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Fuzhong Weng

land ( Weng et al. 2001 ). Prior to this model development, constant emissivity values were used for unfrozen land, snow cover, and sea ice in the NOAA global data assimilation system. Modeling the emissivity for such heterogeneous surfaces is a daunting task. In the case of snow it requires an understanding of radiative transfer theory for dense media ( Weng et al. 2001 ). For example, a more physically based emissivity model was developed for snow, which includes the volumetric scattering from

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Graeme L. Stephens and Christian D. Kummerow

sounding channels in addition to MW window channels for retrieving profiles of precipitation over both water and land. Emission methods applied to optically thin media are commonly formulated using very simplistic expressions of radiative transfer often posed in terms of the transfer through a single layer in the form where τ is the optical depth determined by absorption, I below is the radiance of the surface and/or atmosphere below the cloud layer, and μ is cosine of the view angle. Here B ( T

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

are not applicable over land because of the strong and highly variable microwave emission of the land surface. The emission from ocean surfaces is less variable, so cloud LWP can be estimated from satellite-observed microwave radiances. However, LWP retrieval accuracy is affected by the sea surface temperature, surface wind speed, atmospheric precipitable water vapor, and radiometric calibration while uncertainties in the absorption coefficients used in the microwave radiative transfer model also

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Chinnawat Surussavadee and David H. Staelin

. Rosenkranz’s efficient radiative transfer algorithm TBSCAT ( Rosenkranz 2002 ) that incorporated improved transmittance models ( Liebe et al. 1992 ; Rosenkranz 1998 ), and the complex permittivities for water and ice given by Liebe et al. (1991) and Hufford (1991) , respectively. Sea surface emissivity was computed using FASTEM ( English and Hewison 1998 ), which incorporates geometric optics, Bragg scattering, and foam effects. Sea surface temperatures and 10-m winds were provided by MM5, and land

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K. Franklin Evans

based on the spherical harmonics discrete-ordinate method (SHDOM; Evans 1998 ), which is a three-dimensional (3D) radiative transfer model. SHDOM was chosen for this 1D application because it can be faster than the standard discrete ordinate method. Owing to the complexities of the 3D model and its adaptive grid, a true adjoint was not created; instead, the adjoint was performed by application of the tangent linear model for each element of the input vector. This use of SHDOM for 1D radiative

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Philippe Lopez

convective precipitation over land in a global model. Quart. J. Roy. Meteor. Soc. , 130 , 3119 – 3137 . Benedetti , A. , G. L. Stephens , and J. M. Haynes , 2003 : Ice cloud microphysics retrievals from millimeter radar and visible optical depth using an estimation theory approach. J. Geophys. Res. , 108 . 4335, doi:10.1029/2002JD002693 . Benedetti , A. , P. Lopez , P. Bauer , and E. Moreau , 2005 : Experimental use of TRMM precipitation radar observations in 1D+4D

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Peter M. Norris and Arlindo M. da Silva

generalization of Slingo (1987) . The core of this scheme is a quadratic variation of cloud fraction, f , with relative humidity, RH, above a critical value, RH 0 , approaching complete cloud cover at 100% RH: The tuned version used in the GEOS-4 sets RH 0 = 87%. For mid–high clouds (<750 hPa) RH 0 is increased with a positive Brunt–Väisälä frequency to account for reduced subgrid-scale variability under stable conditions. For low clouds (≥750 hPa) RH 0 is reduced to 77% over snow-free land to account

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Fuzhong Weng, Tong Zhu, and Banghua Yan

developed by the Met Office, United Kingdom ( English and Takashima 1998 ) produced better results in assimilating the AMSU data, especially at high latitudes. A microwave emissivity model was developed for land surfaces ( Weng et al. 2001 ) and has resulted in major impacts in improving uses of microwave data over land and in polar regions. Critical issues remain in simulating the emissivity spectra over extreme surface conditions and at infrared wavelengths. Evidence of these model deficiencies comes

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