lmd_Dufresne2012.bib

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@article{2012GeoRL..3921801N,
  author = {{Nam}, C. and {Bony}, S. and {Dufresne}, J.-L. and {Chepfer}, H.
	},
  title = {{The {\lsquo}too few, too bright{\rsquo} tropical low-cloud problem in CMIP5 models}},
  journal = {\grl},
  keywords = {Atmospheric Composition and Structure: Cloud/radiation interaction, Atmospheric Composition and Structure: Radiation: transmission and scattering, Global Change: Atmosphere (0315, 0325), Global Change: Earth system modeling (1225, 4316), Global Change: Global climate models (3337, 4928)},
  year = 2012,
  month = nov,
  volume = 39,
  eid = {L21801},
  pages = {21801},
  abstract = {{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 {\lsquo}too few, too bright
low-cloud problem{\rsquo} for climate sensitivity and model development
are discussed.
}},
  doi = {10.1029/2012GL053421},
  adsurl = {http://adsabs.harvard.edu/abs/2012GeoRL..3921801N},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@article{2012ClDy...39.2091K,
  author = {{Konsta}, D. and {Chepfer}, H. and {Dufresne}, J.-L.},
  title = {{A process oriented characterization of tropical oceanic clouds for climate model evaluation, based on a statistical analysis of daytime A-train observations}},
  journal = {Climate Dynamics},
  year = 2012,
  month = nov,
  volume = 39,
  pages = {2091-2108},
  abstract = {{This paper aims at characterizing how different key cloud properties
(cloud fraction, cloud vertical distribution, cloud reflectance, a
surrogate of the cloud optical depth) vary as a function of the others
over the tropical oceans. The correlations between the different cloud
properties are built from 2 years of collocated A-train observations
(CALIPSO-GOCCP and MODIS) at a scale close to cloud processes; it
results in a characterization of the physical processes in tropical
clouds, that can be used to better understand cloud behaviors, and
constitute a powerful tool to develop and evaluate cloud
parameterizations in climate models. First, we examine a case study of
shallow cumulus cloud observed simultaneously by the two sensors
(CALIPSO, MODIS), and develop a methodology that allows to build global
scale statistics by keeping the separation between clear and cloudy
areas at the pixel level (250, 330 m). Then we build statistical
instantaneous relationships between the cloud cover, the cloud vertical
distribution and the cloud reflectance. The vertical cloud distribution
indicates that the optically thin clouds (optical thickness {\lt}1.5)
dominate the boundary layer over the trade wind regions. Optically thick
clouds (optical thickness {\gt}3.4) are composed of high and mid-level
clouds associated with deep convection along the ITCZ and SPCZ and over
the warm pool, and by stratocumulus low level clouds located along the
East coast of tropical oceans. The cloud properties are analyzed as a
function of the large scale circulation regime. Optically thick high
clouds are dominant in convective regions (CF {\gt} 80 \%), while low
level clouds with low optical thickness ({\lt}3.5) are present in regimes
of subsidence but in convective regimes as well, associated principally
to low cloud fractions (CF {\lt} 50 \%). A focus on low-level clouds
allows us to quantify how the cloud optical depth increases with cloud
top altitude and with cloud fraction.
}},
  doi = {10.1007/s00382-012-1533-7},
  adsurl = {http://adsabs.harvard.edu/abs/2012ClDy...39.2091K},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@article{2012JGRD..11714105J,
  author = {{Jiang}, J.~H. and {Su}, H. and {Zhai}, C. and {Perun}, V.~S. and 
	{Del Genio}, A. and {Nazarenko}, L.~S. and {Donner}, L.~J. and 
	{Horowitz}, L. and {Seman}, C. and {Cole}, J. and {Gettelman}, A. and 
	{Ringer}, M.~A. and {Rotstayn}, L. and {Jeffrey}, S. and {Wu}, T. and 
	{Brient}, F. and {Dufresne}, J.-L. and {Kawai}, H. and {Koshiro}, T. and 
	{Watanabe}, M. and {L{\'E}Cuyer}, T.~S. and {Volodin}, E.~M. and 
	{Iversen}, T. and {Drange}, H. and {Mesquita}, M.~D.~S. and 
	{Read}, W.~G. and {Waters}, J.~W. and {Tian}, B. and {Teixeira}, J. and 
	{Stephens}, G.~L.},
  title = {{Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA {\ldquo}A-Train{\rdquo} satellite observations}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {climate model, clouds, satellite observation, water vapor, Global Change: Atmosphere (0315, 0325), Global Change: Global climate models (3337, 4928), Global Change: Remote sensing (1855, 4337), Global Change: Water cycles (1836), Global Change: General or miscellaneous},
  year = 2012,
  month = jul,
  volume = 117,
  number = d16,
  eid = {D14105},
  pages = {14105},
  abstract = {{Using NASA's A-Train satellite measurements, we evaluate the accuracy of
cloud water content (CWC) and water vapor mixing ratio (H$_{2}$O)
outputs from 19 climate models submitted to the Phase 5 of Coupled Model
Intercomparison Project (CMIP5), and assess improvements relative to
their counterparts for the earlier CMIP3. We find more than half of the
models show improvements from CMIP3 to CMIP5 in simulating
column-integrated cloud amount, while changes in water vapor simulation
are insignificant. For the 19 CMIP5 models, the model spreads and their
differences from the observations are larger in the upper troposphere
(UT) than in the lower or middle troposphere (L/MT). The modeled mean
CWCs over tropical oceans range from {\tilde}3\% to {\tilde}15{\times} of
the observations in the UT and 40\% to 2{\times} of the observations in
the L/MT. For modeled H$_{2}$Os, the mean values over tropical
oceans range from {\tilde}1\% to 2{\times} of the observations in the UT
and within 10\% of the observations in the L/MT. The spatial
distributions of clouds at 215 hPa are relatively well-correlated with
observations, noticeably better than those for the L/MT clouds. Although
both water vapor and clouds are better simulated in the L/MT than in the
UT, there is no apparent correlation between the model biases in clouds
and water vapor. Numerical scores are used to compare different model
performances in regards to spatial mean, variance and distribution of
CWC and H$_{2}$O over tropical oceans. Model performances at each
pressure level are ranked according to the average of all the relevant
scores for that level.
}},
  doi = {10.1029/2011JD017237},
  adsurl = {http://adsabs.harvard.edu/abs/2012JGRD..11714105J},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

