lmd_Musat2016.bib

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@article{2016JAMES...8.1526L,
  author = {{Leroux}, S. and {Bellon}, G. and {Roehrig}, R. and {Caian}, M. and 
	{Klingaman}, N.~P. and {Lafore}, J.-P. and {Musat}, I. and {Rio}, C. and 
	{Tyteca}, S.},
  title = {{Inter-model comparison of subseasonal tropical variability in aquaplanet experiments: Effect of a warm pool}},
  journal = {Journal of Advances in Modeling Earth Systems},
  keywords = {aquaplanet, tropical variability, inter-model comparison, Madden Julian Oscillation, MJO},
  year = 2016,
  month = dec,
  volume = 8,
  pages = {1526-1551},
  abstract = {{This study compares the simulation of subseasonal tropical variability
by a set of six state-of-the-art AGCMs in two experiments in aquaplanet
configuration: a zonally symmetric experiment, and an experiment with a
warm pool centered on the equator. In all six models, the presence of
the warm pool generates zonal asymmetries in the simulated mean states
in the form of a ``Gill-type'' response, made more complex by feedbacks
between moisture, convective heating and circulation. Noticeable
differences appear from one model to another. Only half the models
simulate mean low-level equatorial westerlies over the warm pool area.
The presence of the warm pool can also favor the development of
large-scale variability consistent with observed Madden-Julian
Oscillation (MJO) characteristics, but this happens only in half the
models. Our results do not support the idea that the presence of the
warm pool and/or of mean low-level equatorial westerlies are sufficient
conditions for MJO-like variability to arise in the models. Comparing
spectral characteristics of the simulated Convectively Coupled
Equatorial Waves (CCEWs) in the aquaplanet experiments and the
corresponding coupled atmosphere-ocean (i.e., CMIP) and atmosphere-only
(i.e., AMIP) simulations, we also show that there is more consistency
for a given model across its configurations, than for a given
configuration across the six models. Overall, our results confirm that
the simulation of subseasonal variability by given model is
significantly influenced by the parameterization of subgrid physical
processes (most-likely cloud processes), both directly and through
modulation of the mean state.
}},
  doi = {10.1002/2016MS000683},
  adsurl = {https://ui.adsabs.harvard.edu/abs/2016JAMES...8.1526L},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}