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Assessing Predictive Potential Associated with the MJO during the Boreal Winter

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  • 1 Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland
  • | 2 Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
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Abstract

In this paper, the question of potential predictability in meteorological variables associated with skillful prediction of the Madden–Julian oscillation (MJO) during boreal winter is analyzed. The analysis is motivated by the fact that dynamical prediction systems are now capable of predicting MJO up to 30 days or earlier (measured in terms of anomaly correlation for RMM indices). Translating recent gains in MJO prediction skill and relating them back to potential for predicting meteorological variables—for example, precipitation and surface temperature—is not straightforward because of a chain of steps that go into the computation and evaluation of RMM indices. This paper assesses potential predictability in meteorological variables that could be attributed to skillful prediction of the MJO. The analysis is based on the observational data alone and assesses the upper limit of MJO-associated predictability that could be achieved.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jieshun Zhu, jieshun.zhu@noaa.gov

Abstract

In this paper, the question of potential predictability in meteorological variables associated with skillful prediction of the Madden–Julian oscillation (MJO) during boreal winter is analyzed. The analysis is motivated by the fact that dynamical prediction systems are now capable of predicting MJO up to 30 days or earlier (measured in terms of anomaly correlation for RMM indices). Translating recent gains in MJO prediction skill and relating them back to potential for predicting meteorological variables—for example, precipitation and surface temperature—is not straightforward because of a chain of steps that go into the computation and evaluation of RMM indices. This paper assesses potential predictability in meteorological variables that could be attributed to skillful prediction of the MJO. The analysis is based on the observational data alone and assesses the upper limit of MJO-associated predictability that could be achieved.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jieshun Zhu, jieshun.zhu@noaa.gov
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