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lmd_Boucher2009.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:"Boucher"  ' -c year=2009 -c $type="ARTICLE" -oc lmd_Boucher2009.txt -ob lmd_Boucher2009.bib /home/WWW/LMD/public/Publis_LMDEMC3.link.bib}}
@article{2009GMD.....2..213H,
  author = {{Huneeus}, N. and {Boucher}, O. and {Chevallier}, F.},
  title = {{Simplified aerosol modeling for variational data assimilation}},
  journal = {Geoscientific Model Development},
  year = 2009,
  month = nov,
  volume = 2,
  pages = {213-229},
  abstract = {{We have developed a simplified aerosol model together with its tangent
linear and adjoint versions for the ultimate aim of optimizing global
aerosol and aerosol precursor emission using variational data
assimilation. The model was derived from the general circulation model
LMDz; it groups together the 24 aerosol species simulated in LMDz into 4
species, namely gaseous precursors, fine mode aerosols, coarse mode
desert dust and coarse mode sea salt. The emissions have been kept as in
the original model. Modifications, however, were introduced in the
computation of aerosol optical depth and in the processes of
sedimentation, dry and wet deposition and sulphur chemistry to ensure
consistency with the new set of species and their composition. 

The simplified model successfully manages to reproduce the main features of the aerosol distribution in LMDz. The largest differences in aerosol load are observed for fine mode aerosols and gaseous precursors. Differences between the original and simplified models are mainly associated to the new deposition and sedimentation velocities consistent with the definition of species in the simplified model and the simplification of the sulphur chemistry. Furthermore, simulated aerosol optical depth remains within the variability of monthly AERONET observations for all aerosol types and all sites throughout most of the year. Largest differences are observed over sites with strong desert dust influence. In terms of the daily aerosol variability, the model is less able to reproduce the observed variability from the AERONET data with larger discrepancies in stations affected by industrial aerosols. The simplified model however, closely follows the daily simulation from LMDz.

Sensitivity analyses with the tangent linear version show that the simplified sulphur chemistry is the dominant process responsible for the strong non-linearity of the model. }}, adsurl = {http://adsabs.harvard.edu/abs/2009GMD.....2..213H}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }
@article{2009ACP.....9.9001K,
  author = {{Koch}, D. and {Schulz}, M. and {Kinne}, S. and {McNaughton}, C. and 
	{Spackman}, J.~R. and {Balkanski}, Y. and {Bauer}, S. and {Berntsen}, T. and 
	{Bond}, T.~C. and {Boucher}, O. and {Chin}, M. and {Clarke}, A. and 
	{de Luca}, N. and {Dentener}, F. and {Diehl}, T. and {Dubovik}, O. and 
	{Easter}, R. and {Fahey}, D.~W. and {Feichter}, J. and {Fillmore}, D. and 
	{Freitag}, S. and {Ghan}, S. and {Ginoux}, P. and {Gong}, S. and 
	{Horowitz}, L. and {Iversen}, T. and {Kirkev{\aa}g}, A. and 
	{Klimont}, Z. and {Kondo}, Y. and {Krol}, M. and {Liu}, X. and 
	{Miller}, R. and {Montanaro}, V. and {Moteki}, N. and {Myhre}, G. and 
	{Penner}, J.~E. and {Perlwitz}, J. and {Pitari}, G. and {Reddy}, S. and 
	{Sahu}, L. and {Sakamoto}, H. and {Schuster}, G. and {Schwarz}, J.~P. and 
	{Seland}, {\O}. and {Stier}, P. and {Takegawa}, N. and {Takemura}, T. and 
	{Textor}, C. and {van Aardenne}, J.~A. and {Zhao}, Y.},
  title = {{Evaluation of black carbon estimations in global aerosol models}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2009,
  month = nov,
  volume = 9,
  pages = {9001-9026},
  abstract = {{We evaluate black carbon (BC) model predictions from the AeroCom model
intercomparison project by considering the diversity among year 2000
model simulations and comparing model predictions with available
measurements. These model-measurement intercomparisons include BC
surface and aircraft concentrations, aerosol absorption optical depth
(AAOD) retrievals from AERONET and Ozone Monitoring Instrument (OMI) and
BC column estimations based on AERONET. In regions other than Asia, most
models are biased high compared to surface concentration measurements.
However compared with (column) AAOD or BC burden retreivals, the models
are generally biased low. The average ratio of model to retrieved AAOD
is less than 0.7 in South American and 0.6 in African biomass burning
regions; both of these regions lack surface concentration measurements.
