lmd_Li2009.bib
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@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{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..11417207J,
author = {{Jin}, X. and {Wu}, T. and {Li}, L. and {Shi}, C.},
title = {{Cloudiness characteristics over Southeast Asia from satellite FY-2C and their comparison to three other cloud data sets}},
journal = {Journal of Geophysical Research (Atmospheres)},
keywords = {Atmospheric Processes: Climatology (1616, 1620, 3305, 4215, 8408), Atmospheric Processes: Clouds and cloud feedbacks, Atmospheric Processes: General circulation (1223), Atmospheric Processes: Remote sensing, Geographic Location: Asia, FY-2C satellite cloud amount, surface-observed cloud, comparison with other satellites},
year = 2009,
month = sep,
volume = 114,
number = d13,
eid = {D17207},
pages = {17207},
abstract = {{Fengyun-2C (FY-2C), launched in October 2004, is the first operational
geostationary meteorological satellite in China. It can provide 1-h
interval cloudiness products with a spatial resolution of 0.04{\deg}
latitude {\times} 0.04{\deg} longitude. The main characteristics of the
regional-scale clouds from a 2-year FY-2C data set (from July 2005 to
June 2007) are presented, including the spatial distribution and the
annual and diurnal cycles of cloudiness. The reliability of FY-2C cloud
products over Southeast Asia is investigated through comparisons to
cloud cover from the International Satellite Cloud Climatology Project,
the Moderate Resolution Imaging Spectroradiometer on board Terra and
Aqua satellites, and conventional ground observations. It is shown that
the FY-2C cloud mask performs consistently with other cloud mask
products over Southeast Asia. In the boreal winter, the whole domain is
dry with little cloudiness. More extensive cloudiness can be observed
over the Sichuan Basin, in the East China Sea and the South China Sea,
along the northwestern border of China, and around the ITCZ in the
Southern Hemisphere. In the boreal summer, the summer monsoon is the
dominant system for the studied domain, which is generally humid with
extensive cloudiness, corresponding to zones of strong convective
activities. Results also reveal considerable discrepancies among
different cloud products over extended areas of north China and
Mongolia. The Sichuan Basin is another region of large discrepancies
among the four cloud products. Diurnal cycles of FY-2C cloudiness for
the four seasons of a year are analyzed. The diurnal range of cloudiness
is generally larger over land than over ocean. Remarkable diurnal
variation is found over the Tibetan Plateau, the northern part of the
Indian Peninsula, and central Asia where there is generally less
precipitation. The peaks of diurnal cycle of cloudiness appear around
local noon over the subtropical land, in the morning over the Indian
Peninsula, and in the afternoon near the equator.
}},
doi = {10.1029/2008JD011422},
adsurl = {http://adsabs.harvard.edu/abs/2009JGRD..11417207J},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009MWRv..137.1898K,
author = {{Ke}, Z. and {Zhang}, P. and {Dong}, W. and {Li}, L.},
title = {{A New Way to Improve Seasonal Prediction by Diagnosing and Correcting the Intermodel Systematic Errors}},
journal = {Monthly Weather Review},
year = 2009,
month = jun,
volume = 137,
pages = {1898-1907},
doi = {10.1175/2008MWR2676.1},
adsurl = {http://adsabs.harvard.edu/abs/2009MWRv..137.1898K},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009GeoRL..3612606L,
author = {{Lenton}, A. and {Codron}, F. and {Bopp}, L. and {Metzl}, N. and
{Cadule}, P. and {Tagliabue}, A. and {Le Sommer}, J.},
title = {{Stratospheric ozone depletion reduces ocean carbon uptake and enhances ocean acidification}},
journal = {\grl},
keywords = {Biogeosciences: Carbon cycling (4806), Biogeosciences: Climate dynamics (1620), Biogeosciences: Modeling, Biogeosciences: Biosphere/atmosphere interactions (0315)},
year = 2009,
month = jun,
volume = 36,
eid = {L12606},
pages = {12606},
abstract = {{Observational and atmospheric inversion studies find that the strength
of the Southern Ocean carbon dioxide (CO$_{2}$) sink is not
increasing, despite rising atmospheric CO$_{2}$. However, this is
yet to be captured by contemporary coupled-climate-carbon-models used to
predict future climate. We show that by accounting for stratospheric
ozone depletion in a coupled-climate-carbon-model, the ventilation of
carbon rich deep water is enhanced through stronger winds, increasing
surface water CO$_{2}$ at a rate in good agreement with observed
trends. We find that Southern Ocean uptake is reduced by 2.47 PgC
(1987-2004) and is consistent with atmospheric inversion studies. The
enhanced ventilation also accelerates ocean acidification, despite
lesser Southern Ocean CO$_{2}$ uptake. Our results link two
important anthropogenic changes: stratospheric ozone depletion and
greenhouse gas increases; and suggest that studies of future climate
that neglect stratospheric ozone depletion likely overestimate regional
and global oceanic CO$_{2}$ uptake and underestimate the impact of
ocean acidification.
}},
doi = {10.1029/2009GL038227},
adsurl = {http://adsabs.harvard.edu/abs/2009GeoRL..3612606L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009GeCAS..73R1414W,
author = {{Wang}, X.~C. and {Li}, X.~H. and {Li}, J. and {Li}, Z.~X. and
{Li}, W.~X.},
title = {{Nature of mantle lithological heterogenity and its role in generation of ca. 825Ma komatiitic basalts, South China}},
journal = {Geochimica et Cosmochimica Acta Supplement},
year = 2009,
month = jun,
volume = 73,
pages = {1414},
adsurl = {http://adsabs.harvard.edu/abs/2009GeCAS..73R1414W},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009JCli...22.3993G,
author = {{Gastineau}, G. and {Li}, L. and {Le Treut}, H.},
title = {{The Hadley and Walker Circulation Changes in Global Warming Conditions Described by Idealized Atmospheric Simulations}},
journal = {Journal of Climate},
year = 2009,
volume = 22,
pages = {3993},
doi = {10.1175/2009JCLI2794.1},
adsurl = {http://adsabs.harvard.edu/abs/2009JCli...22.3993G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2009JApMC..48.1142P,
author = {{Plana-Fattori}, A. and {Brogniez}, G. and {Chervet}, P. and
{Haeffelin}, M. and {Lado-Bordowsky}, O. and {Morille}, Y. and
{Parol}, F. and {Pelon}, J. and {Roblin}, A. and {Sèze}, G. and
{Stubenrauch}, C.},
title = {{Comparison of High-Cloud Characteristics as Estimated by Selected Spaceborne Observations and Ground-Based Lidar Datasets}},
journal = {Journal of Applied Meteorology and Climatology},
year = 2009,
volume = 48,
pages = {1142},
doi = {10.1175/2009JAMC1964.1},
adsurl = {http://adsabs.harvard.edu/abs/2009JApMC..48.1142P},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
