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Dayid S. Gutzler

) yield nearly identical results. No humidity measurements are reported in fullythe upper third of the troposphere. The implications of these uncertainties for determining the climatologicalhumidity profile are quantitatively assessed by bracketing the range of plausible assumptions for unreportedhumidity to produce extreme estimates of the climatological profile. These profiles, together with the observedclimatological temperature profile, are used as input to a radiative transfer model to ascertain

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Xiaoming Hu, Yana Li, Song Yang, Yi Deng, and Ming Cai

. These vertical profiles of partial radiative heating perturbations are calculated as the difference between two calculations of a radiative transfer model: one with inputs taken from the mean state of 1984–95 and the other with identical inputs except the field denoted by the superscript, which is taken from the mean state of 2002–13. As in Deng et al. (2012) , all of the radiative heating calculations are made with the Fu–Liou radiative transfer model ( Fu and Liou 1992 , 1993 ). We note that the

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Lyle D. Wilson, Judith A. Curry, and Thomas P. Ackerman

in the Arctic during the cold half ofthe year, with an estimated 50% frequency of occurrence during the winter season. Curry et al. (1990)© 1993 American Meteorological Society1468 JOURNAL OF CLIMATE VOLUME6carded out detailed radiative transfer calculations usingobserved vertical profiles of temperatures, humidity,and ice crystal concentrations and

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Alexandra K. Jonko, Karen M. Shell, Benjamin M. Sanderson, and Gokhan Danabasoglu

repeated runs of an offline radiative transfer model, making it computationally expensive. Colman et al. (1997) propose a modified PRP approach to investigate the nonlinear behavior of climate feedbacks resulting from globally uniform SST perturbations ranging between ±2 K in the CAWCR model. The consideration of higher-order terms allows them to evaluate nonlinearities for individual feedbacks and estimate errors that would result from using linear theory. They find that the largest nonlinearities

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Ken Takahashi

a standard case run with stand-alone versions of the radiative transfer schemes used in the CMIP3 models considered from the Radiative Transfer Model Intercomparison Project (RTMIP; Collins et al. 2006a ) were also compared to the climate model data. 3. Results and analysis In Fig. 1a we show ΔLH plotted against the change in global mean surface air temperature (Δ T ) for all climate models and runs. The linear model (2) with a single set of coefficients is a reasonable representation of

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Manajit Sengupta, Eugene E. Clothiaux, Thomas P. Ackerman, Seiji Kato, and Qilong Min

and retrievals of cloud microphysics from a radiative transfer perspective. The paradigm involves calculating surface solar fluxes using cloud microphysics from different sources and comparing the results with actual radiation measurements. We adapt the paradigm to assess retrievals of boundary layer cloud liquid water paths and cloud drop effective radii. A best-fit baseline effective radius appropriate for stratus at the ARM SGP site is used for comparison. We also assess the sensitivity of

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John W. Bergman and Murry L. Salby

LW measure the cloud diurnal contribution to time-mean radiative heating of the atmospheric column. A radiative transfer calculation in an idealized atmosphere ( section 2 ) illustrates how the components of F ′ c arise from the nonlinear dependence of radiative fluxes on diurnally varying properties and explores the cloud diurnal contributions to the vertical distribution of atmospheric heating rates. In section 3 , an observationally driven radiative transfer model quantifies F ′ c for

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Dan Lubin

investigatedusing radiometric Fourier Transform Infrared (FlrlR) measurements of atmospheric emission in conjunctionwith detailed radiative transfer theory. The California Space Institute FTIR Spectroradiometer was deployed atPalmer Station, Antarctica (64°46'S, 64°04'W), where it made zenith sky emission measurements several timesdaily between 25 August 1991 and 17 November 1991. Emission spectra covered the entire middle infrared(5-20 ~tm) with one inverse centimeter spectral resolution. For FT1R data

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Mark D. Zelinka, Stephen A. Klein, and Dennis L. Hartmann

perturbations in each bin of the CTP- and τ -partitioned histogram as a function of latitude, month, and surface albedo using a radiative transfer code. We will refer to this as a cloud radiative kernel. Then, multiplying the cloud radiative kernel with the change in cloud fraction histogram per unit of global mean surface air temperature change between a control and doubled-CO 2 climate, we compute the cloud feedbacks in the CFMIP simulations. To build confidence in our method, we demonstrate that the

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Zhanqing Li, H. G. Leighton, Kazuhiko Masuda, and Tsutomu Takashima

or snow. In addition, the majority ofmodels require inputs such as cloud-optical thickness that are usually not known. Extensive radiative transfer modeling for different surface, atmospheric, and cloud conditions suggests a linearrelationship between the TOA-reflected flux and the flux absorbed at the surface for a fixed solar zenith angle(SZA). The linear relationship is independent of cloud-optical thickness and surface albedo. Sensitivity testsshow that the relationship depends strongly on

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