In Asia the average model to observed ratio is 0.7 for AAOD and 0.5 for
BC surface concentrations. Compared with aircraft measurements over the
Americas at latitudes between 0 and 50N, the average model is a factor
of 8 larger than observed, and most models exceed the measured BC
standard deviation in the mid to upper troposphere. At higher latitudes
the average model to aircraft BC ratio is 0.4 and models underestimate
the observed BC loading in the lower and middle troposphere associated
with springtime Arctic haze. Low model bias for AAOD but overestimation
of surface and upper atmospheric BC concentrations at lower latitudes
suggests that most models are underestimating BC absorption and should
improve estimates for refractive index, particle size, and optical
effects of BC coating. Retrieval uncertainties and/or differences with
model diagnostic treatment may also contribute to the model-measurement
disparity. Largest AeroCom model diversity occurred in northern Eurasia
and the remote Arctic, regions influenced by anthropogenic sources.
Changing emissions, aging, removal, or optical properties within a
single model generated a smaller change in model predictions than the
range represented by the full set of AeroCom models. Upper tropospheric
concentrations of BC mass from the aircraft measurements are suggested
to provide a unique new benchmark to test scavenging and vertical
dispersion of BC in global models.
}},
  adsurl = {http://adsabs.harvard.edu/abs/2009ACP.....9.9001K},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009ACP.....9.8697Q,
  author = {{Quaas}, J. and {Ming}, Y. and {Menon}, S. and {Takemura}, T. and 
	{Wang}, M. and {Penner}, J.~E. and {Gettelman}, A. and {Lohmann}, U. and 
	{Bellouin}, N. and {Boucher}, O. and {Sayer}, A.~M. and {Thomas}, G.~E. and 
	{McComiskey}, A. and {Feingold}, G. and {Hoose}, C. and {Kristj{\'a}nsson}, J.~E. and 
	{Liu}, X. and {Balkanski}, Y. and {Donner}, L.~J. and {Ginoux}, P.~A. and 
	{Stier}, P. and {Grandey}, B. and {Feichter}, J. and {Sednev}, I. and 
	{Bauer}, S.~E. and {Koch}, D. and {Grainger}, R.~G. and {Kirkev{\aa}g}, A. and 
	{Iversen}, T. and {Seland}, {\O}. and {Easter}, R. and {Ghan}, S.~J. and 
	{Rasch}, P.~J. and {Morrison}, H. and {Lamarque}, J.-F. and 
	{Iacono}, M.~J. and {Kinne}, S. and {Schulz}, M.},
  title = {{Aerosol indirect effects - general circulation model intercomparison and evaluation with satellite data}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2009,
  month = nov,
  volume = 9,
  pages = {8697-8717},
  abstract = {{Aerosol indirect effects continue to constitute one of the most
important uncertainties for anthropogenic climate perturbations. Within
the international AEROCOM initiative, the representation of
aerosol-cloud-radiation interactions in ten different general
circulation models (GCMs) is evaluated using three satellite datasets.
The focus is on stratiform liquid water clouds since most GCMs do not
include ice nucleation effects, and none of the model explicitly
parameterises aerosol effects on convective clouds. We compute
statistical relationships between aerosol optical depth
({$\tau$}$_{a}$) and various cloud and radiation quantities in a
manner that is consistent between the models and the satellite data. It
is found that the model-simulated influence of aerosols on cloud droplet
number concentration (N$_{d}$) compares relatively well to the
satellite data at least over the ocean. The relationship between
{$\tau$}$_{a}$ and liquid water path is simulated much too strongly
by the models. This suggests that the implementation of the second
aerosol indirect effect mainly in terms of an autoconversion
parameterisation has to be revisited in the GCMs. A positive
relationship between total cloud fraction (f$_{cld}$) and
{$\tau$}$_{a}$ as found in the satellite data is simulated by the
majority of the models, albeit less strongly than that in the satellite
data in most of them. In a discussion of the hypotheses proposed in the
literature to explain the satellite-derived strong
f$_{cld}$-{$\tau$}$_{a}$ relationship, our results
indicate that none can be identified as a unique explanation.
