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Yefim L. Kogan, Zena N. Kogan, and David B. Mechem

global climate models emphasized a systematic underestimate of the frequency of drizzle events over stratocumulus cloud regimes ( Lau et al. 1996 ). In the current study we evaluate techniques for remote sensing retrieval of important microphysical parameters from marine stratocumulus clouds. Specifically we analyze errors in retrievals of cloud liquid water content ( Q l ) and precipitation flux ( R ) based on three different sets of parameters: (a) radar reflectivity, Z , (b) radar reflectivity

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J. Li, X. Gao, and S. Sorooshian

, primarily over the San Juan Mountains, and the summertime, localized, monsoon-associated convective rainfall, is the main source for the river flow and groundwater recharge. The average annual precipitation varies from more than 130 cm at the high-elevation north to less than 15 cm in the low-elevation southern parts of the basin. Because the basin’s population and economy have grown rapidly, currently the river gains water only above Santa Fe, New Mexico, and loses water farther south. The upper Rio

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Binayak P. Mohanty and Jianting Zhu

1. Introduction Moisture flux across the land–atmosphere boundary (through infiltration, evaporation, and plant transpiration) is an important component of large-scale hydroclimatic processes. Predicting the mean flux rate for a remote sensing footprint or model grid/pixel is usually a primary concern in most practical soil–vegetation–atmospheric transfer (SVAT) models. One of the key land–atmosphere linkages is described by Koster et al. (2004) , whose results from a recent model

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Richard G. Lawford, John Roads, Dennis P. Lettenmaier, and Phillip Arkin

forecast centers and satellite laboratories to produce maps of land surface variables. Collaboration between modeling, observation, and validation groups is needed for a complete description of the analysis errors. Some global product groups do not use data assimilation systems because they feel that current assimilation methods are not sufficiently accurate and prefer other nonlinear methods. At seasonal prediction time scales, boundary conditions such as sea surface temperatures, soil moisture, and

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Song Yang, S-H. Yoo, R. Yang, K. E. Mitchell, H. van den Dool, and R. W. Higgins

1. Introduction It is widely recognized that, in addition to sea surface temperature (SST), soil moisture provides a strong forcing for governing atmospheric processes on various time scales (see reviews in Betts et al. 1996 ; Dirmeyer et al. 1999 ; Yang and Lau 2006 ; Koster et al. 2006 ). In the midlatitude continents, it may be the most important boundary condition during warm seasons (e.g., Koster and Suarez 1995 ; Lau and Bua 1998 ; Koster et al. 2000 ), especially in relatively dry

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Guoxiong Wu, Yimin Liu, Qiong Zhang, Anmin Duan, Tongmei Wang, Rijin Wan, Xin Liu, Weiping Li, Zaizhi Wang, and Xiaoyun Liang

boundary layer, are quite distinct from those over lower-elevated regions (e.g., Liou and Zhou 1987 ; Smith and Shi 1992 ; Shi and Smith 1992 ). While the TP receives strong solar radiation at the surface, the other parts of Asia at such a level are already in the cold middle troposphere. Geographically the TP is located in the subtropics with westerly winds to the north and easterlies to the south in summer, but it provides a barrier to the subtropical westerly jet in winter. Perturbations forced

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