lmd_Bony2006_abstracts.html

2006 .

F. Hourdin, I. Musat, S. Bony, P. Braconnot, F. Codron, J.-L. Dufresne, L. Fairhead, M.-A. Filiberti, P. Friedlingstein, J.-Y. Grandpeix, G. Krinner, P. Levan, Z.-X. Li, and F. Lott. The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Climate Dynamics, 27:787-813, December 2006. [ bib | DOI | ADS link ]

The LMDZ4 general circulation model is the atmospheric component of the IPSL CM4 coupled model which has been used to perform climate change simulations for the 4th IPCC assessment report. The main aspects of the model climatology (forced by observed sea surface temperature) are documented here, as well as the major improvements with respect to the previous versions, which mainly come form the parametrization of tropical convection. A methodology is proposed to help analyse the sensitivity of the tropical Hadley Walker circulation to the parametrization of cumulus convection and clouds. The tropical circulation is characterized using scalar potentials associated with the horizontal wind and horizontal transport of geopotential (the Laplacian of which is proportional to the total vertical momentum in the atmospheric column). The effect of parametrized physics is analysed in a regime sorted framework using the vertical velocity at 500 hPa as a proxy for large scale vertical motion. Compared to Tiedtkes convection scheme, used in previous versions, the Emanuels scheme improves the representation of the Hadley Walker circulation, with a relatively stronger and deeper large scale vertical ascent over tropical continents, and suppresses the marked patterns of concentrated rainfall over oceans. Thanks to the regime sorted analyses, these differences are attributed to intrinsic differences in the vertical distribution of convective heating, and to the lack of self-inhibition by precipitating downdraughts in Tiedtkes parametrization. Both the convection and cloud schemes are shown to control the relative importance of large scale convection over land and ocean, an important point for the behaviour of the coupled model.

D. Zurovac-Jevti, S. Bony, and K. Emanuel. On the Role of Clouds and Moisture in Tropical Waves: A Two-Dimensional Model Study. Journal of Atmospheric Sciences, 63:2140-2155, August 2006. [ bib | DOI | ADS link ]

Observations show that convective perturbations of the tropical atmosphere are associated with substantial variations of clouds and water vapor. Recent studies suggest that these variations may play an active role in the large-scale organization of the tropical atmosphere. The present study investigates that possibility by using a two-dimensional, nonrotating model that includes a set of physical parameterizations carefully evaluated against tropical data. In the absence of cloud radiation interactions, the model spontaneously generates fast upwind (eastward) moving planetary-scale oscillations through the wind-induced surface heat exchange mechanism. In the presence of cloud radiative effects, the model generates slower upwind (eastward) propagating modes in addition to small-scale disturbances advected downwind (westward) by the mean flow. Enhanced cloud radiative effects further slow down upwind propagating waves and make them more prominent in the spectrum. On the other hand, the model suggests that interactions between moisture and convection favor the prominence of moist Kelvin-like waves in tropical variability at the expense of small-scale advective disturbances. These numerical results, consistent with theoretical predictions, suggest that the interaction of water vapor and cloud variations with convection and radiation plays an active role in the large-scale organization of the tropical atmosphere.<BR />HR ALIGN=”center” WIDTH=”30%”<BR />

M. J. Webb, C. A. Senior, D. M. H. Sexton, W. J. Ingram, K. D. Williams, M. A. Ringer, B. J. McAvaney, R. Colman, B. J. Soden, R. Gudgel, T. Knutson, S. Emori, T. Ogura, Y. Tsushima, N. Andronova, B. Li, I. Musat, S. Bony, and K. E. Taylor. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Climate Dynamics, 27:17-38, July 2006. [ bib | DOI | ADS link ]

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO₂ doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.

K. D. Williams, M. A. Ringer, C. A. Senior, M. J. Webb, B. J. McAvaney, N. Andronova, S. Bony, J.-L. Dufresne, S. Emori, R. Gudgel, T. Knutson, B. Li, K. Lo, I. Musat, J. Wegner, A. Slingo, and J. F. B. Mitchell. Evaluation of a component of the cloud response to climate change in an intercomparison of climate models. Climate Dynamics, 26:145-165, February 2006. [ bib | DOI | ADS link ]

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time-mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere-mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60degN-60degS mean change in CRF to increased CO₂ and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.

S. Bony, R. Colman, V. M. Kattsov, R. P. Allan, C. S. Bretherton, J.-L. Dufresne, A. Hall, S. Hallegatte, M. M. Holland, W. Ingram, D. A. Randall, B. J. Soden, G. Tselioudis, and M. J. Webb. How Well Do We Understand and Evaluate Climate Change Feedback Processes? Journal of Climate, 19:3445, 2006. [ bib | DOI | ADS link ]