Relationships similar to the ones found in satellite data between
{$\tau$}$_{a}$ and cloud top temperature or outgoing long-wave
radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate
a negative OLR-{$\tau$}$_{a}$ relationship show a strong
positive correlation between {$\tau$}$_{a}$ and f$_{cld}$. The
short-wave total aerosol radiative forcing as simulated by the GCMs is
strongly influenced by the simulated anthropogenic fraction of
{$\tau$}$_{a}$, and parameterisation assumptions such as a lower
bound on N$_{d}$. Nevertheless, the strengths of the statistical
relationships are good predictors for the aerosol forcings in the
models. An estimate of the total short-wave aerosol forcing inferred
from the combination of these predictors for the modelled forcings with
the satellite-derived statistical relationships yields a global annual
mean value of -1.5{\plusmn}0.5 Wm$^{-2}$. In an
alternative approach, the radiative flux perturbation due to
anthropogenic aerosols can be broken down into a component over the
cloud-free portion of the globe (approximately the aerosol direct
effect) and a component over the cloudy portion of the globe
(approximately the aerosol indirect effect). An estimate obtained by
scaling these simulated clear- and cloudy-sky forcings with estimates of
anthropogenic {$\tau$}$_{a}$ and satellite-retrieved
N$_{d}$-{$\tau$}$_{a}$ regression slopes, respectively,
yields a global, annual-mean aerosol direct effect estimate of
-0.4{\plusmn}0.2 Wm$^{-2}$ and a cloudy-sky (aerosol
indirect effect) estimate of -0.7{\plusmn}0.5
Wm$^{-2}$, with a total estimate of -1.2{\plusmn}0.4
Wm$^{-2}$.
}},
  adsurl = {http://adsabs.harvard.edu/abs/2009ACP.....9.8697Q},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009ACP.....9.8493Q,
  author = {{Quaas}, J. and {Boucher}, O. and {Jones}, A. and {Weedon}, G.~P. and 
	{Kieser}, J. and {Joos}, H.},
  title = {{Exploiting the weekly cycle as observed over Europe to analyse aerosol indirect effects in two climate models}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2009,
  month = nov,
  volume = 9,
  pages = {8493-8501},
  abstract = {{A weekly cycle in aerosol pollution and some meteorological quantities
is observed over Europe. In the present study we exploit this effect to
analyse aerosol-cloud-radiation interactions. A weekly cycle is imposed
on anthropogenic emissions in two general circulation models that
include parameterizations of aerosol processes and cloud microphysics.
It is found that the simulated weekly cycles in sulfur dioxide, sulfate,
and aerosol optical depth in both models agree reasonably well with
those observed indicating model skill in simulating the aerosol cycle. A
distinct weekly cycle in cloud droplet number concentration is
demonstrated in both observations and models. For other variables, such
as cloud liquid water path, cloud cover, top-of-the-atmosphere radiation
fluxes, precipitation, and surface temperature, large variability and
contradictory results between observations, model simulations, and model
control simulations without a weekly cycle in emissions prevent us from
reaching any firm conclusions about the potential aerosol impact on
meteorology or the realism of the modelled second aerosol indirect
effects.
}},
  adsurl = {http://adsabs.harvard.edu/abs/2009ACP.....9.8493Q},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009ERL.....4d4007B,
  author = {{Boucher}, O. and {Friedlingstein}, P. and {Collins}, B. and 
	{Shine}, K.~P.},
  title = {{The indirect global warming potential and global temperature change potential due to methane oxidation}},
  journal = {Environmental Research Letters},
  year = 2009,
  month = oct,
  volume = 4,
  number = 4,
  eid = {044007},
  pages = {044007},
  abstract = {{Methane is the second most important anthropogenic greenhouse gas in the
atmosphere next to carbon dioxide. Its global warming potential (GWP)
for a time horizon of 100 years is 25, which makes it an attractive
target for climate mitigation policies. Although the methane GWP
traditionally includes the methane indirect effects on the
concentrations of ozone and stratospheric water vapour, it does not take
into account the production of carbon dioxide from methane oxidation. We
argue here that this CO$_{2}$-induced effect should be included
for fossil sources of methane, which results in slightly larger GWP
values for all time horizons. If the global temperature change potential
is used as an alternative climate metric, then the impact of the
CO$_{2}$-induced effect is proportionally much larger. We also
discuss what the correction term should be for methane from
anthropogenic biogenic sources.
}},
  doi = {10.1088/1748-9326/4/4/044007},
  adsurl = {http://adsabs.harvard.edu/abs/2009ERL.....4d4007B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009JGRD..11413205B,
  author = {{Benedetti}, A. and {Morcrette}, J.-J. and {Boucher}, O. and 
	{Dethof}, A. and {Engelen}, R.~J. and {Fisher}, M. and {Flentje}, H. and 
	{Huneeus}, N. and {Jones}, L. and {Kaiser}, J.~W. and {Kinne}, S. and 
	{Mangold}, A. and {Razinger}, M. and {Simmons}, A.~J. and {Suttie}, M.
