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Xianglei Huang, Xiuhong Chen, Mark Flanner, Ping Yang, Daniel Feldman, and Chaincy Kuo

graybody emissivity is assumed in the land model. Spectral variations of surface emissivities are not considered in either the atmosphere or land model components of the CESM. To ensure consistency of surface longwave flux across the atmosphere and land models, a radiative skin temperature is derived from the surface upward longwave flux generated from the land model and is then used in subsequent atmospheric radiative transfer calculation (further details are described in section 2a ). We have also

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Mark A. Miller, Virendra P. Ghate, and Robert K. Zahn

radiative divergence and the clear-sky atmospheric radiative divergence and is given by It only depends on the cloud properties in the column (cloud fraction, cloud-top temperature, etc.) and its relationship with the CRF is written as Clouds impact the atmospheric radiation budget in the Sahel region of West Africa according to these relationships, so a comparison between measured and GCM-simulated values of the CRE contains fundamental information about the interworkings of the radiation transfer in

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Daniel M. Gilford and Susan Solomon

describes the satellite observations of water vapor and ozone seasonal cycles along with the broadband radiative transfer model used to calculate their radiative impacts; radiative calculations, sensitivity test results, and the latitudinal variability of results are discussed in section 3 ; and conclusions are summarized in section 4 . 2. Data and methods a. Observations To study the radiative impacts of constituent seasonal cycles, this study uses observations of water vapor, ozone, and temperature

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Gunnar Myhre and Arne Myhre

data are used. The effect of different PNV can be assessed by looking at Figs. 2e,f where the same cropland distribution is adopted in both but associated with different PNV datasets. The differences between these two figures are particularly evident in Australia, India, and large parts of Africa. c. Radiative transfer model To assess the radiative forcing of the various current vegetation and PNV we relied on radiative transfer calculations. We apply a multistream model using the discrete

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Gang Hong, Ping Yang, Bryan A. Baum, Andrew J. Heymsfield, and Kuan-Man Xu

using a combination of the discrete ordinates radiative transfer model (DISORT; Stamnes et al. 1988 ) and a line-by-line model (LBL; Heidinger 1998 ) that provides monochromatic molecular absorption in the atmosphere. The standard tropical atmospheric profile in the LBL is used to calculate the transmission for clear sky. CRF here follows the formulas used by, for example, Liou (1992) and Yang et al. (2007) : where F is the net total flux (SW plus LW) at the top of the atmosphere or surface

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Tyler J. Thorsen, Seiji Kato, Norman G. Loeb, and Fred G. Rose

sources of data to help quantify uncertainties, as is done in this study. Descriptions of the inputs and radiative transfer model are given in sections 2 and 3 , respectively. Section 4 reviews the PRP and kernel methods and discusses their implementation in CERES-PRP. Validation of the computed fluxes are provided in section 5 , including assessing the efficacy of using monthly mean inputs and the CloudSat / CALIPSO clustering method, along with comparisons to the CERES-observed fluxes. A

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Diane J. Ivy, Susan Solomon, and Harald E. Rieder

radiative transfer model in a seasonally evolving fixed dynamical heating calculation). We also extend earlier work by evaluating both the Arctic and Antarctic stratospheric temperature trends and their drivers and highlight key differences between the two poles. Internal variability is also considered along with the trends. The aim of this study is to understand radiative contributions to observed polar stratospheric temperature trends, in particular how anthropogenic forcings (primarily increased well

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Vanda Salgueiro, Maria João Costa, Ana Maria Silva, and Daniele Bortoli

of its importance in understanding the effects of clouds on the radiative balance, which controls the earth–atmosphere temperature; Ramanathan et al. (1989) and Harrison et al. (1990) were the first to estimate the global CRF and the seasonal effects of clouds on the radiation budget from Earth Radiation Budget Experiment (ERBE) data. Since then, with the improvement of satellites, ground-based instruments, and radiative transfer and climate models, many other studies dedicated to the

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Jun Inoue, Jiping Liu, James O. Pinto, and Judith A. Curry

rain gauge at the SHEBA site. Observations showed significant precipitation on 11–13 and 29–30 May. Both events were successfully reproduced by COAMPS and RCA; however, the total accumulated precipitation in this month was almost 50% greater than observed primarily because precipitation in the latter event was overestimated. Neither ARCSYM nor HIRHAM simulated any significant precipitation until nearly the end of the month. c. Radiative transfer Clouds have a complex effect on surface radiation

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Lukas Kluft, Sally Dacie, Stefan A. Buehler, Hauke Schmidt, and Bjorn Stevens

McAvaney (2009) find a balancing of water vapor and lapse rate feedback in a warmer climate in a global climate model (GCM). For our RCE simulations we use a radiation scheme that trades accuracy for computational efficiency. By using line-by-line radiative transfer simulations we evaluate the fidelity of these base calculations and pinpoint how different radiative feedbacks are distributed spectrally. Besides its impact on ECS, water vapor also impacts the temperature profile and its evolution in a

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