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@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=2011 -c $type="ARTICLE" -oc lmd_Boucher2011.txt -ob lmd_Boucher2011.bib /home/WWW/LMD/public/}}
  author = {{Kulmala}, M. and {Asmi}, A. and {Lappalainen}, H.~K. and {Baltensperger}, U. and 
	{Brenguier}, J.-L. and {Facchini}, M.~C. and {Hansson}, H.-C. and 
	{Hov}, {\O}. and {O'Dowd}, C.~D. and {P{\"o}schl}, U. and {Wiedensohler}, A. and 
	{Boers}, R. and {Boucher}, O. and {de Leeuw}, G. and {Denier van der Gon}, H.~A.~C. and 
	{Feichter}, J. and {Krejci}, R. and {Laj}, P. and {Lihavainen}, H. and 
	{Lohmann}, U. and {McFiggans}, G. and {Mentel}, T. and {Pilinis}, C. and 
	{Riipinen}, I. and {Schulz}, M. and {Stohl}, A. and {Swietlicki}, E. and 
	{Vignati}, E. and {Alves}, C. and {Amann}, M. and {Ammann}, M. and 
	{Arabas}, S. and {Artaxo}, P. and {Baars}, H. and {Beddows}, D.~C.~S. and 
	{Bergstr{\"o}m}, R. and {Beukes}, J.~P. and {Bilde}, M. and 
	{Burkhart}, J.~F. and {Canonaco}, F. and {Clegg}, S.~L. and 
	{Coe}, H. and {Crumeyrolle}, S. and {D'Anna}, B. and {Decesari}, S. and 
	{Gilardoni}, S. and {Fischer}, M. and {Fjaeraa}, A.~M. and {Fountoukis}, C. and 
	{George}, C. and {Gomes}, L. and {Halloran}, P. and {Hamburger}, T. and 
	{Harrison}, R.~M. and {Herrmann}, H. and {Hoffmann}, T. and 
	{Hoose}, C. and {Hu}, M. and {Hyv{\"a}rinen}, A. and {H{\~o}rrak}, U. and 
	{Iinuma}, Y. and {Iversen}, T. and {Josipovic}, M. and {Kanakidou}, M. and 
	{Kiendler-Scharr}, A. and {Kirkev{\aa}g}, A. and {Kiss}, G. and 
	{Klimont}, Z. and {Kolmonen}, P. and {Komppula}, M. and {Kristj{\'a}nsson}, J.-E. and 
	{Laakso}, L. and {Laaksonen}, A. and {Labonnote}, L. and {Lanz}, V.~A. and 
	{Lehtinen}, K.~E.~J. and {Rizzo}, L.~V. and {Makkonen}, R. and 
	{Manninen}, H.~E. and {McMeeking}, G. and {Merikanto}, J. and 
	{Minikin}, A. and {Mirme}, S. and {Morgan}, W.~T. and {Nemitz}, E. and 
	{O'Donnell}, D. and {Panwar}, T.~S. and {Pawlowska}, H. and 
	{Petzold}, A. and {Pienaar}, J.~J. and {Pio}, C. and {Plass-Duelmer}, C. and 
	{Prév{\^o}t}, A.~S.~H. and {Pryor}, S. and {Reddington}, C.~L. and 
	{Roberts}, G. and {Rosenfeld}, D. and {Schwarz}, J. and {Seland}, {\O}. and 
	{Sellegri}, K. and {Shen}, X.~J. and {Shiraiwa}, M. and {Siebert}, H. and 
	{Sierau}, B. and {Simpson}, D. and {Sun}, J.~Y. and {Topping}, D. and 
	{Tunved}, P. and {Vaattovaara}, P. and {Vakkari}, V. and {Veefkind}, J.~P. and 
	{Visschedijk}, A. and {Vuollekoski}, H. and {Vuolo}, R. and 
	{Wehner}, B. and {Wildt}, J. and {Woodward}, S. and {Worsnop}, D.~R. and 
	{van Zadelhoff}, G.-J. and {Zardini}, A.~A. and {Zhang}, K. and 
	{van Zyl}, P.~G. and {Kerminen}, V.-M. and {Carslaw}, K.~S. and 
	{Pandis}, S.~N.},
  title = {{General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) - integrating aerosol research from nano to global scales}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2011,
  month = dec,
  volume = 11,
  pages = {13061-13143},
  abstract = {{In this paper we describe and summarize the main achievements of the
European Aerosol Cloud Climate and Air Quality Interactions project
(EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December
2010 leaving a rich legacy including: (a) a comprehensive database with
a year of observations of the physical, chemical and optical properties
of aerosol particles over Europe, (b) comprehensive aerosol measurements
in four developing countries, (c) a database of airborne measurements of
aerosols and clouds over Europe during May 2008, (d) comprehensive
modeling tools to study aerosol processes fron nano to global scale and
their effects on climate and air quality. In addition a new Pan-European
aerosol emissions inventory was developed and evaluated, a new cluster
spectrometer was built and tested in the field and several new aerosol
parameterizations and computations modules for chemical transport and
global climate models were developed and evaluated. These achievements
and related studies have substantially improved our understanding and
reduced the uncertainties of aerosol radiative forcing and air
quality-climate interactions. The EUCAARI results can be utilized in
European and global environmental policy to assess the aerosol impacts
and the corresponding abatement strategies.