	},
  title = {{Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906), Atmospheric Processes: Data assimilation, Atmospheric Composition and Structure: Pollution: urban and regional (0305, 0478, 4251), Paleoceanography: Aerosols (0305, 4801), aerosol analysis, aerosol forecast, data assimiliation},
  year = 2009,
  month = jul,
  volume = 114,
  number = d13,
  eid = {D13205},
  pages = {13205},
  abstract = {{This study presents the new aerosol assimilation system, developed at
the European Centre for Medium-Range Weather Forecasts, for the Global
and regional Earth-system Monitoring using Satellite and in-situ data
(GEMS) project. The aerosol modeling and analysis system is fully
integrated in the operational four-dimensional assimilation apparatus.
Its purpose is to produce aerosol forecasts and reanalyses of aerosol
fields using optical depth data from satellite sensors. This paper is
the second of a series which describes the GEMS aerosol effort. It
focuses on the theoretical architecture and practical implementation of
the aerosol assimilation system. It also provides a discussion of the
background errors and observations errors for the aerosol fields, and
presents a subset of results from the 2-year reanalysis which has been
run for 2003 and 2004 using data from the Moderate Resolution Imaging
Spectroradiometer on the Aqua and Terra satellites. Independent data
sets are used to show that despite some compromises that have been made
for feasibility reasons in regards to the choice of control variable and
error characteristics, the analysis is very skillful in drawing to the
observations and in improving the forecasts of aerosol optical depth.
}},
  doi = {10.1029/2008JD011115},
  adsurl = {http://adsabs.harvard.edu/abs/2009JGRD..11413205B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009JGRD..11410106J,
  author = {{Jones}, A. and {Haywood}, J. and {Boucher}, O.},
  title = {{Climate impacts of geoengineering marine stratocumulus clouds}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {Atmospheric Processes: Climate change and variability (1616, 1635, 3309, 4215, 4513), Atmospheric Composition and Structure: Cloud/radiation interaction, Global Change: Global climate models (3337, 4928), Global Change: Regional climate change, Atmospheric Processes: Clouds and aerosols, geoengineering, climate change, cloud modification},
  year = 2009,
  month = may,
  volume = 114,
  number = d13,
  eid = {D10106},
  pages = {10106},
  abstract = {{Theoretical potential geoengineering solutions to the global warming
problem have recently been proposed. Here, we present an idealized study
of the climate response to deliberately seeding large-scale
stratocumulus cloud decks in the North Pacific, South Pacific, and South
Atlantic, thereby inducing cooling via aerosol indirect effects.
Atmosphere-only, atmosphere/mixed-layer ocean, and fully coupled
atmosphere/ocean versions of the Met Office Hadley Centre model are used
to investigate the radiative forcing, climate efficacy, and regional
response of temperature, precipitation, and net primary productivity to
such geoengineering. The radiative forcing simulations indicate that,
for our parameterization of aerosol indirect effects, up to 35\% of the
radiative forcing due to current levels of greenhouse gases could be
offset by stratocumulus modification. Equilibrium simulations with the
atmosphere/mixed-layer ocean model, wherein each of the three
stratocumulus sheets is modified in turn, reveal that the most efficient
cooling per unit radiative forcing occurs when the South Pacific
stratocumulus sheet is modified. Transient coupled model simulations
suggest that geoengineering all three stratocumulus areas delays the
simulated global warming by about 25 years. These simulations also
indicate that, while some areas experience increases in precipitation
and net primary productivity, sharp decreases are simulated in South
America, with particularly detrimental impacts on the Amazon rain
forest. These results show that, while some areas benefit from
geoengineering, there are significant areas where the response could be
very detrimental with implications for the practical applicability of
such a scheme.
}},
  doi = {10.1029/2008JD011450},
  adsurl = {http://adsabs.harvard.edu/abs/2009JGRD..11410106J},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009JGRD..114.6206M,
  author = {{Morcrette}, J.-J. and {Boucher}, O. and {Jones}, L. and {Salmond}, D. and 
	{Bechtold}, P. and {Beljaars}, A. and {Benedetti}, A. and {Bonet}, A. and 
	{Kaiser}, J.~W. and {Razinger}, M. and {Schulz}, M. and {Serrar}, S. and 
	{Simmons}, A.~J. and {Sofiev}, M. and {Suttie}, M. and {Tompkins}, A.~M. and 
	{Untch}, A.},
  title = {{Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: Forward modeling}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906), Global Change: Earth system modeling (1225), Atmospheric Processes: Clouds and aerosols, aerosol modelling, weather forecast},
  year = 2009,
  month = mar,
  volume = 114,
  eid = {D06206},
  pages = {6206},
  abstract = {{This paper presents the aerosol modeling now part of the ECMWF
Integrated Forecasting System (IFS). It includes new prognostic
variables for the mass of sea salt, dust, organic matter and black
carbon, and sulphate aerosols, interactive with both the dynamics and
the physics of the model. It details the various parameterizations used
in the IFS to account for the presence of tropospheric aerosols. Details
are given of the various formulations and data sets for the sources of
the different aerosols and of the parameterizations describing their
sinks. Comparisons of monthly mean and daily aerosol quantities like
optical depths against satellite and surface observations are presented.
