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Robert D. Cess, Minghua Zhang, Bruce A. Wielicki, David F. Young, Xue-Long Zhou, and Yuri Nikitenko

1. Introduction Clouds radiatively cool the climate system through reflection of shortwave (solar) radiation from the system, while they radiatively warm the system by reducing the outgoing longwave (infrared) radiation that increases the atmospheric greenhouse effect. One of the many insights provided by data from the Earth Radiation Budget Experiment (ERBE) involved understanding the role of clouds on the climate system through analyzing top-of-the-atmosphere (TOA) cloud-radiative forcing

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Jason M. Keeler, Brian F. Jewett, Robert M. Rauber, Greg M. McFarquhar, Roy M. Rasmussen, Lulin Xue, Changhai Liu, and Gregory Thompson

an understanding of GC dynamics is important to understanding winter cyclone precipitation processes. In recent years, it has been suggested that the dynamics of GCs could be analogous to that of stratocumulus clouds ( Syrett et al. 1995 ; Kumjian et al. 2014 ; Rauber et al. 2014a , b ), where radiative forcing favors destabilization at cloud top and development of convection ( Wood 2012 ). Keeler et al. (2016 , hereafter Part I) directly addressed this hypothesis by performing idealized

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Melanie F. Fitzpatrick and Stephen G. Warren

the radiation budget is normally called cloud radiative forcing (CRF), although it might more accurately be referred to as cloud radiative effect, since “forcing” in other contexts means changes in radiative fluxes (due to an external influence on the system, often specifically anthropogenic contributions) rather than the climatological baseline. Clouds are of course highly interactive with the other components of the climate system. Here we use the standard term, CRF. In the solar (shortwave

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Warren P. Smith, Melville E. Nicholls, and Roger A. Pielke Sr.

in the early morning and is weakest in the afternoon local time ( Jacobson and Gray 1976 ). This has been attributed to both a nocturnal differential radiative forcing between cloud structures and their relatively clear-sky surroundings ( Gray and Jacobson 1977 ) and to nocturnal longwave-induced destabilization ( Xu and Randall 1995 ). Convective destabilization of clouds due to longwave radiation is sensitive to the cloud quantity ( Godbole 1973 ) and has been linked to the intensification of

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Ulrike Lohmann, Norman McFarlane, Lubomir Levkov, Kenzu Abdella, and Frank Albers

as the 3D GESIMA version was initialized with. Every time step the domain-averaged sum of the vertical and horizontal advection of temperature, specific humidity, and cloud ice obtained from GESIMA are used as a forcing for all SCM simulations. The adiabatic expansion is included in this expression. No surface forcing is specified for this study. Figure 4 shows the forcing for the SCM simulations, the sum of vertical and horizontal advection of temperature, water vapor, and cloud ice obtained

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Xiaodong Hong, Martin J. Leach, and Sethu Raman

2008JOURNAL OF APPLIED METEOROLOGYVOLUME 34A Sensitivity Study of Convective Cloud Formation by Vegetation Forcing with Different Atmospheric Conditions XIAODONG HONG, MARTIN J. LEACH, AND SETHU RAMANDepartment of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina(Manuscript received 5 April 1994, in final form 6 March 1995) ABSTRACT Variable vegetation cover is a possible triger for convection, especially

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Florian Bennhold and Steven Sherwood

) argued that low-level clouds would stabilize climate via a strong negative albedo feedback, if the relationship to low-level static stability reported by Klein and Hartmann (1993) held up. Since the 1970s, satellite observations have offered the possibility of assessing the performance of GCM present-day climate simulations using measured quantities on a global scale. Among those quantities measured are radiative forcings, water vapor in different layers of the atmosphere, and air and sea

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Michael J. Pavolonis and Jeffrey R. Key

from the surface in the polar regions. Regardless, satellite-derived datasets are very useful for studying spatial and temporal trends in a given parameter such as cloud radiative effect (commonly referred to as cloud forcing). It is also important to understand the sensitivities of cloud forcing at the surface to changes in various surface and cloud parameters. Parameters such as surface reflectance, surface temperature, cloud fraction, cloud-top height, cloud optical depth, cloud

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Harshvardhan, David A. Randall, and Donald A. Dazlich

DECEMBER 1990 HARSHVARDHAN, RANDALL AND DAZLICH 1435Relationship between the Longwave Cloud Radiative Forcing at the Surface and the Top of the Atmosphere HARSHVARDHANDepartment of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana DAVID A. RANDALL AND DONALD A. DAZLICHDepartment of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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William H. Raymond, William S. Olson, and Geary Callan

366MONTHLY WEATHER REVIEWVOLUME 123Diabatic Forcing and Initialization with Assimilation of Cloud Water and ,Rainwater in a Forecast Model WILLIAM H. RAYMOND AND WILLIAM S. OLSON*Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, Madison, Wisconsin ~JEARY CALLANNational Environmental Satellite Dam and Information Service ( NOAA ), Madison, Wisconsin(Manuscript received 25 August 1993, in final form 8 June 1994

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