lmd_Bony2005_abstracts.html
2005 .
(5 publications)F. Vimeux, R. Gallaire, S. Bony, G. Hoffmann, and J. C. H. Chiang. What are the climate controls on @dD in precipitation in the Zongo Valley (Bolivia)? Implications for the Illimani ice core interpretation [rapid communication]. Earth and Planetary Science Letters, 240:205-220, December 2005. [ bib | DOI | ADS link ]
Controversy has surrounded the interpretation of the water isotopic composition ( δD or δ18O) in tropical and subtropical ice cores in South America. Although recent modeling studies using AGCM have provided useful constraints at interannual time scales, no direct calibration based on modern observations has been achieved. In the context of the recent ice core drilling at Nevado Illimani (16deg39'S-67deg47'W) in Bolivia, we examine the climatic controls on the modern isotopic composition of precipitation in the Zongo Valley, located on the northeast side of the Cordillera Real, at about 55 km from Nevado Illimani. Monthly precipitation samples were collected from September 1999 to August 2004 at various altitudes along this valley. First we examine the local and regional controls on the common δD signal measured along this valley. We show that (1) local temperature has definitely no control on δD variations, and (2) local rainout is a poor factor to explain δD variations. We thus seek regional controls upstream the Valley potentially affecting air masses distillation. Based on backtrajectory calculations and using satellite data (TRMM precipitation, NOAA OLR) and direct observations of precipitation (IAEA/GNIP), we show that moisture transport history and the degree of rainout upstream are more important factors explaining seasonal δD variations. Analysis of a 92-yr simulation from the ECHAM-4 model (T30 version) implemented with water stable isotopes confirms our observations at seasonal time scale and emphasize the role of air masses distillation upstream as a prominent factor controlling interannual δD variations. Lastly, we focus on the isotopic depletion along the valley when air masses are lifted up. Our results suggest that, if the temperature gradient between the base and the top of the Andes was higher by a few degrees during the Last Glacial Maximum (LGM), less than 10% of the glacial to interglacial isotopic variation recorded in the Illimani ice core could be accounted for by this temperature change. It implies that the rest of the variation would originate from wetter conditions along air masses trajectory during LGM.
S. Bony and J.-L. Dufresne. Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophysical Research Letters, 32:20806, October 2005. [ bib | DOI | ADS link ]
The radiative response of tropical clouds to global warming exhibits a large spread among climate models, and this constitutes a major source of uncertainty for climate sensitivity estimates. To better interpret the origin of that uncertainty, we analyze the sensitivity of the tropical cloud radiative forcing to a change in sea surface temperature that is simulated by 15 coupled models simulating climate change and current interannual variability. We show that it is in regimes of large-scale subsidence that the model results (1) differ the most in climate change and (2) disagree the most with observations in the current climate (most models underestimate the interannual sensitivity of clouds albedo to a change in temperature). This suggests that the simulation of the sensitivity of marine boundary layer clouds to changing environmental conditions constitutes, currently, the main source of uncertainty in tropical cloud feedbacks simulated by general circulation models.
M. H. Zhang, W. Y. Lin, S. A. Klein, J. T. Bacmeister, S. Bony, R. T. Cederwall, A. D. Del Genio, J. J. Hack, N. G. Loeb, U. Lohmann, P. Minnis, I. Musat, R. Pincus, P. Stier, M. J. Suarez, M. J. Webb, J. B. Wu, S. C. Xie, M.-S. Yao, and J. H. Zhang. Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. Journal of Geophysical Research (Atmospheres), 110:15, August 2005. [ bib | DOI | ADS link ]
To assess the current status of climate models in simulating clouds, basic cloud climatologies from ten atmospheric general circulation models are compared with satellite measurements from the International Satellite Cloud Climatology Project (ISCCP) and the Clouds and Earth's Radiant Energy System (CERES) program. An ISCCP simulator is employed in all models to facilitate the comparison. Models simulated a four-fold difference in high-top clouds. There are also, however, large uncertainties in satellite high thin clouds to effectively constrain the models. The majority of models only simulated 30-40% of middle-top clouds in the ISCCP and CERES data sets. Half of the models underestimated low clouds, while none overestimated them at a statistically significant level. When stratified in the optical thickness ranges, the majority of the models simulated optically thick clouds more than twice the satellite observations. Most models, however, underestimated optically intermediate and thin clouds. Compensations of these clouds biases are used to explain the simulated longwave and shortwave cloud radiative forcing at the top of the atmosphere. Seasonal sensitivities of clouds are also analyzed to compare with observations. Models are shown to simulate seasonal variations better for high clouds than for low clouds. Latitudinal distribution of the seasonal variations correlate with satellite measurements at 0.9, 0.6-0.9, and -0.2-0.7 levels for high, middle, and low clouds, respectively. The seasonal sensitivities of cloud types are found to strongly depend on the basic cloud climatology in the models. Models that systematically underestimate middle clouds also underestimate seasonal variations, while those that overestimate optically thick clouds also overestimate their seasonal sensitivities. Possible causes of the systematic cloud biases in the models are discussed.
