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Sunwook Park and Xiaoqing Wu

monthlong CRM simulations have also conducted by Wu et al. (1998 , 1999) during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) between November 1992 and February 1993 and by Wu et al. (2007) during the ARM SGP intensive observation period (IOP) in 1997. They showed that the CRM-produced data have reasonable agreement with ground-measured and satellite-retrieved data such as temperature, moisture, surface heat fluxes, precipitation, and radiative

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Boutheina Oueslati, Benjamin Pohl, Vincent Moron, Sandra Rome, and Serge Janicot

investigate the role of atmospheric circulation, turbulent and radiative fluxes, and their sensitivity to water vapor and clouds. The paper is structured as follows. Section 2 presents the datasets used in the study and the HW definition retained for the Sahel. Section 3 describes the HW characteristics in terms of frequency, duration, intensity, and spatial extent. Sections 4 and 5 investigate the physical processes controlling warm temperature anomalies, focusing first on the spring 2010 case

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John E. Harries and Claudio Belotti

actually is a quasi steady state. Energy from the sun is absorbed by the earth, and energy from the earth is radiated back to space, so as to maintain a balance between the two at the TOA. Between the arrival and exit of these two streams of energy, a huge array of individual processes cascade the incoming energy down a chain of decreasing energy quality and increasing disorder. The photon stream arrives as a flux of high energy, with relatively few photons, and departs as a larger number of low

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A. Protat, S. A. Young, S. A. McFarlane, T. L’Ecuyer, G. G. Mace, J. M. Comstock, C. N. Long, E. Berry, and J. Delanoë

characterized in terms of radiative effect differences at the surface and the top of the atmosphere ( section 4 ) and of radiative heating-rate profile differences ( section 5 ). Concluding remarks are given in section 6 . 2. Observations and methodology In this paper, 2 yr (2007 and 2008) of ARM ground-based and CloudSat – CALIPSO cloud frequencies of occurrence and radiative fluxes are compared. In what follows, we briefly describe each product used, as well as the strategy adopted for the ground

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David S. Henderson, Tristan L’Ecuyer, Graeme Stephens, Phil Partain, and Miho Sekiguchi

representation of the vertical distribution of cloud properties in radiative flux calculations. New cloud boundary information from these sensors offers the potential to dramatically reduce errors in cloud boundaries that can reach 1 km or more (e.g., Holz et al. 2008 ; Menzel et al. 2008 ; Naud et al. 2005 ). From the sensitivity studies described below, this improved vertical resolution may reduce errors in global estimates of cloud LW forcing by as much as 6 W m −2 . The potential for using this new

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Martin Wild and Erich Roeckner

shortwave and longwave fluxes. In the present study we use the information contained in both surface and top-of-atmosphere (TOA) observations to assess the radiative fluxes simulated in the ECHAM5 GCM. Radiative fluxes in previous versions of the ECHAM model suite have been evaluated in a series of papers from both a satellite and surface point of view ( Roeckner et al. 1992 , 1996 ; Chen and Roeckner 1996 ; Wild et al. 1995a , b , 1998 , 2001 ). The purpose of the present study is to document the

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David A. Rutan, Seiji Kato, David R. Doelling, Fred G. Rose, Le Trang Nguyen, Thomas E. Caldwell, and Norman G. Loeb

more complex than at the TOA, as it requires a radiative transfer model and satellite-derived properties of clouds and aerosols and atmospheric state from either satellites or reanalysis. Underlying assumptions in the radiative transfer model calculations and ancillary input data error increases the uncertainty in the surface radiation budget estimates. Furthermore, it is known that the diurnal cycle of clouds and their contribution to the diurnal cycle of surface radiant flux must be taken into

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Xiaoqing Wu, Xin-Zhong Liang, and Sunwook Park

independent datasets such as longwave and shortwave radiative flux, cloud radiative forcing, surface sensible and latent heat fluxes, and airborne radar reflectivity. The general agreement between modeled and satellite-retrieved radiative fluxes gives confidence in the use of CRM-generated cloud and radiative properties to evaluate the cloud and radiation parameterization schemes of GCMs ( Wu and Moncrieff 2001 ). The TOGA COARE observations and successful long-term CRM simulations help establish the

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Aaron Donohoe, Ed Blanchard-Wrigglesworth, Axel Schweiger, and Philip J. Rasch

(area weighted) average of RI TOA, α , the radiative impact of sea ice change [the local top-of-atmosphere (TOA) radiative flux change due to surface albedo changes ( α ) from sea ice loss per degree of global averaged surface temperature change]: (1) SIAF = [ RI TOA , α ⁡ ( x , y ) ] , where square brackets indicate a global average. Following Winton (2006) [Eq. (1) ], the spatial map of RI TOA, α ( x , y ) is the product of two quantities ( Soden and Held 2006 ; Shell et al. 2008 ): 1) the

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Nicholas A. Bond and Meghan F. Cronin

of the region are dominated by the surface sensible and latent heat fluxes in winter, and by the radiative heat fluxes in summer, and it is therefore reasonable to suppose that different kinds of weather patterns are responsible for flux anomalies at different times of the year. Comparison of the winter with the summer weather patterns driving short-term flux variability represents one of the two primary objectives of this paper. On yearly and longer time scales, the temperature fluctuations for

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