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lmd_Picon2005.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:"Picon"  ' -c year=2005 -c $type="ARTICLE" -oc lmd_Picon2005.txt -ob lmd_Picon2005.bib /home/WWW/LMD/public/Publis_LMDEMC3.link.bib}}
@article{2005GeoRL..3219708B,
  author = {{Brogniez}, H. and {Roca}, R. and {Picon}, L.},
  title = {{Evaluation of the distribution of subtropical free tropospheric humidity in AMIP-2 simulations using METEOSAT water vapor channel data}},
  journal = {\grl},
  keywords = {Global Change: Atmosphere (0315, 0325), Global Change: Global climate models (3337, 4928), Global Change: Remote sensing (1855)},
  year = 2005,
  month = oct,
  volume = 32,
  eid = {L19708},
  pages = {19708},
  abstract = {{In the framework of the Atmospheric Model Intercomparison Project (AMIP)
phase 2, we have established a diagnostic of the free tropospheric
humidity (FTH) distribution using METEOSAT data over the 1984-1995
period for 14 climate models. The methodology of evaluation follows a
two step ``model-to-satellite'' approach. First the raw METEOSAT ``Water
Vapor'' radiances are simulated from the model profiles of temperature
and humidity using the RTTOV-7 radiative transfer model. Second, the
radiances are converted into FTH using the same coefficients as in the
satellite product offering a direct comparison. The analysis is focused
on the dry subtropical areas observed by METEOSAT: the Eastern
Mediterranean and the tropical South Atlantic Ocean. Most of the models
reproduce the observed seasonal cycle both in terms of phasing and
magnitude, despite an overall moist bias. A few models are in close
agreement with the satellite data. The magnitude of the satellite
estimated inter-annual variability is also generally captured by models.
Again, a small subset of models shows close agreement with the
observations. This comparison suggests general improvements of the
models with respect to the AMIP-1 simulations.
}},
  doi = {10.1029/2005GL024341},
  adsurl = {http://adsabs.harvard.edu/abs/2005GeoRL..3219708B},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2005MAP....90...49R,
  author = {{Roca}, R. and {Louvet}, S. and {Picon}, L. and {Desbois}, M.
	},
  title = {{A study of convective systems, water vapor and top of the atmosphere cloud radiative forcing over the Indian Ocean using INSAT-1B and ERBE data}},
  journal = {Meteorology and Atmospheric Physics},
  year = 2005,
  month = sep,
  volume = 90,
  pages = {49-65},
  abstract = {{The distribution of cloud radiative forcing (CRF) at the top of the
atmosphere over the Indian Ocean is investigated using satellite
observations. Two key regions are considered: The eastern Indian Ocean
and the Bay of Bengal which experience maximum upper-level cloudiness in
winter and summer respectively. It is found that longwave CRF in the Bay
of Bengal during summer is similar to that over the eastern Indian Ocean
during winter. On the other hand shortwave CRF magnitude is larger in
the Bay of Bengal. These differences explain the net CRF difference
between the two regions. The stronger shortwave forcing seems to be
related to the Upper-Level Cloudiness being larger over the Bay than
over the eastern Indian Ocean. The reasons for the longwave CRF
similarities are analysed in more details. Using the results from a
convective system classification method, it is first shown that the
longwave radiative properties of the individual systems do not vary much
from one region to another. The distribution of the different kind of
systems, a proxy for the vertical cloudiness structure, does not either
indicate strong difference between the regions. It is then proposed that
the substantial precipitable water vapour amount observed over the Bay
of Bengal damps the effects of the upper-level cloudiness on radiation
compared to the relatively dryer eastern Indian Ocean area; yielding to
similar LW CRF in both region despite more Upper-Level Cloudiness over
the Bay of Bengal. These observations are supported by idealised
radiative transfer computations. The distribution of cloudiness and
radiative forcing is then analysed over the whole tropical Indian Ocean
for each season. July is characterized by a low longwave CRF regime
(relative to January) over the most convectively active part of the
Ocean. The non linear damping effect of water vapor on longwave CRF is
also shown to contribute to this regime. Overall, this study reaffirms
the need for simultaneous documentation of the cloud systems properties
together with their moist environment in order to understand the overall
net radiative signature of tropical convection at the top of the
atmosphere (TOA).
}},
  doi = {10.1007/s00703-004-0098-3},
  adsurl = {http://adsabs.harvard.edu/abs/2005MAP....90...49R},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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