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Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part I: the representation of the MJO

Hirons, L. C. , Inness, P., Vitart, F. and Bechtold, P. (2013) Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part I: the representation of the MJO. Quarterly Journal of the Royal Meteorological Society, 139 (675). pp. 1417-1426. ISSN 1477-870X

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To link to this article DOI: 10.1002/qj.2060

Abstract/Summary

As a major mode of intraseasonal variability, which interacts with weather and climate systems on a near-global scale, the Madden – Julian Oscillation (MJO) is a crucial source of predictability for numerical weather prediction (NWP) models. Despite its global significance and comprehensive investigation, improvements in the representation of the MJO in an NWP context remain elusive. However, recent modifications to the model physics in the ECMWF model led to advances in the representation of atmospheric variability and the unprecedented propagation of the MJO signal through the entire integration period. In light of these recent advances, a set of hindcast experiments have been designed to assess the sensitivity of MJO simulation to the formulation of convection. Through the application of established MJO diagnostics, it is shown that the improvements in the representation of the MJO can be directly attributed to the modified convective parametrization. Furthermore, the improvements are attributed to the move from a moisture-convergent- to a relative-humidity-dependent formulation for organized deep entrainment. It is concluded that, in order to understand the physical mechanisms through which a relative-humidity-dependent formulation for entrainment led to an improved simulation of the MJO, a more process-based approach should be taken. T he application of process-based diagnostics t o t he hindcast experiments presented here will be the focus of Part II of this study.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > NCAS
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:31398
Publisher:Royal Meteorological Society

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