  doi = {10.5194/acp-11-13061-2011},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Bellouin}, N. and {Rae}, J. and {Jones}, A. and {Johnson}, C. and 
	{Haywood}, J. and {Boucher}, O.},
  title = {{Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {CMIP5, aerosol forcing, climate change, nitrate, sulfate, Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906), Global Change: Atmosphere (0315, 0325), Global Change: Earth system modeling (1225, 4316), Global Change: Global climate models (3337, 4928), Atmospheric Processes: Clouds and aerosols},
  year = 2011,
  month = oct,
  volume = 116,
  number = d15,
  eid = {D20206},
  pages = {20206},
  abstract = {{The latest Hadley Centre climate model, HadGEM2-ES, includes Earth
system components such as interactive chemistry and eight species of
tropospheric aerosols. It has been run for the period 1860-2100 in
support of the fifth phase of the Climate Model Intercomparison Project
(CMIP5). Anthropogenic aerosol emissions peak between 1980 and 2020,
resulting in a present-day all-sky top of the atmosphere aerosol forcing
of -1.6 and -1.4 W m$^{-2}$ with and without ammonium nitrate
aerosols, respectively, for the sum of direct and first indirect aerosol
forcings. Aerosol forcing becomes significantly weaker in the 21st
century, being weaker than -0.5 W m$^{-2}$ in 2100 without
nitrate. However, nitrate aerosols become the dominant species in Europe
and Asia and decelerate the decrease in global mean aerosol forcing.
Considering nitrate aerosols makes aerosol radiative forcing 2-4 times
stronger by 2100 depending on the representative concentration pathway,
although this impact is lessened when changes in the oxidation
properties of the atmosphere are accounted for. Anthropogenic aerosol
residence times increase in the future in spite of increased
precipitation, as cloud cover and aerosol-cloud interactions decrease in
tropical and midlatitude regions. Deposition of fossil fuel black carbon
onto snow and ice surfaces peaks during the 20th century in the Arctic
and Europe but keeps increasing in the Himalayas until the middle of the
21st century. Results presented here confirm the importance of aerosols
in influencing the Earth's climate, albeit with a reduced impact in the
future, and suggest that nitrate aerosols will partially replace
sulphate aerosols to become an important anthropogenic species in the
remainder of the 21st century.
  doi = {10.1029/2011JD016074},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Haywood}, J.~M. and {Bellouin}, N. and {Jones}, A. and {Boucher}, O. and 
	{Wild}, M. and {Shine}, K.~P.},
  title = {{The roles of aerosol, water vapor and cloud in future global dimming/brightening}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {aerosols, global brightening, global dimming, water vapor, Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906), Atmospheric Composition and Structure: Radiation: transmission and scattering, Atmospheric Processes: Clouds and aerosols, Oceanography: Biological and Chemical: Aerosols (0305, 4906)},
  year = 2011,
  month = oct,
  volume = 116,
  number = d15,
  eid = {D20203},
  pages = {20203},
  abstract = {{Observational evidence indicates significant regional trends in solar
radiation at the surface in both all-sky and cloud-free conditions.
