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lmd_Bony2012_abstracts.html

2012 .

(7 publications)

C. Nam, S. Bony, J.-L. Dufresne, and H. Chepfer. The too few, too bright tropical low-cloud problem in CMIP5 models. Geophysical Research Letters, 39:21801, November 2012. [ bib | DOI | ADS link ]

Previous generations of climate models have been shown to under-estimate the occurrence of tropical low-level clouds and to over-estimate their radiative effects. This study analyzes outputs from multiple climate models participating in the Fifth phase of the Coupled Model Intercomparison Project (CMIP5) using the Cloud Feedback Model Intercomparison Project Observations Simulator Package (COSP), and compares them with different satellite data sets. Those include CALIPSO lidar observations, PARASOL mono-directional reflectances and CERES radiative fluxes at the top of the atmosphere. We show that current state-of-the-art climate models predict overly bright low-clouds, even for a correct low-cloud cover. The impact of these biases on the Earth' radiation budget, however, is reduced by compensating errors. Those include the tendency of models to under-estimate the low-cloud cover and to over-estimate the occurrence of mid- and high-clouds above low-clouds. Finally, we show that models poorly represent the dependence of the vertical structure of low-clouds on large-scale environmental conditions. The implications of this too few, too bright low-cloud problem for climate sensitivity and model development are discussed.

J.-L. Lacour, C. Risi, L. Clarisse, S. Bony, D. Hurtmans, C. Clerbaux, and P.-F. Coheur. Mid-tropospheric δD observations from IASI/MetOp at high spatial and temporal resolution. Atmospheric Chemistry & Physics, 12:10817-10832, November 2012. [ bib | DOI | ADS link ]

In this paper we retrieve atmospheric HDO, H2O concentrations and their ratio δD from IASI radiances spectra. Our method relies on an existing radiative transfer model (Atmosphit) and an optimal estimation inversion scheme, but goes further than our previous work by explicitly considering correlations between the two species. A global HDO and H2O a priori profile together with a covariance matrix were built from daily LMDz-iso model simulations of HDO and H2O profiles over the whole globe and a whole year. The retrieval parameters are described and characterized in terms of errors. We show that IASI is mostly sensitive to δD in the middle troposphere and allows retrieving δD for an integrated 3-6 km column with an error of 38 on an individual measurement basis. We examine the performance of the retrieval to capture the temporal (seasonal and short-term) and spatial variations of δD for one year of measurement at two dedicated sites (Darwin and Izaña) and a latitudinal band from -60deg to 60deg for a 15 day period in January. We report a generally good agreement between IASI and the model and indicate the capabilities of IASI to reproduce the large scale variations of δD (seasonal cycle and latitudinal gradient) with good accuracy. In particular, we show that there is no systematic significant bias in the retrieved δD values in comparison with the model, and that the retrieved variability is similar to the one in the model even though there are certain local differences. Moreover, the noticeable differences between IASI and the model are briefly examined and suggest modeling issues instead of retrieval effects. Finally, the results further reveal the unprecedented capabilities of IASI to capture short-term variations in δD, highlighting the added value of the sounder for monitoring hydrological processes.

I. Tobin, S. Bony, and R. Roca. Observational Evidence for Relationships between the Degree of Aggregation of Deep Convection, Water Vapor, Surface Fluxes, and Radiation. Journal of Climate, 25:6885-6904, October 2012. [ bib | DOI | ADS link ]

F. Brient and S. Bony. How may low-cloud radiative properties simulated in the current climate influence low-cloud feedbacks under global warming? Geophysical Research Letters, 39:20807, October 2012. [ bib | DOI | ADS link ]

The influence of cloud modelling uncertainties on the projection of the tropical low-cloud response to global warming is explored by perturbing model parameters of the IPSL-CM5A climate model in a range of configurations (realistic general circulation model, aqua-planet, single-column model). While the positive sign and the mechanism of the low-cloud response to climate warming predicted by the model are robust, the amplitude of the response can vary considerably depending on the model tuning parameters. Moreover, the strength of the low-cloud response to climate change exhibits a strong correlation with the strength of the low-cloud radiative effects simulated in the current climate. We show that this correlation primarily results from a local positive feedback (referred to as the beta feedback) between boundary-layer cloud radiative cooling, relative humidity and low-cloud cover. Based on this correlation and observational constraints, it is suggested that the strength of the tropical low-cloud feedback predicted by the IPSL-CM5A model in climate projections might be overestimated by about fifty percent.

