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Titlebook: Climate Sensitivity to Radiative Perturbations; Physical Mechanisms Hervé Le Treut Conference proceedings 1996 Springer-Verlag Berlin Heid

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GCM Implications for Mechanisms Determining Cloud and Water Vapor Feedbacksion. One might wait instead for a consensus to be reached among climate GCMs about sensitivity, independent of observations.But different GCMs’ may predict similar sensitivities for very different reasons. Finally, one might validate the mean state of GCMs against the many global data sets now becom
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Sensitivity of the Simulated Climate to Parameterization of Cloud Optical Properties in the MGO GCMopical latitudes. The net effect produces the surface cooling by 6°C in the northern polar region and by 10°C in Antartica in winter. In tropics, the net cooling due to the effect of the cloud-radiative forcing results in intensification of convection, increase of high clouds and precipitation. The
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Water Vapour and Cloud Feedback in the BMRC AGCMs for fixed July conditions in a range of FANGIO (Feedback Analysis of GCMs for Intercomparison and Observations) experiments (e.g. Cess et al., 1990, Randall et al., 1992). Variations on this technique have been used for the investigation of snow feedback (Cess et al., 1991; Randall et al., 1994; C
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Sensitivity Parameters of the Meteo-France Climate Models: Emeraude and Arpege. Thus, we have the opportunity to compare the sensitivity of these two models which were also used for time-slice 2*.. experiments (mahfouf et al., 1994a et Timbal et al., 1995). Since ARPEGE includes a wider range of options, we have performed three sets of experiments to study the impact of a new
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https://doi.org/10.1007/978-981-15-5293-9ained from a comparison between the ECMWF model and Meteosat data over Africa and the Atlantic Ocean. Three model time series are used based either on “first guess” or on two runs without assimilation. The aim of the “first guess” time series is to validate the response of the cloud parameterization
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https://doi.org/10.1007/978-1-349-10224-2ion. One might wait instead for a consensus to be reached among climate GCMs about sensitivity, independent of observations.But different GCMs’ may predict similar sensitivities for very different reasons. Finally, one might validate the mean state of GCMs against the many global data sets now becom
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