Negative trends in the downwelling solar surface irradiance (SSI) have
become known as `dimming' while positive trends have become known as
`brightening'. We use the Met Office Hadley Centre HadGEM2 climate model
to model trends in cloud-free and total SSI from the pre-industrial to
the present-day and compare these against observations. Simulations
driven by CMIP5 emissions are used to model the future trends in
dimming/brightening up to the year 2100. The modeled trends are
reasonably consistent with observed regional trends in dimming and
brightening which are due to changes in concentrations in anthropogenic
aerosols and, potentially, changes in cloud cover owing to the aerosol
indirect effects and/or cloud feedback mechanisms. The future
dimming/brightening in cloud-free SSI is not only caused by changes in
anthropogenic aerosols: aerosol impacts are overwhelmed by a large
dimming caused by increases in water vapor. There is little trend in the
total SSI as cloud cover decreases in the climate model used here, and
compensates the effect of the change in water vapor. In terms of the
surface energy balance, these trends in SSI are obviously more than
compensated by the increase in the downwelling terrestrial irradiance
from increased water vapor concentrations. However, the study shows that
while water vapor is widely appreciated as a greenhouse gas, water vapor
impacts on the atmospheric transmission of solar radiation and the
future of global dimming/brightening should not be overlooked.
  doi = {10.1029/2011JD016000},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Hanappe}, P. and {Beurivé}, A. and {Laguzet}, F. and {Steels}, L. and 
	{Bellouin}, N. and {Boucher}, O. and {Yamazaki}, Y.~H. and {Aina}, T. and 
	{Allen}, M.},
  title = {{FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm}},
  journal = {Geoscientific Model Development},
  year = 2011,
  month = sep,
  volume = 4,
  pages = {835-844},
  abstract = {{We have optimised the atmospheric radiation algorithm of the FAMOUS
climate model on several hardware platforms. The optimisation involved
translating the Fortran code to C and restructuring the algorithm around
the computation of a single air column. Instead of the existing
MPI-based domain decomposition, we used a task queue and a thread pool
to schedule the computation of individual columns on the available
processors. Finally, four air columns are packed together in a single
data structure and computed simultaneously using Single Instruction
Multiple Data operations. 

The modified algorithm runs more than 50 times faster on the CELL's Synergistic Processing Element than on its main PowerPC processing element. On Intel-compatible processors, the new radiation code runs 4 times faster. On the tested graphics processor, using OpenCL, we find a speed-up of more than 2.5 times as compared to the original code on the main CPU. Because the radiation code takes more than 60 \% of the total CPU time, FAMOUS executes more than twice as fast. Our version of the algorithm returns bit-wise identical results, which demonstrates the robustness of our approach. We estimate that this project required around two and a half man-years of work. }}, doi = {10.5194/gmd-4-835-2011}, adsurl = {}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }
  author = {{Clark}, D.~B. and {Mercado}, L.~M. and {Sitch}, S. and {Jones}, C.~D. and 
	{Gedney}, N. and {Best}, M.~J. and {Pryor}, M. and {Rooney}, G.~G. and 
	{Essery}, R.~L.~H. and {Blyth}, E. and {Boucher}, O. and {Harding}, R.~J. and 
	{Huntingford}, C. and {Cox}, P.~M.},
  title = {{The Joint UK Land Environment Simulator (JULES), model description - Part 2: Carbon fluxes and vegetation dynamics}},
  journal = {Geoscientific Model Development},
  year = 2011,
  month = sep,
  volume = 4,
  pages = {701-722},
  abstract = {{The Joint UK Land Environment Simulator (JULES) is a process-based model
that simulates the fluxes of carbon, water, energy and momentum between
the land surface and the atmosphere. Many studies have demonstrated the
important role of the land surface in the functioning of the Earth
System. Different versions of JULES have been employed to quantify the
effects on the land carbon sink of climate change, increasing
atmospheric carbon dioxide concentrations, changing atmospheric aerosols
and tropospheric ozone, and the response of methane emissions from
wetlands to climate change. 

This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model.

