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Behnjamin J. Zib, Xiquan Dong, Baike Xi, and Aaron Kennedy

must first be addressed. Several studies have investigated the performance of reanalyses over the Arctic for a variety of fields including atmospheric moisture budgets ( Bromwich et al. 2000 , 2002 ), upper-level winds ( Francis 2002 ), precipitation ( Serreze and Hurst 2000 ), cloud fraction (CF) and radiative fluxes ( Walsh et al. 2009 ), and general tropospheric assessments ( Bromwich and Wang 2005 ; Bromwich et al. 2007 ). These studies, however, were based on the earlier generations of

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Carlos Domenech, Ernesto Lopez-Baeza, David P. Donovan, and Tobias Wehr

region of the same clouds, which cannot be penetrated by the lidar, will be observed using the radar. To gain cross-track information needed for the retrieval of three-dimensional structures of clouds and aerosols, the active instruments will be supported by a 150-km swath multispectral imager. To link the computed three-dimensional cloud and aerosol structures to the radiative fluxes, the corresponding shortwave (SW) and longwave (LW) outgoing radiation will be measured by using the broadband

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Jason M. English, Andrew Gettelman, and Gina R. Henderson

occurred in recent decades and projecting future Arctic climate change is challenging because of the complexity of representing the processes associated with Arctic amplification and the sensitivity of radiative fluxes to differences in cloud, snow-extent, and sea-ice coverage and albedo. Hence, in order to accurately represent Arctic climate, models must accurately represent numerous components including surface type and albedo, cloud amount, and cloud phase. Additionally, the Arctic region suffers

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Patrick C. Taylor

monthly diurnal cycle composites? A discussion of the implications, physical meaning, and cause of diurnal cycle variability is presented in section 5 followed by a summary and conclusions in section 6 . 2. Data The CERES SYN Ed2Rev1 dataset contains all-sky OLR and RSW fluxes and clear-sky OLR (OLR CLR ) and RSW (RSW CLR ) fluxes extending from March 2000 through October 2005 with 1° × 1° spatial and 3-hourly temporal resolution ( Loeb et al. 2009 ; Doelling et al. 2013 ). The radiative forcing

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Virendra P. Ghate, Bruce A. Albrecht, Christopher W. Fairall, and Robert A. Weller

Climate Processes in the Coupled Ocean–Atmosphere System (EPIC) was conducted in 2001 ( Bretherton et al. 2004 ). Under this study the Woods Hole Oceanography Institute’s (WHOI) Upper Ocean Process (UOP) group deployed an Ocean Reference Station (Stratus ORS) near the annual maximum of stratus cloud cover in October 2000. The Stratus ORS is located at 20°S, 85°W and has collected observations of broadband radiative fluxes and surface meteorological parameters continuously since it was launched

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C. M. Naud, I. Rangwala, M. Xu, and J. R. Miller

(2006) reported changes in cloud amount over the Tibetan Plateau [also identified by Zhang et al. (2008) and Yang et al. (2012 )] and suggested that these changes (i.e., daytime decrease, nighttime increase) played a role in the temperature increase in the region, through their radiative impact. Ye et al. (2009) , for example, found a strong correlation between surface downward shortwave fluxes and the diurnal temperature range. Yang et al. (2012) demonstrated that the increase in deep

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Hua Zhang, Feng Zhang, Qiang Fu, Zhongping Shen, and Peng Lu

on the source function technique proposed by Davies (1980) and Toon et al. (1989) . Fu et al. (1997) showed that they are suitable for the radiative flux and heating rate calculations in the infrared, with an accuracy close to the δ -four-stream method but a computational efficiency only about 50% more than the δ -two-stream methods. Unfortunately, for the solar radiation, when the single scattering albedo is equal to 1, these approaches do not necessarily yield conserved radiative fluxes

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Sally A. McFarlane, James H. Mather, and Eli J. Mlawer

the key elements of Earth’s energy budget ( Trenberth et al. 2009 ). While satellites provide measurements of the global distribution of reflected and emitted broadband fluxes at the top of the atmosphere (TOA), less information is available on the radiative budget at the surface and the vertical distribution of absorption and emission in the atmosphere. Key goals of the Atmospheric Radiation Measurement (ARM) Program are to quantify the radiative energy balance profile in Earth’s atmosphere, to

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Nadir Jeevanjee and Stephan Fueglistaler

approximation hold? How do these conditions break down (as they must in PRE), and how can this be reconciled with the double cancellation argument given above? The goal of this paper is to shed light on these questions. A key ingredient in our analysis will be a refinement of the canonical decomposition of radiative flux divergence given by Green (1967) into a new decomposition which naturally captures the double cancellation described above, and which also isolates the contributions which do not cancel

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Zhonghai Jin and Andrew Lacis

1. Introduction Clouds have very important effect on Earth’s radiation budget of the atmosphere, thus making clouds one of the fundamental issues in the study and modeling of the climate. Accurate computation of radiative fluxes and absorption in clouds is needed to assess their impact on climate, but rigorous radiative transfer computations (e.g., Hansen and Travis 1974 ) are only feasible in the framework of plane-parallel homogeneous (PPH) geometry. In contrast, surface and space

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