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lmd_Dufresne2004_bib.html

lmd_Dufresne2004.bib

@comment{{This file has been generated by bib2bib 1.95}}
@comment{{Command line: /usr/bin/bib2bib --quiet -c 'not journal:"Discussions"' -c 'not journal:"Polymer Science"' -c '  author:"Dufresne"  ' -c year=2004 -c $type="ARTICLE" -oc lmd_Dufresne2004.txt -ob lmd_Dufresne2004.bib /home/WWW/LMD/public/Publis_LMDEMC3.link.bib}}
@article{2004ClDy...23..779Q,
  author = {{Quaas}, J. and {Boucher}, O. and {Dufresne}, J.-L. and {Treut}, H.
	},
  title = {{Impacts of greenhouse gases and aerosol direct and indirect effects on clouds and radiation in atmospheric GCM simulations of the 1930 1989 period}},
  journal = {Climate Dynamics},
  year = 2004,
  month = dec,
  volume = 23,
  pages = {779-789},
  abstract = {{Among anthropogenic perturbations of the Earth{\rsquo}s atmosphere,
greenhouse gases and aerosols are considered to have a major impact on
the energy budget through their impact on radiative fluxes. We use three
ensembles of simulations with the LMDZ general circulation model to
investigate the radiative impacts of five species of greenhouse gases
(CO$_{2}$, CH$_{4}$, N$_{2}$O, CFC-11 and CFC-12) and
sulfate aerosols for the period 1930 1989. Since our focus is on the
atmospheric changes in clouds and radiation from greenhouse gases and
aerosols, we prescribed sea-surface temperatures in these simulations.
Besides the direct impact on radiation through the greenhouse effect and
scattering of sunlight by aerosols, strong radiative impacts of both
perturbations through changes in cloudiness are analysed. The increase
in greenhouse gas concentration leads to a reduction of clouds at all
atmospheric levels, thus decreasing the total greenhouse effect in the
longwave spectrum and increasing absorption of solar radiation by
reduction of cloud albedo. Increasing anthropogenic aerosol burden
results in a decrease in high-level cloud cover through a cooling of the
atmosphere, and an increase in the low-level cloud cover through the
second aerosol indirect effect. The trend in low-level cloud lifetime
due to aerosols is quantified to 0.5 min day$^{-1}$
decade$^{-1}$ for the simulation period. The different
changes in high (decrease) and low-level (increase) cloudiness due to
the response of cloud processes to aerosols impact shortwave radiation
in a contrariwise manner, and the net effect is slightly positive. The
total aerosol effect including the aerosol direct and first indirect
effects remains strongly negative.
}},
  doi = {10.1007/s00382-004-0475-0},
  adsurl = {http://adsabs.harvard.edu/abs/2004ClDy...23..779Q},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2004ClDy...22...71B,
  author = {{Bony}, S. and {Dufresne}, J.-L. and {Le Treut}, H. and {Morcrette}, J.-J. and 
	{Senior}, C.},
  title = {{On dynamic and thermodynamic components of cloud changes}},
  journal = {Climate Dynamics},
  year = 2004,
  volume = 22,
  pages = {71-86},
  abstract = {{Clouds are sensitive to changes in both the large-scale circulation and
the thermodynamic structure of the atmosphere. In the tropics,
temperature changes that occur on seasonal to decadal time scales are
often associated with circulation changes. Therefore, it is difficult to
determine the part of cloud variations that results from a change in the
dynamics from the part that may result from the temperature change
itself. This study proposes a simple framework to unravel the dynamic
and non-dynamic (referred to as thermodynamic) components of the cloud
response to climate variations. It is used to analyze the contrasted
response, to a prescribed ocean warming, of the tropically-averaged
cloud radiative forcing (CRF) simulated by the ECMWF, LMD and UKMO
climate models. In each model, the dynamic component largely dominates
the CRF response at the regional scale, but this is the thermodynamic
component that explains most of the average CRF response to the imposed
perturbation. It is shown that this component strongly depends on the
behaviour of the low-level clouds that occur in regions of moderate
subsidence (e.g. in the trade wind regions). These clouds exhibit a
moderate sensitivity to temperature changes, but this is mostly their
huge statistical weight that explains their large influence on the
tropical radiation budget. Several propositions are made for assessing
the sensitivity of clouds to changes in temperature and in large-scale
motions using satellite observations and meteorological analyses on the
one hand, and mesoscale models on the other hand.