The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model. }}, doi = {10.5194/gmd-4-701-2011}, adsurl = {}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }
  author = {{Best}, M.~J. and {Pryor}, M. and {Clark}, D.~B. and {Rooney}, G.~G. and 
	{Essery}, R.~L.~H. and {Ménard}, C.~B. and {Edwards}, J.~M. and 
	{Hendry}, M.~A. and {Porson}, A. and {Gedney}, N. and {Mercado}, L.~M. and 
	{Sitch}, S. and {Blyth}, E. and {Boucher}, O. and {Cox}, P.~M. and 
	{Grimmond}, C.~S.~B. and {Harding}, R.~J.},
  title = {{The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes}},
  journal = {Geoscientific Model Development},
  year = 2011,
  month = sep,
  volume = 4,
  pages = {677-699},
  abstract = {{This manuscript describes the energy and water components of a new
community land surface model called the Joint UK Land Environment
Simulator (JULES). This is developed from the Met Office Surface
Exchange Scheme (MOSES). It can be used as a stand alone land surface
model driven by observed forcing data, or coupled to an atmospheric
global circulation model. The JULES model has been coupled to the Met
Office Unified Model (UM) and as such provides a unique opportunity for
the research community to contribute their research to improve both
world-leading operational weather forecasting and climate change
prediction systems. In addition JULES, and its forerunner MOSES, have
been the basis for a number of very high-profile papers concerning the
land-surface and climate over the last decade. JULES has a modular
structure aligned to physical processes, providing the basis for a
flexible modelling platform.
  doi = {10.5194/gmd-4-677-2011},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Verma}, S. and {Venkataraman}, C. and {Boucher}, O.},
  title = {{Attribution of aerosol radiative forcing over India during the winter monsoon to emissions from source categories and geographical regions}},
  journal = {Atmospheric Environment},
  year = 2011,
  month = aug,
  volume = 45,
  pages = {4398-4407},
  abstract = {{We examine the aerosol radiative effects due to aerosols emitted from
different emission sectors (anthropogenic and natural) and originating
from different geographical regions within and outside India during the
northeast (NE) Indian winter monsoon (January-March). These studies are
carried out through aerosol transport simulations in the general
circulation (GCM) model of the Laboratoire de Météorologie
Dynamique (LMD). The model estimates of aerosol single scattering albedo
(SSA) show lower values (0.86-0.92) over the region north to 10{\deg}N
comprising of the Indian subcontinent, Bay of Bengal, and parts of the
Arabian Sea compared to the region south to 10{\deg}N where the estimated
SSA values lie in the range 0.94-0.98. The model estimated SSA is
consistent with the SSA values inferred through measurements on various
platforms. Aerosols of anthropogenic origin reduce the incoming solar
radiation at the surface by a factor of 10-20 times the reduction due to
natural aerosols. At the top-of-atmosphere (TOA), aerosols from biofuel
use cause positive forcing compared to the negative forcing from fossil
fuel and natural sources in correspondence with the distribution of SSA
which is estimated to be the lowest (0.7-0.78) from biofuel combustion
emissions. Aerosols originating from India and Africa-west Asia lead to
the reduction in surface radiation (-3 to -8 W m $^{-2}$) by
40-60\% of the total reduction in surface radiation due to all aerosols
over the Indian subcontinent and adjoining ocean. Aerosols originating
from India and Africa-west Asia also lead to positive radiative effects
at TOA over the Arabian Sea, central India (CNI), with the highest
positive radiative effects over the Bay of Bengal and cause either
negative or positive effects over the Indo-Gangetic plain (IGP).
