lmd_Bony2001.bib
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@article{2001JAtS...58.3158B,
author = {{Bony}, S. and {Emanuel}, K.~A.},
title = {{A Parameterization of the Cloudiness Associated with Cumulus Convection; Evaluation Using TOGA COARE Data.}},
journal = {Journal of Atmospheric Sciences},
year = 2001,
month = nov,
volume = 58,
pages = {3158-3183},
abstract = {{A new parameterization of the cloudiness associated with cumulus
convection is proposed for use in climate models. It is based upon the
idea that the convection scheme predicts the local concentration of
condensed water (the in-cloud water content) produced at the subgrid
scale, and that a statistical cloud scheme predicts how this condensed
water is spatially distributed within the domain. The cloud scheme uses
a probability distribution function (PDF) of the total water whose
variance and skewness coefficient are diagnosed from the amount of
condensed water produced at the subgrid scale by cumulus convection and
at the large scale by supersaturation, from the degree of saturation of
the environment, and from the lower bound of the total water
distribution that is taken equal to zero.This parameterization is used
in a single-column model forced by the Tropical Ocean Global Atmosphere
Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) data, and
including the cumulus convection scheme of Emanuel whose humidity
prediction has been optimized using these data. Simulations are carried
out during the 120 days of operation of the TOGA COARE intensive
observation period. The model is able to reproduce some of the main
characteristics of the cloudiness observed over the warm pool. This
includes the occurrence of different populations of clouds (shallow,
midlevel, and deep convective), a minimum cloud cover between 600 and
800 hPa, some relationship between the distribution of cloud tops and
the presence of stable atmospheric layers, the formation of long-lasting
upper-tropospheric anvils associated with the maturation of the
convective cloud systems, and the presence of an extensive layer of thin
cirrus clouds just below the tropopause. Nevertheless, shallow-level
clouds are likely to be underestimated. The behavior of the predicted
cloud fields is consistent with some statistical features suggested by
cloud-resolving model simulations of tropical cloud systems over oceans.
The radiative fluxes calculated interactively by the model from the
predicted profiles of humidity, temperature, and clouds are in
reasonable agreement with satellite data. Sea surface temperatures
predicted by the model using its own radiative and turbulent fluxes
calculated at the ocean surface differ from observations by a few tenths
of a degree.Sensitivity tests show that the performance of the
cloudiness parameterization does not critically depend upon the choice
of the PDF. On the other hand, they show that the prediction of
radiative fluxes is improved when the statistical moments of the PDF are
predicted from both large-scale variables and subgrid-scale convective
activity rather than from large-scale variables only.
}},
doi = {10.1175/1520-0469(2001)058<3158:APOTCA>2.0.CO;2},
adsurl = {http://adsabs.harvard.edu/abs/2001JAtS...58.3158B},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2001ClDy...17..905W,
author = {{Webb}, M. and {Senior}, C. and {Bony}, S. and {Morcrette}, J.-J.
},
title = {{Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models}},
journal = {Climate Dynamics},
year = 2001,
volume = 17,
pages = {905-922},
abstract = {{This study compares radiative fluxes and cloudiness fields from three
general circulation models (the HadAM4 version of the Hadley Centre
Unified model, cycle 16r2 of the ECMWF model and version LMDZ 2.0 of the
LMD GCM), using a combination of satellite observations from the Earth
Radiation Budget Experiment (ERBE) and the International Satellite Cloud
Climatology Project (ISCCP). To facilitate a meaningful comparison with
the ISCCP C1 data, values of column cloud optical thickness and cloud
top pressure are diagnosed from the models in a manner consistent with
the satellite view from space. Decomposing the cloud radiative effect
into contributions from low-medium- and high-level clouds reveals a
tendency for the models' low-level clouds to compensate for
underestimates in the shortwave cloud radiative effect caused by a lack
of high-level or mid-level clouds. The low clouds fail to compensate for
the associated errors in the longwave. Consequently, disproportionate
errors in the longwave and shortwave cloud radiative effect in models
may be taken as an indication that compensating errors are likely to be
present. Mid-level cloud errors in the mid-latitudes appear to depend as
much on the choice of the convection scheme as on the cloud scheme.
Convective and boundary layer mixing schemes require as much
consideration as cloud and precipitation schemes when it comes to
assessing the simulation of clouds by models. Two distinct types of
cloud feedback are discussed. While there is reason to doubt that
current models are able to simulate potential `cloud regime' type
feedbacks with skill, there is hope that a model capable of simulating
potential `cloud amount' type feedbacks will be achievable once the
reasons for the remaining differences between the models are understood.
}},
doi = {10.1007/s003820100157},
adsurl = {http://adsabs.harvard.edu/abs/2001ClDy...17..905W},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
