Inter-model comparison of sub-seasonal tropical variability in aquaplanet experimets: effect of a warm poolLeroux, S., Bellon, G., Roehrig, R., Caian, M., Klingaman, N. P. ORCID: https://orcid.org/0000-0002-2927-9303, Lafore, J.-P., Musat, I., Rio, C. and Tyteca, S. (2016) Inter-model comparison of sub-seasonal tropical variability in aquaplanet experimets: effect of a warm pool. Journal of Advances in Modeling Earth Systems, 8 (4). pp. 1526-1551. ISSN 1942-2466
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1002/2016MS000683 Abstract/SummaryThis study compares the simulation of sub-seasonal tropical variability by a set of six state-of-the-art AGCMs in two experiments in aqua-planet 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 sub-seasonal variability by given model is significantly influenced by the parameterization of sub-grid physical processes (most-likely cloud processes), both directly and through modulation of the mean state.
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