Open Access
Inter‐model comparison of subseasonal tropical variability in aquaplanet experiments: Effect of a warm pool
Author(s) -
Leroux Stephanie,
Bellon Gilles,
Roehrig Romain,
Caian Mihaela,
Klingaman Nicholas P.,
Lafore JeanPhilippe,
Musat Ionela,
Rio Catherine,
Tyteca Sophie
Publication year - 2016
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1002/2016ms000683
Subject(s) - madden–julian oscillation , equator , climatology , environmental science , atmospheric sciences , atmospheric model , atmosphere (unit) , convection , westerlies , meteorology , geology , physics , latitude , geodesy
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.