S. Bony and K. A. Emanuel. On the Role of Moist Processes in Tropical Intraseasonal Variability: Cloud-Radiation and Moisture-Convection Feedbacks. Journal of Atmospheric Sciences, 62:2770-2789, August 2005. [ bib | DOI | ADS link ]
Recent observations of the tropical atmosphere reveal large variations of water vapor and clouds at intraseasonal time scales. This study investigates the role of these variations in the large-scale organization of the tropical atmosphere, and in intraseasonal variability in particular. For this purpose, the influence of feedbacks between moisture (water vapor, clouds), radiation, and convection that affect the growth rate and the phase speed of unstable modes of the tropical atmosphere is investigated.Results from a simple linear model suggest that interactions between moisture and tropospheric radiative cooling, referred to as moist-radiative feedbacks, play a significant role in tropical intraseasonal variability. Their primary effect is to reduce the phase speed of large-scale tropical disturbances: by cooling the atmosphere less efficiently during the rising phase of the oscillations (when the atmosphere is moister) than during episodes of large-scale subsidence (when the atmosphere is drier), the atmospheric radiative heating reduces the effective stratification felt by propagating waves and slows down their propagation. In the presence of significant moist-radiative feedbacks, planetary disturbances are characterized by an approximately constant frequency. In addition, moist-radiative feedbacks excite small-scale disturbances advected by the mean flow. The interactions between moisture and convection exert a selective damping effect upon small-scale disturbances, thereby favoring large-scale propagating waves at the expense of small-scale advective disturbances. They also weaken the ability of radiative processes to slow down the propagation of planetary-scale disturbances. This study suggests that a deficient simulation of cloud radiative interactions or of convection-moisture interactions may explain some of the difficulties experienced by general circulation models in simulating tropical intraseasonal oscillations.
M. Haeffelin, L. Barthès, O. Bock, C. Boitel, S. Bony, D. Bouniol, H. Chepfer, M. Chiriaco, J. Cuesta, J. Delanoë, P. Drobinski, J.-L. Dufresne, C. Flamant, M. Grall, A. Hodzic, F. Hourdin, F. Lapouge, Y. Lemaître, A. Mathieu, Y. Morille, C. Naud, V. Noël, W. O'Hirok, J. Pelon, C. Pietras, A. Protat, B. Romand, G. Scialom, and R. Vautard. SIRTA, a ground-based atmospheric observatory for cloud and aerosol research. Annales Geophysicae, 23:253-275, February 2005. [ bib | DOI | ADS link ]
Ground-based remote sensing observatories have a crucial role to play in providing data to improve our understanding of atmospheric processes, to test the performance of atmospheric models, and to develop new methods for future space-borne observations. Institut Pierre Simon Laplace, a French research institute in environmental sciences, created the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA), an atmospheric observatory with these goals in mind. Today SIRTA, located 20km south of Paris, operates a suite a state-of-the-art active and passive remote sensing instruments dedicated to routine monitoring of cloud and aerosol properties, and key atmospheric parameters. Detailed description of the state of the atmospheric column is progressively archived and made accessible to the scientific community. This paper describes the SIRTA infrastructure and database, and provides an overview of the scientific research associated with the observatory. Researchers using SIRTA data conduct research on atmospheric processes involving complex interactions between clouds, aerosols and radiative and dynamic processes in the atmospheric column. Atmospheric modellers working with SIRTA observations develop new methods to test their models and innovative analyses to improve parametric representations of sub-grid processes that must be accounted for in the model. SIRTA provides the means to develop data interpretation tools for future active remote sensing missions in space (e.g. CloudSat and CALIPSO). SIRTA observation and research activities take place in networks of atmospheric observatories that allow scientists to access consistent data sets from diverse regions on the globe.