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Tristan S. L’Ecuyer and Greg McGarragh

framework that uses retrieved cloud properties as input to broadband radiative transfer calculations to simulate radiative flux profiles through the atmosphere; however, each makes trade-offs between spatial resolution, temporal sampling, spatial coverage, and the quality of the its input datasets. The Hydrologic Cycle and Earth’s Radiation Budget (HERB) algorithm, described in detail in L’Ecuyer and Stephens (2003 , hereafter LS03 , 2007) , strikes its own compromise between spatial resolution

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Richard H. Johnson, Paul E. Ciesielski, Tristan S. L’Ecuyer, and Andrew J. Newman

-dimensional structure of clouds and precipitation in the atmosphere. Aerosols are prescribed using a static climatology of monthly distributions from the Global Aerosol Climatology Project (GACP). These fields provide input to a broadband radiative transfer model that simulates vertical profiles of upwelling and downwelling longwave and shortwave radiative fluxes and their convergence defines the vertical profile of atmospheric radiative heating Q R . A comprehensive description of the uncertainty characteristics

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T. N. Krishnamurti, Arindam Chakraborty, and A. K. Mishra

over the entire tropics. This appears to be a major mismatch between model and TRMM-based results. The models place the level of maximum heating between 9 and 14 km in most places. A lot of those are nonrainy areas, such as the subtropical highs. The regions colored white in the TRMM-based estimates are nonrainy areas where no data were available. Over these regions the discrepancies arise from other components of physical parameterization such as the radiative transfer. These are large systematic

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Wei-Kuo Tao, Stephen Lang, Xiping Zeng, Shoichi Shige, and Yukari Takayabu

Cumulus Ensemble (GCE) model] simulations but also include profiles from sounding budget studies. In GPROF, CRM-simulated vertical profiles of hydrometeors (and associated LH) that have radiative characteristics consistent with a given set of multispectral microwave radiometric observations are composited to create (retrieve) a best estimate of the observed profiles ( Olson et al. 1999 ; Grecu et al. 2009 ). The HH algorithm 3 estimates LH profiles as a function of the vertical derivative of the

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Mircea Grecu, William S. Olson, Chung-Lin Shie, Tristan S. L’Ecuyer, and Wei-Kuo Tao

, 2007) . Briefly, HERB synthesizes ice cloud microphysical property information from VIRS; liquid cloud properties, precipitation profiles, SST, and water vapor retrievals from the TRMM TMI; and vertical profiles of temperature and humidity from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalyses to characterize the three-dimensional structure of clouds and precipitation in the atmosphere. These provide input to a broadband radiative transfer model that simulates vertical

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Shoichi Shige, Yukari N. Takayabu, Satoshi Kida, Wei-Kuo Tao, Xiping Zeng, Chie Yokoyama, and Tristan L’Ecuyer

the reference pressure (1000 mb), C p the specific heat of dry air at constant pressure, and R the gas constant for dry air. The overbars denote horizontal averages. The Q 1 can be directly related to the contributions of cloud effects, which can be explicitly estimated by CRMs, by The primes indicate deviations from the horizontal averages; ρ is the air density and Q R the cooling/heating rate associated with radiative processes. The subgrid-scale (smaller than the cloud scale

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Manuel D. Zuluaga, Carlos D. Hoyos, and Peter J. Webster

algorithm does not produce estimates of heating. However, on a large-scale view the net amount of LH in the absence of surface precipitation is very small. The second dataset is derived using a Bayesian approach with a database of hydrometeor profiles and their computed brightness temperatures ( Olson et al. 1999 ). In the algorithm, GCE simulations, coupled to a radiative transfer code, are used to generate a large supporting database of simulated precipitation/LH profiles and corresponding upwelling

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