Climate Dynamics

, Volume 37, Issue 11–12, pp 2129–2141

Assessing the simulation and prediction of rainfall associated with the MJO in the POAMA seasonal forecast system

  • Andrew G. Marshall
  • Debra Hudson
  • Matthew C. Wheeler
  • Harry H. Hendon
  • Oscar Alves
Article

DOI: 10.1007/s00382-010-0948-2

Cite this article as:
Marshall, A.G., Hudson, D., Wheeler, M.C. et al. Clim Dyn (2011) 37: 2129. doi:10.1007/s00382-010-0948-2

Abstract

We assess the ability of the Predictive Ocean Atmosphere Model for Australia (POAMA) to simulate and predict weekly rainfall associated with the MJO using a 27-year hindcast dataset. After an initial 2-week atmospheric adjustment, the POAMA model is shown to simulate well, both in pattern and in intensity, the weekly-mean rainfall variation associated with the evolution of the MJO over the tropical Indo-Pacific. The simulation is most realistic in December–February (austral summer) and least realistic in March–May (austral autumn). Regionally, the most problematic area is the Maritime Continent, which is a common problem area in other models. Coupled with our previous demonstration of the ability of POAMA to predict the evolution of the large-scale structure of the MJO for up to about 3 weeks, this ability to simulate the regional rainfall evolution associated with the MJO translates to enhanced predictability of rainfall regionally throughout much of the tropical Indo-Pacific when the MJO is present in the initial conditions during October–March. We also demonstrate enhanced prediction skill of rainfall at up to 3 weeks lead time over the north-east Pacific and north Atlantic, which are areas of pronounced teleconnections excited by the MJO-modulation of tropical Indo-Pacific rainfall. Failure to simulate and predict the modulation of rainfall in such places as the Maritime Continent and tropical Australia by the MJO indicates, however, there is still much room for improvement of the prediction of the MJO and its teleconnections.

Keywords

MJO Intra-seasonal POAMA Climate model Simulation Prediction Predictability Forecast Probabilistic skill Rainfall Teleconnection 

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Andrew G. Marshall
    • 1
  • Debra Hudson
    • 2
  • Matthew C. Wheeler
    • 2
  • Harry H. Hendon
    • 2
  • Oscar Alves
    • 2
  1. 1.Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric ResearchHobart,Australia
  2. 2.Centre for Australian Weather and Climate Research, Bureau of MeteorologyMelbourneAustralia

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