  doi = {10.1016/j.atmosenv.2011.05.048},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Huneeus}, N. and {Schulz}, M. and {Balkanski}, Y. and {Griesfeller}, J. and 
	{Prospero}, J. and {Kinne}, S. and {Bauer}, S. and {Boucher}, O. and 
	{Chin}, M. and {Dentener}, F. and {Diehl}, T. and {Easter}, R. and 
	{Fillmore}, D. and {Ghan}, S. and {Ginoux}, P. and {Grini}, A. and 
	{Horowitz}, L. and {Koch}, D. and {Krol}, M.~C. and {Landing}, W. and 
	{Liu}, X. and {Mahowald}, N. and {Miller}, R. and {Morcrette}, J.-J. and 
	{Myhre}, G. and {Penner}, J. and {Perlwitz}, J. and {Stier}, P. and 
	{Takemura}, T. and {Zender}, C.~S.},
  title = {{Global dust model intercomparison in AeroCom phase I}},
  journal = {Atmospheric Chemistry \& Physics},
  year = 2011,
  month = aug,
  volume = 11,
  pages = {7781-7816},
  abstract = {{This study presents the results of a broad intercomparison of a total of
15 global aerosol models within the AeroCom project. Each model is
compared to observations related to desert dust aerosols, their direct
radiative effect, and their impact on the biogeochemical cycle, i.e.,
aerosol optical depth (AOD) and dust deposition. Additional comparisons
to Angstr{\"o}m exponent (AE), coarse mode AOD and dust surface
concentrations are included to extend the assessment of model
performance and to identify common biases present in models. These data
comprise a benchmark dataset that is proposed for model inspection and
future dust model development. There are large differences among the
global models that simulate the dust cycle and its impact on climate. In
general, models simulate the climatology of vertically integrated
parameters (AOD and AE) within a factor of two whereas the total
deposition and surface concentration are reproduced within a factor of
10. In addition, smaller mean normalized bias and root mean square
errors are obtained for the climatology of AOD and AE than for total
deposition and surface concentration. Characteristics of the datasets
used and their uncertainties may influence these differences. Large
uncertainties still exist with respect to the deposition fluxes in the
southern oceans. Further measurements and model studies are necessary to
assess the general model performance to reproduce dust deposition in
ocean regions sensible to iron contributions. Models overestimate the
wet deposition in regions dominated by dry deposition. They generally
simulate more realistic surface concentration at stations downwind of
the main sources than at remote ones. Most models simulate the gradient
in AOD and AE between the different dusty regions. However the
seasonality and magnitude of both variables is better simulated at
African stations than Middle East ones. The models simulate the offshore
transport of West Africa throughout the year but they overestimate the
AOD and they transport too fine particles. The models also reproduce the
dust transport across the Atlantic in the summer in terms of both AOD
and AE but not so well in winter-spring nor the southward displacement
of the dust cloud that is responsible of the dust transport into South
America. Based on the dependency of AOD on aerosol burden and size
distribution we use model bias with respect to AOD and AE to infer the
bias of the dust emissions in Africa and the Middle East. According to
this analysis we suggest that a range of possible emissions for North
Africa is 400 to 2200 Tg yr$^{-1}$ and in the Middle East 26 to
526 Tg yr$^{-1}$.
  doi = {10.5194/acp-11-7781-2011},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Boucher}, O.},
  title = {{Atmospheric science: Seeing through contrails}},
  journal = {Nature Climate Change},
  year = 2011,
  month = apr,
  volume = 1,
  pages = {24-25},
  abstract = {{Contrails formed by aircraft can evolve into cirrus clouds
indistinguishable from those formed naturally. These 'spreading
contrails' may be causing more climate warming today than all the carbon
dioxide emitted by aircraft since the start of aviation.
