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Philippe Lopez

latent heat of vaporization, C is the rate of large-scale condensation/evaporation, and Q r is the radiative heating/cooling rate. Primes denote subgrid-scale fluctuations and overbars indicate an averaging of subgrid-scale fluxes over the model grid box. Resolved moist processes are summarized in C while the contribution of subgrid-scale moist processes is included in (∂ /∂ p ) and (∂ /∂ p ). Note that the two latter terms also include contributions from other subgrid-scale phenomena such as

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

based upon model data. However, because NWP models have only a finite horizontal resolution, any subgrid-scale cloud process must be parameterized within the radiative transfer model. Therefore, cloud liquid water and ice contents as well as liquid and frozen precipitation fluxes represent grid box averages. No explicit information on the spatial distribution of these quantities inside the grid box is available other than the profile of cloud fraction. The NWP model cloud fraction is usually

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K. Franklin Evans

output radiative quantities are upwelling and downwelling hemispheric fluxes and mean radiances at the layer boundaries and radiances at specified levels and directions. SHDOMPP represents the radiation field using the source function from which the radiance field can be obtained by integrating the radiative transfer equation. The angular aspects of the source function are represented with spherical harmonics series, while the spatial aspects are represented with a discrete vertical grid. Only cosine

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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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Arthur Y. Hou and Sara Q. Zhang

/or SSM/I rain retrievals using the VCA scheme improves not only precipitation analysis but also related climate parameters such as the upper-tropospheric moisture and top-of-the-atmosphere radiative fluxes. Hou et al. (2004) provided examples of improved hurricane track forecasts and precipitation forecast threat scores using the VCA scheme. However, these early studies were based on limited months of assimilated data. In the following section, we will use four years of the GEOS-3 “TRMM reanalysis

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Ronald M. Errico, Peter Bauer, and Jean-François Mahfouf

developed. Lopez and Moreau (2005) developed a mass-flux convection scheme following Tiedtke (1989) but with several discontinuities removed. The modified nonlinear scheme compares well with the original in terms of surface precipitation, but the Jacobians of the revised scheme are much smoother, increasing significantly the range of validity of the tangent-linear approximation. Tompkins and Janisková (2004) developed a diagnostic cloud scheme as a simplified version of the prognostic cloud scheme

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

greenhouse gases. Bull. Amer. Meteor. Soc. , 87 , 911 – 926 . Clough , S. A. , M. J. Iacono , and J-L. Moncet , 1992 : Line-by-line calculations of atmospheric fluxes and cooling rates: Application to water vapor. J. Geophys. Res. , 97 , 15761 – 15785 . Comstock , J. M. , T. P. Ackerman , and G. G. Mace , 2002 : Ground-based lidar and radar remote sensing of tropical cirrus clouds at Nauru Island: Cloud statistics and radiative impacts. J. Geophys. Res. , 107 . 4714, doi:10

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Fuzhong Weng, Tong Zhu, and Banghua Yan

, surface friction, surface fluxes, and dry convective adjustment. The variational analysis is carried out on a 27-km horizontal resolution domain with 76 × 73 grid points. Before the 4DVAR assimilation, the high-resolution (27 km × 27 km) background fields are created from low resolution (1° × 1°) GDAS fields through interpolation. The assimilation window is 6 h, and the integration time interval is 90 s. 4. Case studies The HVAR scheme is applied in creating the vortex analysis for Hurricanes Katrina

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