}},
  doi = {10.1007/s00382-003-0369-6},
  adsurl = {http://adsabs.harvard.edu/abs/2004ClDy...22...71B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2004AtmRe..72..239E,
  author = {{Eymet}, V. and {Dufresne}, J.~L. and {Ricchiazzi}, P. and {Fournier}, R. and 
	{Blanco}, S.},
  title = {{Long-wave radiative analysis of cloudy scattering atmospheres using a net exchange formulation}},
  journal = {Atmospheric Research},
  year = 2004,
  month = nov,
  volume = 72,
  pages = {239-261},
  abstract = {{The Net Exchange Formulation (NEF) is an alternative to the usual
radiative transfer equation. It was proposed in 1967 by Green [Q. J. R.
Meteorol. Soc. 93 (1967) 371] for atmospheric sciences and by Hottel
[H.C. Hottel, A.F. Sarofim. Radiative Transfer McGraw Hill, New York,
1967] for engineering sciences. Until now, the NEF has been used only in
a very few cases for atmospheric studies. Recently we have developed a
long-wave radiative code based on this formulation for a GCM of the Mars
planet. Here, we will present results for the Earth atmosphere, obtained
with a Monte Carlo Method based on the NEF. In this method, fluxes are
not addressed any more. The basic variables are the net exchange rates
(NER) between each pair of atmospheric layer ( i, j), i.e. the radiative
power emitted by i and absorbed by j minus the radiative power emitted
by j and absorbed by i. The graphical representation of the NER matrix
highlights the radiative exchanges that dominate the radiative budget of
the atmosphere and allows one to have a very good insight of the
radiative exchanges. Results will be presented for clear sky atmospheres
with Mid-Latitude Summer and Sub-Arctic Winter temperature profiles, and
for the same atmospheres with three different types of clouds. The
effect of scattering on long-wave radiative exchanges will also be
analysed.
}},
  doi = {10.1016/j.atmosres.2004.03.017},
  adsurl = {http://adsabs.harvard.edu/abs/2004AtmRe..72..239E},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2004GeoRL..31.3103M,
  author = {{Mahowald}, N.~M. and {Dufresne}, J.-L.},
  title = {{Sensitivity of TOMS aerosol index to boundary layer height: Implications for detection of mineral aerosol sources}},
  journal = {\grl},
  keywords = {Atmospheric Composition and Structure: Aerosols and particles (0345, 4801), Atmospheric Composition and Structure: Biosphere/atmosphere interactions, Global Change: Atmosphere (0315, 0325), Global Change: Biogeochemical processes (4805), Atmospheric Composition and Structure: Troposphere-composition and chemistry},
  year = 2004,
  month = feb,
  volume = 31,
  eid = {L03103},
  pages = {3103},
  abstract = {{The TOMS aerosol index (AI) is proposed as a powerful tool in
determining the sources of mineral aerosols. The sensitivity of the AI
to the height of the aerosol layer has been noted previously, but the
implications of this sensitivity for deducing sources has not been
explicitly considered. Here, we present a methodology and sensitivity
test to show the importance of spatial and temporal variations of the
planetary boundary layer height to deducing sources using the AI. These
results suggest that while dry topographic low sources may be large
sources of desert dust, conclusions eliminating other sources may be
premature, especially when these sources occur on the edges of deserts,
where boundary layer heights are lower, and human influences potentially
more important. The compounding problem of differentiating downwind
transport and local sources suggests it may not currently be possible to
use the AI to conclusively determine mineral aerosol source regions.
}},
  doi = {10.1029/2003GL018865},
  adsurl = {http://adsabs.harvard.edu/abs/2004GeoRL..31.3103M},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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