@article{2012ACP....12.5583D,
  author = {{Déandreis}, C. and {Balkanski}, Y. and {Dufresne}, J.~L. and 
	{Cozic}, A.},
  title = {{Radiative forcing estimates of sulfate aerosol in coupled climate-chemistry models with emphasis on the role of the temporal variability}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2012,
  month = jun,
  volume = 12,
  pages = {5583-5602},
  abstract = {{This paper describes the impact on the sulfate aerosol radiative effects
of coupling the radiative code of a global circulation model with a
chemistry-aerosol module. With this coupling, temporal variations of
sulfate aerosol concentrations influence the estimate of aerosol
radiative impacts. Effects of this coupling have been assessed on net
fluxes, radiative forcing and temperature for the direct and first
indirect effects of sulfate. 

 The direct effect respond
almost linearly to rapid changes in concentrations whereas the first
indirect effect shows a strong non-linearity. In particular, sulfate
temporal variability causes a modification of the short wave net fluxes
at the top of the atmosphere of +0.24 and +0.22 W m$^{-2}$ for the
present and preindustrial periods, respectively. This change is small
compared to the value of the net flux at the top of the atmosphere
(about 240 W m$^{-2}$). The effect is more important in regions
with low-level clouds and intermediate sulfate aerosol concentrations
(from 0.1 to 0.8 {$\mu$}g (SO$_{4}$) m$^{-3}$ in our model).


 The computation of the aerosol direct radiative forcing is
quite straightforward and the temporal variability has little effect on
its mean value. In contrast, quantifying the first indirect radiative
forcing requires tackling technical issues first. We show that the
preindustrial sulfate concentrations have to be calculated with the same
meteorological trajectory used for computing the present ones. If this
condition is not satisfied, it introduces an error on the estimation of
the first indirect radiative forcing. Solutions are proposed to assess
radiative forcing properly. In the reference method, the coupling
between chemistry and climate results in a global average increase of 8\%
in the first indirect radiative forcing. This change reaches 50\% in the
most sensitive regions. However, the reference method is not suited to
run long climate simulations. We present other methods that are simpler
to implement in a coupled chemistry/climate model and that offer the
possibility to assess radiative forcing.
}},
  doi = {10.5194/acp-12-5583-2012},
  adsurl = {http://adsabs.harvard.edu/abs/2012ACP....12.5583D},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}