  doi = {10.1038/nclimate1078},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Mangold}, A. and {de Backer}, H. and {de Paepe}, B. and {Dewitte}, S. and 
	{Chiapello}, I. and {Derimian}, Y. and {Kacenelenbogen}, M. and 
	{LéOn}, J.-F. and {Huneeus}, N. and {Schulz}, M. and {Ceburnis}, D. and 
	{O'Dowd}, C. and {Flentje}, H. and {Kinne}, S. and {Benedetti}, A. and 
	{Morcrette}, J.-J. and {Boucher}, O.},
  title = {{Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 3. Evaluation by means of case studies}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906), Atmospheric Composition and Structure: Troposphere: composition and chemistry, aerosol modeling, atmospheric composition, model evaluation},
  year = 2011,
  month = feb,
  volume = 116,
  eid = {D03302},
  pages = {3302},
  abstract = {{A near real-time system for assimilation and forecasts of aerosols,
greenhouse and trace gases, extending the ECMWF Integrated Forecasting
System (IFS), has been developed in the framework of the Global and
regional Earth-system Monitoring using Satellite and in-situ data (GEMS)
project. The GEMS aerosol modeling system is novel as it is the first
aerosol model fully coupled to a numerical weather prediction model with
data assimilation. A reanalysis of the period 2003-2009 has been carried
out with the same system. During its development phase, the aerosol
system was first run for the time period January 2003 to December 2004
and included sea salt, desert dust, organic matter, black carbon, and
sulfate aerosols. In the analysis, Moderate Resolution Imaging
Spectroradiometer (MODIS) total aerosol optical depth (AOD) at 550 nm
over ocean and land (except over bright surfaces) was assimilated. This
work evaluates the performance of the aerosol system by means of case
studies. The case studies include (1) the summer heat wave in Europe in
August 2003, characterized by forest fire aerosol and conditions of high
temperatures and stagnation, favoring photochemistry and secondary
aerosol formation, (2) a large Saharan dust event in March 2004, and (3)
periods of high and low sea salt aerosol production. During the heat
wave period in 2003, the linear correlation coefficients between modeled
and observed AOD (550 nm) and between modeled and observed PM2.5 mass
concentrations are 0.82 and 0.71, respectively, for all investigated
sites together. The AOD is slightly and the PM2.5 mass concentration is
clearly overestimated by the aerosol model during this period. The
simulated sulfate mass concentration is significantly correlated with
observations but is distinctly overestimated. The horizontal and
vertical locations of the main features of the aerosol distribution
during the Saharan dust outbreak are generally well captured, as well as
the timing of the AOD peaks. The aerosol model simulates winter sea salt
AOD reasonably well, however, showing a general overestimation. Summer
sea salt events show a better agreement. Overall, the assimilation of
MODIS AOD data improves the subsequent aerosol predictions when compared
with observations, in particular concerning the correlation and AOD peak
values. The assimilation is less effective in correcting a positive
(PM2.5, sulfate mass concentration, Angstr{\"o}m exponent) or negative
(desert dust plume AOD) model bias.
  doi = {10.1029/2010JD014864},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
  author = {{Andrews}, T. and {Doutriaux-Boucher}, M. and {Boucher}, O. and 
	{Forster}, P.~M.},
  title = {{A regional and global analysis of carbon dioxide physiological forcing and its impact on climate}},
  journal = {Climate Dynamics},
  keywords = {Carbon dioxide physiological forcing, Climate response, Hydrological cycle, Surface energy balance, Fast responses},
  year = 2011,
  month = feb,
  volume = 36,
  pages = {783-792},
  abstract = {{An increase in atmospheric carbon dioxide concentration has both a
radiative (greenhouse) effect and a physiological effect on climate. The
physiological effect forces climate as plant stomata do not open as wide
under enhanced CO$_{2}$ levels and this alters the surface energy
balance by reducing the evapotranspiration flux to the atmosphere, a
process referred to as `carbon dioxide physiological forcing'. Here the
climate impact of the carbon dioxide physiological forcing is isolated
using an ensemble of twelve 5-year experiments with the Met Office
Hadley Centre HadCM3LC fully coupled atmosphere-ocean model where
atmospheric carbon dioxide levels are instantaneously quadrupled and
thereafter held constant. Fast responses (within a few months) to carbon
dioxide physiological forcing are analyzed at a global and regional
scale. Results show a strong influence of the physiological forcing on
the land surface energy budget, hydrological cycle and near surface
climate. For example, global precipitation rate reduces by \~{}3\% with
significant decreases over most land-regions, mainly from reductions to
convective rainfall. This fast hydrological response is still evident
after 5 years of model integration. Decreased evapotranspiration over
land also leads to land surface warming and a drying of near surface
air, both of which lead to significant reductions in near surface
relative humidity (\~{}6\%) and cloud fraction (\~{}3\%). Patterns of fast
responses consistently show that results are largest in the Amazon and
central African forest, and to a lesser extent in the boreal and
temperate forest. Carbon dioxide physiological forcing could be a source
of uncertainty in many model predicted quantities, such as climate
sensitivity, transient climate response and the hydrological
sensitivity. These results highlight the importance of including
biological components of the Earth system in climate change studies.
  doi = {10.1007/s00382-010-0742-1},
  adsurl = {},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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Real time LMDZ simulations

Today's LMDZ meteogram for the SIRTA site

Intranet EMC3

Intranet EMC3