lmd_Musat2005.bib

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@article{2005JGRD..11015S02Z,
  author = {{Zhang}, M.~H. and {Lin}, W.~Y. and {Klein}, S.~A. and {Bacmeister}, J.~T. and 
	{Bony}, S. and {Cederwall}, R.~T. and {Del Genio}, A.~D. and 
	{Hack}, J.~J. and {Loeb}, N.~G. and {Lohmann}, U. and {Minnis}, P. and 
	{Musat}, I. and {Pincus}, R. and {Stier}, P. and {Suarez}, M.~J. and 
	{Webb}, M.~J. and {Wu}, J.~B. and {Xie}, S.~C. and {Yao}, M.-S. and 
	{Zhang}, J.~H.},
  title = {{Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements}},
  journal = {Journal of Geophysical Research (Atmospheres)},
  keywords = {Atmospheric Processes: Clouds and cloud feedbacks, Atmospheric Processes: Global climate models (1626, 4928), Atmospheric Processes: Theoretical modeling, Global Change: Global climate models (3337, Global Change: Climate dynamics (0429, 3309), climate models, cloud modeling, seasonal variation of clouds},
  year = 2005,
  month = aug,
  volume = 110,
  number = d9,
  eid = {D15S02},
  pages = {D15S02},
  abstract = {{To assess the current status of climate models in simulating clouds,
basic cloud climatologies from ten atmospheric general circulation
models are compared with satellite measurements from the International
Satellite Cloud Climatology Project (ISCCP) and the Clouds and Earth's
Radiant Energy System (CERES) program. An ISCCP simulator is employed in
all models to facilitate the comparison. Models simulated a four-fold
difference in high-top clouds. There are also, however, large
uncertainties in satellite high thin clouds to effectively constrain the
models. The majority of models only simulated 30-40\% of middle-top
clouds in the ISCCP and CERES data sets. Half of the models
underestimated low clouds, while none overestimated them at a
statistically significant level. When stratified in the optical
thickness ranges, the majority of the models simulated optically thick
clouds more than twice the satellite observations. Most models, however,
underestimated optically intermediate and thin clouds. Compensations of
these clouds biases are used to explain the simulated longwave and
shortwave cloud radiative forcing at the top of the atmosphere. Seasonal
sensitivities of clouds are also analyzed to compare with observations.
Models are shown to simulate seasonal variations better for high clouds
than for low clouds. Latitudinal distribution of the seasonal variations
correlate with satellite measurements at $\gt$0.9, 0.6-0.9, and -0.2-0.7
levels for high, middle, and low clouds, respectively. The seasonal
sensitivities of cloud types are found to strongly depend on the basic
cloud climatology in the models. Models that systematically
underestimate middle clouds also underestimate seasonal variations,
while those that overestimate optically thick clouds also overestimate
their seasonal sensitivities. Possible causes of the systematic cloud
biases in the models are discussed.
}},
  doi = {10.1029/2004JD005021},
  adsurl = {https://ui.adsabs.harvard.edu/abs/2005JGRD..11015S02Z},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@article{2005GeoRL..3221704R,
  author = {{Rimbu}, N. and {Dima}, M. and {Lohmann}, G. and {Musat}, I.
	},
  title = {{Seasonal prediction of Danube flow variability based on stable teleconnection with sea surface temperature}},
  journal = {\grl},
  keywords = {Global Change: Climate dynamics (0429, 3309), Global Change: Regional climate change, Hydrology: Climate impacts, Hydrology: Hydrometeorology, Atmospheric Processes: General circulation (1223)},
  year = 2005,
  month = nov,
  volume = 32,
  eid = {L21704},
  pages = {L21704},
  abstract = {{It is shown that spring Danube flow anomalies are significantly related
to winter SST anomalies from several key regions. These areas are
identified through stable teleconnections between flow and SST. A
forecast scheme is developed and applied to predict flow anomalies using
SST anomalies from these key regions. Small potential predictability of
winter flow anomalies from autumn sea surface temperature anomalies was
also detected. The predictability of the flow anomalies from summer and
autumn using SST from the previous seasons is limited by the instability
of teleconnections.
}},
  doi = {10.1029/2005GL024241},
  adsurl = {https://ui.adsabs.harvard.edu/abs/2005GeoRL..3221704R},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}