The capability of the forecast model to simulate aerosol events is
illustrated through comparisons of dust plume events. The ECMWF IFS
provides a good description of the horizontal distribution and temporal
variability of the main aerosol types. The forecast-only model described
here generally gives the total aerosol optical depth within 0.12 of the
relevant observations and can therefore provide the background
trajectory information for the aerosol assimilation system described in
part 2 of this paper.
}},
  doi = {10.1029/2008JD011235},
  adsurl = {http://adsabs.harvard.edu/abs/2009JGRD..114.6206M},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009ClDy...32..237B,
  author = {{Boucher}, O. and {Jones}, A. and {Betts}, R.~A.},
  title = {{Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3}},
  journal = {Climate Dynamics},
  keywords = {Carbon dioxide, Physiological forcing, Climate response, Feedbacks},
  year = 2009,
  month = feb,
  volume = 32,
  pages = {237-249},
  abstract = {{The concentration of carbon dioxide in the atmosphere acts to control
the stomatal conductance of plants. There is observational and modelling
evidence that an increase in the atmospheric concentration of
CO$_{2}$ would suppress the evapotranspiration (ET) rate over
land. This process is known as CO$_{2}$ physiological forcing and
has been shown to induce changes in surface temperature and continental
runoff. We analyse two transient climate simulations for the
twenty-first century to isolate the climate response to the
CO$_{2}$ physiological forcing. The land surface warming
associated with the decreased ET rate is accompanied by an increase in
the atmospheric lapse rate, an increase in specific humidity, but a
decrease in relative humidity and stratiform cloud over land. We find
that the water vapour feedback more than compensates for the decrease in
latent heat flux over land as far as the budget of atmospheric water
vapour is concerned. There is evidence that surface snow, water vapour
and cloudiness respond to the CO$_{2}$ physiological forcing and
all contribute to further warm the climate system. The climate response
to the CO$_{2}$ physiological forcing has a quite different
signature to that from the CO$_{2}$ radiative forcing, especially
in terms of the changes in the temperature vertical profile and surface
energy budget over land.
}},
  doi = {10.1007/s00382-008-0459-6},
  adsurl = {http://adsabs.harvard.edu/abs/2009ClDy...32..237B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009GeoRL..36.2703D,
  author = {{Doutriaux-Boucher}, M. and {Webb}, M.~J. and {Gregory}, J.~M. and 
	{Boucher}, O.},
  title = {{Carbon dioxide induced stomatal closure increases radiative forcing via a rapid reduction in low cloud}},
  journal = {\grl},
  keywords = {Biogeosciences: Carbon cycling (4806), Global Change: Global climate models (3337, 4928), Global Change: Land/atmosphere interactions (1218, 1843, 3322), Atmospheric Processes: Clouds and cloud feedbacks},
  year = 2009,
  month = jan,
  volume = 36,
  eid = {L02703},
  pages = {2703},
  abstract = {{We performed an ensemble of twelve five-year experiments using a coupled
climate-carbon-cycle model with scenarios of prescribed atmospheric
carbon dioxide concentration; CO$_{2}$ was instantaneously doubled
or quadrupled at the start of the experiments. Within these five years,
climate feedback is not significantly influenced by the effects of
climate change on the carbon system. However, rapid changes take place,
within much less than a year, due to the physiological effect of
CO$_{2}$ on plant stomatal conductance, leading to adjustment in
the shortwave cloud radiative effect over land, due to a reduction in
low cloud cover. This causes a 10\% enhancement to the radiative forcing
due to CO$_{2}$, which leads to an increase in the equilibrium
warming of 0.4 and 0.7 K for doubling and quadrupling. The implications
for calibration of energy-balance models are discussed.
}},
  doi = {10.1029/2008GL036273},
  adsurl = {http://adsabs.harvard.edu/abs/2009GeoRL..36.2703D},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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