M. Zhang, C. S. Bretherton, P. N. Blossey, S. Bony, F. Brient, and J.-C. Golaz. The CGILS experimental design to investigate low cloud feedbacks in general circulation models by using single-column and large-eddy simulation models. Journal of Advances in Modeling Earth Systems, 4:12001, April 2012. [ bib | DOI | ADS link ]

A surrogate climate change is designed to investigate low cloud feedbacks in the northeastern Pacific by using Single Column Models (SCMs), Cloud Resolving Models (CRMs), and Large Eddy Simulation models (LES), as part of the CGILS study (CFMIP-GASS Intercomparison of LES and SCM models). The constructed large-scale forcing fields, including subsidence and advective tendencies, and their perturbations in the warmer climate are shown to compare well with conditions in General Circulation Models (GCMs), but they are free from the impact of any GCM parameterizations. The forcing fields in the control climate are also shown to resemble the mean conditions in the ECMWF-Interim Reanalysis. Applications of the forcing fields in SCMs are presented. It is shown that the idealized design can offer considerable insight into the mechanisms of cloud feedbacks in the models. Caveats and advantages of the design are also discussed.

C. Risi, D. Noone, J. Worden, C. Frankenberg, G. Stiller, M. Kiefer, B. Funke, K. Walker, P. Bernath, M. Schneider, S. Bony, J. Lee, D. Brown, and C. Sturm. Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopic observations: 2. Using isotopic diagnostics to understand the mid and upper tropospheric moist bias in the tropics and subtropics. Journal of Geophysical Research (Atmospheres), 117:5304, March 2012. [ bib | DOI | ADS link ]

Evaluating the representation of processes controlling tropical and subtropical tropospheric relative humidity (RH) in atmospheric general circulation models (GCMs) is crucial to assess the credibility of predicted climate changes. GCMs have long exhibited a moist bias in the tropical and subtropical mid and upper troposphere, which could be due to the mis-representation of cloud processes or of the large-scale circulation, or to excessive diffusion during water vapor transport. The goal of this study is to use observations of the water vapor isotopic ratio to understand the cause of this bias. We compare the three-dimensional distribution of the water vapor isotopic ratio measured from space and ground to that simulated by several versions of the isotopic GCM LMDZ. We show that the combined evaluation of RH and of the water vapor isotopic composition makes it possible to discriminate the most likely cause of RH biases. Models characterized either by an excessive vertical diffusion, an excessive convective detrainment or an underestimated in situ cloud condensation will all produce a moist bias in the free troposphere. However, only an excessive vertical diffusion can lead to a reversed seasonality of the free tropospheric isotopic composition in the subtropics compared to observations. Comparing seven isotopic GCMs suggests that the moist bias found in many GCMs in the mid and upper troposphere most frequently results from an excessive diffusion during vertical water vapor transport. This study demonstrates the added value of water vapor isotopic measurements for interpreting shortcomings in the simulation of RH by climate models.

C. Risi, D. Noone, J. Worden, C. Frankenberg, G. Stiller, M. Kiefer, B. Funke, K. Walker, P. Bernath, M. Schneider, D. Wunch, V. Sherlock, N. Deutscher, D. Griffith, P. O. Wennberg, K. Strong, D. Smale, E. Mahieu, S. Barthlott, F. Hase, O. GarcíA, J. Notholt, T. Warneke, G. Toon, D. Sayres, S. Bony, J. Lee, D. Brown, R. Uemura, and C. Sturm. Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations. Journal of Geophysical Research (Atmospheres), 117:5303, March 2012. [ bib | DOI | ADS link ]

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity.

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