. Kahn, P. Yang, and G. G. Mace

. 2004 ) for the speedy computation of clear-column transmittances in numerical weather prediction models, and a thin cirrus radiative transfer parameterization based on prescribed size and habit distribution models and the associated scattering and absorption properties. We use this model to simulate infrared spectral radiances, and apply it to the AIRS data to generate clear and thin cirrus cloud brightness temperature (BT) spectra. Cirrus optical depth and cloud microphysical properties, including

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Graeme L. Stephens and Christian D. Kummerow

cld ) is the Planck blackbody function defined by a “cloud” temperature T cld . All emission methods revert to determining the optical depth τ from which other information about the cloud and precipitation is inferred. It will become apparent from the examples below that the largest source of uncertainty in these methods arise more from model parameters, like I below and B ( T cld ) in (2) , than from radiance measurement uncertainties. a. Cirrus cloud optical properties from split

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Ruiyue Chen, Fu-Lung Chang, Zhanqing Li, Ralph Ferraro, and Fuzhong Weng

evolution of cloud systems and affects water redistribution ( Stephens 1999 ). The effect of boundary layer clouds is so strong that even small changes in their optical and microphysical properties are likely to have major consequences for climate change. The liquid water path (LWP) is an important cloud microphysical property that determines the climatic effects of boundary layer clouds. For example, Greenwald et al. (1995) found that a 0.05 kg m −2 increase in LWP (for LWP < 0.2 kg m −2 ) results

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Christopher W. O’Dell, Peter Bauer, and Ralf Bennartz

quite similar. This is probably due to the larger number of strongly convective cases in the summer profiles generating frozen precipitation at relatively high altitudes, roughly matching the lower-altitude frozen precipitation in the winter profiles. To conduct radiative transfer simulations, optical properties of the relevant atmospheric variables were calculated at the SSM/I frequencies. The profiles of pressure, temperature, water vapor, cloud liquid water, and cloud ice were used to obtain

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Ronald M. Errico, George Ohring, Fuzhong Weng, Peter Bauer, Brad Ferrier, Jean-François Mahfouf, and Joe Turk

) measurements are affected by sensitivity to the highly variable land surface emissivity and similar optical properties of cloud water and light rainfall that limit the detectability and retrieval accuracy of either component. Current observations also lack sensitivity to drizzle and snowfall. Specific workshop recommendations regarding observations include 1) expanding the use of ARM site observations and conducting well-planned field campaigns to provide better validation of satellite cloud and

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Fuzhong Weng

-phase particles, or the so-called mixed-phase clouds. For an ice-phase cloud, a comprehensive database of the single-scattering properties of ice particles with various geometries has been developed ( Yang et al. 2005 ). For a liquid-phase cloud, the droplets are simulated using a modified gamma size distribution with an effective radius as a function of rain rate for precipitating clouds. For nonprecipitating clouds, cloud optical properties are computed from cloud water content and effective radius ( Liu

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Philippe Lopez

, V. I. , and K. Sassen , 1998 : Cirrus cloud simulation using explicit microphysics and radiation. Part II: Microphysics, vapor and ice mass budgets, and optical and radiative properties. J. Atmos. Sci. , 55 , 1822 – 1845 . Krishnamurti , T. N. , H. S. Bedi , and K. Ingles , 1993 : Physical initialization using SSM/I rain rates. Tellus , 45A , 247 – 269 . Kuo , H. L. , 1965 : On the formation and intensification of tropical cyclones through latent heat release by cumulus

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Fuzhong Weng, Tong Zhu, and Banghua Yan

. Community radiative transfer model (CRTM) For a plane-parallel atmosphere, the radiance vector can be derived from and where 𝗠 is the phase matrix; I = [ I , Q , U , V ] T ; B ( T ) is the Planck function at a temperature T ; F 0 is the solar spectral constant; μ 0 and ϕ 0 are the cosine of zenith angle and the azimuthal angle of sun; μ and ϕ are the cosine of zenith angle and the azimuthal angle at scattering direction; ϖ is the single-scattering albedo; and τ is the optical

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